The Definition of Informatics Competencies in Finnish Healthcare and Social Welfare Education

Finland is a world leader in the use of public electronic services. Continuous improvement to competencies is a prerequisite for the success of digitalisation in the service development sector. The increasing use of information technology in health and social care needs to be taken into account in the education of the health and social care sector work force. The mandate of the national SotePeda 24/7 project is to identify and define the informatics competencies required for multidisciplinary education of this sector in Finland. The project has adapted international recommendations for use in the national context. The national recommendation covers 12 areas of competency and related content. In addition to defining competencies, the project has produced a toolbox of materials for use by educators of these topics in universities that cover applied sciences and lifelong learning. The results of the project are expected to significantly improve the preparedness of graduating health and social care and related engineering and business sector students to make full use information technology, all of which benefits the national health and social welfare system.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: BioMediTech, Tampere Uni. of Applied Sci., Laurea University of Applied Sciences, University of Eastern Finland
Contributors: Värri, A., Tiainen, M., Rajalahti, E., Kinnunen, U. M., Saarni, L., Ahonen, O.
Number of pages: 5
Pages: 1143-1147
Publication date: 16 Jun 2020

Host publication information

Title of host publication: Digital Personalized Health and Medicine : Proceedings of MIE 2020
Publisher: IOP Press
ISBN (Print): 978-1-64368-082-8
ISBN (Electronic): 978-1-64368-083-5

Publication series

Name: Studies in Health Technology and Informatics
Volume: 270
ISSN (Print): 0926-9630
ASJC Scopus subject areas: Biomedical Engineering, Health Informatics, Health Information Management
Keywords: competence, education, health care, informatics, information technology, skill, social care
Electronic versions: 
Source: Scopus
Source ID: 85086905812

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

TinderMIX: Time-dose integrated modelling of toxicogenomics data

BACKGROUND: Omics technologies have been widely applied in toxicology studies to investigate the effects of different substances on exposed biological systems. A classical toxicogenomic study consists in testing the effects of a compound at different dose levels and different time points. The main challenge consists in identifying the gene alteration patterns that are correlated to doses and time points. The majority of existing methods for toxicogenomics data analysis allow the study of the molecular alteration after the exposure (or treatment) at each time point individually. However, this kind of analysis cannot identify dynamic (time-dependent) events of dose responsiveness. RESULTS: We propose TinderMIX, an approach that simultaneously models the effects of time and dose on the transcriptome to investigate the course of molecular alterations exerted in response to the exposure. Starting from gene log fold-change, TinderMIX fits different integrated time and dose models to each gene, selects the optimal one, and computes its time and dose effect map; then a user-selected threshold is applied to identify the responsive area on each map and verify whether the gene shows a dynamic (time-dependent) and dose-dependent response; eventually, responsive genes are labelled according to the integrated time and dose point of departure. CONCLUSIONS: To showcase the TinderMIX method, we analysed 2 drugs from the Open TG-GATEs dataset, namely, cyclosporin A and thioacetamide. We first identified the dynamic dose-dependent mechanism of action of each drug and compared them. Our analysis highlights that different time- and dose-integrated point of departure recapitulates the toxicity potential of the compounds as well as their dynamic dose-dependent mechanism of action.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: BioMediTech, Tampere University, University of Helsinki
Contributors: Serra, A., Fratello, M., Del Giudice, G., Saarimäki, L. A., Paci, M., Federico, A., Greco, D.
Publication date: 1 May 2020
Peer-reviewed: Yes

Publication information

Journal: GigaScience
Volume: 9
Issue number: 5
ISSN (Print): 2047-217X
Original language: English
ASJC Scopus subject areas: Computer Science Applications, Health Informatics
Keywords: BMD, dose-response, dynamic dose-dependent, gene expression, integrated modeling, mechanism of action, MOA, time course, toxicogenomics
Electronic versions: 
Source: Scopus
Source ID: 85085537918

Research output: Contribution to journalArticleScientificpeer-review

Fusion enhancement for tracking of respiratory rate through intrinsic mode functions in photoplethysmography

Decline in respiratory regulation demonstrates the primary forewarning for the onset of physiological aberrations. In clinical environment, the obtrusive nature and cost of instrumentation have retarded the integration of continuous respiration monitoring for standard practice. Photoplethysmography (PPG) presents a non-invasive, optical method of assessing blood flow dynamics in peripheral vasculature. Incidentally, respiration couples as a surrogate constituent in PPG signal, justifying respiratory rate (RR) estimation. The physiological processes of respiration emerge as distinctive oscillations that are fluctuations in various parameters extracted from PPG signal. We propose a novel algorithm designed to account for intermittent diminishment of the respiration induced variabilities (RIV) by a fusion-based enhancement of wavelet synchrosqueezed spectra. We have combined the information on intrinsic mode functions (IMF) of five RIVs to enhance mutually occurring, instantaneous frequencies of the spectra. The respiration rate estimate is obtained by tracking the spectral ridges with a particle filter. We have evaluated the method with a dataset recorded from 29 young adult subjects (mean: 24.17 y, SD: 4.19 y) containing diverse, voluntary, and periodically metronome-assisted respiratory patterns. Bayesian inference on fusion-enhanced Respiration Induced Frequency Variability (RIFV) indicated MAE and RMSE of 1.764 and 3.996 BPM, respectively. The fusion approach was deemed to improve MAE and RMSE of RIFV by 0.185 BPM (95% HDI: 0.0285-0.3488, effect size: 0.548) and 0.250 BPM (95% HDI: 0.0733-0.431, effect size: 0.653), respectively, with further pronounced improvements to other RIVs. We conclude that the fusion of variability signals proves important to IMF localization in the spectral estimation of RR.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: BioMediTech, Research group: Sensor Technology and Biomeasurements (STB)
Contributors: Pirhonen, M., Vehkaoja, A.
Number of pages: 11
Publication date: 2020
Peer-reviewed: Yes

Publication information

Journal: Biomedical Signal Processing and Control
Volume: 59
Article number: 101887
ISSN (Print): 1746-8094
Original language: English
ASJC Scopus subject areas: Signal Processing, Health Informatics
Keywords: Particle filtering, Photoplethysmography, Respiration rate, Spectral fusion, Synchrosqueezing
URLs: 

Bibliographical note

INT=bmte,"Pirhonen, Mikko"

Source: Scopus
Source ID: 85079696106

Research output: Contribution to journalArticleScientificpeer-review

Optimized wake-up scheme with bounded delay for energy-efficient MTC

The limitations of state-of-the-art cellular modems prevent achieving low-power and low-latency Machine Type Communications (MTC) based on current power saving mechanisms alone. Recently, the concept of wake-up scheme has been proposed to enhance battery lifetime of 5G devices, while reducing the buffering delay. The existing wake-up algorithms use static operational parameters that are determined by the radio access network at the start of the userâ™s session. In this paper, the average power consumption of the wake-up enabled MTC UE is modeled by using a semi-Markov process and then optimized through a delay-constrained optimization problem, by which the optimal wake-up cycle is obtained in closed form. Numerical results show that the proposed solution reduces the power consumption of an optimized Discontinuous Reception (DRX) scheme by up to 40% for a given delay requirement.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Electrical Engineering, Helsinki RanD Center, Huawei Technologies Oy (Finland). Co. Ltd., Centre Tecnologic de Telecomunicacions de Catalunya
Contributors: Rostami, S., Lagen, S., Costa, M., DIni, P., Valkama, M.
Publication date: 1 Dec 2019

Host publication information

Title of host publication: 2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings
Publisher: IEEE
Article number: 9013534
ISBN (Electronic): 9781728109626
ASJC Scopus subject areas: Computer Networks and Communications, Hardware and Architecture, Information Systems, Signal Processing, Information Systems and Management, Safety, Risk, Reliability and Quality, Media Technology, Health Informatics
Keywords: 5G, DRX, Energy efficiency, MTC, Wake-up schemes

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Prototyping directional UAV-based wireless access and backhaul systems

Providing sufficient mobile coverage during mass public events or critical situations is a highly challenging task for the network operators. To fulfill the extreme capacity and coverage demands within a limited area, several augmenting solutions might be used. Among them, novel technologies like a fleet of compact base stations mounted on Unmanned Aerial Vehicles (UAVs) are gaining momentum because of their time- and cost- efficient deployment. Despite the fact that the concept of aerial wireless access networks has been investigated recently in many research studies, there are still numerous practical aspects that require further understanding and extensive evaluation. Taking this as a motivation, in this paper, we develop the concept of continuous wireless coverage provisioning by the means of UAVs and assess its usability in mass scenarios with thousands of users. With our system-level simulations as well as a measurement campaign, we take into account a set of important parameters including weather conditions, UAV speed, weight, power consumption, and millimeter- wave (mmWave) antenna configuration. As a result, we provide more realistic data about the performance of the access and backhaul links together with the practical lessons learned about the design and real-world applicability of the UAV-enabled wireless access networks.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Electrical Engineering, Department of Telecommunications, Brno University of Technology
Contributors: Gerasimenko, M., Pokorny, J., Schneider, T., Sirjov, J., Andreev, S., Hosek, J.
Publication date: 1 Dec 2019

Host publication information

Title of host publication: 2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings
Publisher: IEEE
Article number: 9014228
ISBN (Electronic): 9781728109626
ASJC Scopus subject areas: Computer Networks and Communications, Hardware and Architecture, Information Systems, Signal Processing, Information Systems and Management, Safety, Risk, Reliability and Quality, Media Technology, Health Informatics

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca 2+ Transient Profiles

Background Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previously observed that a few genetic cardiac diseases can be separated from each other and healthy controls by applying machine learning to Ca 2+ transient signals measured from iPSC-derived cardiomyocytes (CMs). Objectives For the current research, 419 hypertrophic cardiomyopathy (HCM) transient signals and 228 long QT syndrome (LQTS) transient signals were measured. HCM signals included data recorded from iPSC-CMs carrying either α-tropomyosin, i.e., TPM1 (HCMT) or MYBPC3 or myosin-binding protein C (HCMM) mutation and LQTS signals included data recorded from iPSC-CMs carrying potassium voltage-gated channel subfamily Q member 1 (KCNQ1) mutation (long QT syndrome 1 [LQT1]) or KCNH2 mutation (long QT syndrome 2 [LQT2]). The main objective was to study whether and how effectively HCMM and HCMT can be separated from each other as well as LQT1 from LQT2. Methods After preprocessing those Ca 2+ signals where we computed peak waveforms we then classified the two mutations of both disease pairs by using several different machine learning methods. Results We obtained excellent classification accuracies of 89% for HCM and even 100% for LQT at their best. Conclusion The results indicate that the methods applied would be efficient for the identification of these genetic cardiac diseases.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: BioMediTech, Tampere University, Tampere University Hospital
Contributors: Joutsijoki, H., Penttinen, K., Juhola, M., Aalto-Setälä, K.
Number of pages: 12
Pages: 167-178
Publication date: 1 Nov 2019
Peer-reviewed: Yes

Publication information

Journal: Methods of Information in Medicine
Volume: 58
Issue number: 4-5
ISSN (Print): 0026-1270
Ratings: 
  • Scopus rating (2019): CiteScore 3.5 SJR 0.588 SNIP 0.788
Original language: English
ASJC Scopus subject areas: Health Informatics, Advanced and Specialised Nursing, Health Information Management
Keywords: calcium transient signal, genetic cardiac diseases, machine learning, mutations
Source: Scopus
Source ID: 85083905746

Research output: Contribution to journalArticleScientificpeer-review

Red Alert: Break-Glass Protocol to Access Encrypted Medical Records in the Cloud

Availability of medical records during an emergency situation is of paramount importance since it allows healthcare professionals to access patient's data on time and properly plan the next steps that need to be taken. Cloud storage has the potential to provide a solution to the problem of data unavailability during an emergency situation. However, sharing medical records raises several concerns about security and privacy. In this paper, we study the problem of how to share encrypted patients' data during an emergency situation. To this end, we propose a protocol through which a team of healthcare professionals can securely decrypt the medical records of a patient who is under an emergency situation (e.g. acute stroke). Furthermore, our protocol ensures that a team of healthcare professionals will only have access to the patient's data for the time needed to complete a specific process related to the patient's situation (e.g. transfer patient to the hospital). In our study, the dynamically granting and revoking data access during an emergency treatment is the main novelty.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Computing Sciences, University of Amsterdam
Contributors: De Oliveira, M. T., Michalas, A., Groot, A. E., Marquering, H. A., Olabarriaga, S. D.
Publication date: 1 Oct 2019

Host publication information

Title of host publication: 2019 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2019
Publisher: IEEE
Article number: 9009598
ISBN (Electronic): 9781728104027
ASJC Scopus subject areas: Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, Human-Computer Interaction, Health Informatics, Health(social science)
Keywords: Attribute-Based Encryption, e-Health Privacy, Electronic Medical Records, Emergency care, Secure Cloud Storage

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Face verification and recognition for digital forensics and information security

In this paper, we present an extensive evaluation of face recognition and verification approaches performed by the European COST Action MULTI-modal Imaging of FOREnsic SciEnce Evidence (MULTI-FORESEE). The aim of the study is to evaluate various face recognition and verification methods, ranging from methods based on facial landmarks to state-of-the-art off-the-shelf pre-trained Convolutional Neural Networks (CNN), as well as CNN models directly trained for the task at hand. To fulfill this objective, we carefully designed and implemented a realistic data acquisition process, that corresponds to a typical face verification setup, and collected a challenging dataset to evaluate the real world performance of the aforementioned methods. Apart from verifying the effectiveness of deep learning approaches in a specific scenario, several important limitations are identified and discussed through the paper, providing valuable insight for future research directions in the field.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Computing Sciences, Inst. of Info. Sci. and Technol. of the Natl. Res. Cncl. of Italy (ISTI-CNR), University of Milan Bicocca, Department of Informatics, Aristotle University of Thessaloniki, University of Applied Sciences of Southern Switzerland
Contributors: Amato, G., Falchi, F., Gennaro, C., Massoli, F. V., Passalis, N., Tefas, A., Trivilini, A., Vairo, C.
Publication date: 1 Jun 2019

Host publication information

Title of host publication: 7th International Symposium on Digital Forensics and Security, ISDFS 2019
Publisher: IEEE
Editors: Varol, A., Karabatak, M., Varol, C., Teke, S.
ISBN (Electronic): 9781728128276
ASJC Scopus subject areas: Health Informatics, Pathology and Forensic Medicine, Computer Networks and Communications, Computer Science Applications, Safety, Risk, Reliability and Quality
Keywords: Deep learning, Face verification, Forensics, Security, Surveillance

Bibliographical note

EXT="Tefas, Anastasios"

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Societal impact as Cost-Benefit Analysis: Comparative analysis of two research infrastructures

The impact of basic science projects is more difficult to assess than that of science projects, which lead to direct applications. Especially, the benefits of fundamental science projects are less obvious and indirect than applied science (e.g. pharmaceutical or IT). Pure scientific quality does not tell anything about the societal and economical value of the project. Public resources used for funding the growing scientific research face scarcity, and choosing where to distribute the limited resources is difficult without tools to assess the impacts. Politicians and other decision makers are struggling to evaluate the benefits of supporting science projects. Therefore, it is essential to find methods to fairly measure the impacts of science projects into the surrounding society. One way of assessing societal impact is Cost-Benefit Analysis (CBA). This contribution explores CBA as a tool for societal impact assessment by reviewing and comparing two research infrastructures' assessments.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Industrial Engineering and Management, Research group: Center for Innovation and Technology Research, European Organization for Nuclear Research
Contributors: Magazinik, A., Bedolla, J. S., Lasheras, N. C., Mäkinen, S.
Publication date: 1 Jun 2019

Host publication information

Title of host publication: 2019 IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2019
Publisher: IEEE
ISBN (Electronic): 9781728134017
ASJC Scopus subject areas: Industrial and Manufacturing Engineering, Management of Technology and Innovation, Strategy and Management, Civil and Structural Engineering, Health Informatics, Health(social science), Computer Networks and Communications, Information Systems and Management
Keywords: Big Science Centre, research organisation, social impact assessment, societal impact assessment

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Error analysis of NOMA-based user cooperation with SWIPT

The present contribution analyzes the performance of non-orthogonal multiple access (NOMA)-based user cooperation with simultaneous wireless information and power transfer (SWIPT). In particular, we consider a two-user NOMA-based cooperative SWIPT scenario, in which the near user acts as a SWIPT-enabled relay that assists the farthest user. In this context, we derive analytic expressions for the pairwise error probability (PEP) of both users assuming the both amplify-and-forward (AF) and decode-and-forward (DF) relay protocols. The derived expressions are expressed in closed-form and have a tractable algebraic representation which renders them convenient to handle both analytically and numerically. In addition to this, we derive a simple asymptotic closed-form expression for the PEP in the high signal-to-noise ratio (SNR) regime which provide useful insights on the impact of the involved parameters on the overall system performance. Capitalizing on this, we subsequently quantify the maximum achievable diversity order of both users. It is shown that numerical and simulation results corroborate the derived analytic expressions. Furthermore, the offered results provide interesting insights into the error rate performance of each user, which are expected to be useful in future designs and deployments of NOMA based SWIPT systems.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Research group: Wireless Communications and Positioning, Electrical Engineering, Taiyuan University of Science and Technology, Khalifa University, University of Surrey, Center on Cyber-Physical Systems, Simon Fraser University
Contributors: Li, S., Bariah, L., Muhaidat, S., Sofotasios, P., Liang, J., Wang, A.
Number of pages: 7
Pages: 507-513
Publication date: 1 May 2019

Host publication information

Title of host publication: Proceedings - 15th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2019
Publisher: IEEE
ISBN (Electronic): 9781728105703
ASJC Scopus subject areas: Computer Networks and Communications, Computer Science Applications, Hardware and Architecture, Health Informatics, Instrumentation, Transportation, Communication
Keywords: NOMA, Wireless Power Transfer
Source: Scopus
Source ID: 85071915507

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open framework for mammography-based breast cancer risk assessment

In recent years, several studies have established a relationship between mammographic parenchymal patterns and breast cancer risk. However, there is a lack of publicly available data and software for objective comparison and clinical validation. This paper presents an open and adaptable implementation (OpenBreast v1.0) of a fully-Automatic computerized framework for mammographic image analysis for breast cancer risk assessment. OpenBreast implements mammographic image analysis in four stages: breast segmentation, detection of region-of-interests, feature extraction and risk scoring. For each stage, we provide implementations of several state-of-The-Art methods. The pipeline is tested on a set of 305 full-field digital mammography images corresponding to 84 patients (51 cases and 49 controls) from the breast cancer digital repository (BCDR). OpenBreast achieves a competitive AUC of 0.846 in breast cancer risk assessment. In addition, used jointly with widely accepted risk factors such as patient age and breast density, mammographic image analysis using OpenBreast shows a statistically significant improvement in performance with an AUC of 0.876 (\mathrm{p}<0.001). Our framework will be made publicly available and it is easy to incorporate new methods.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Computing Sciences, Research group: Vision, Universidad Industrial de Santander, Tampere University, Brigham and Women's Hospital
Contributors: Pertuz, S., Torres, G. F., Tamimi, R., Kämäräinen, J.
Publication date: 1 May 2019

Host publication information

Title of host publication: 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings
Publisher: IEEE
ISBN (Electronic): 9781728108483
ASJC Scopus subject areas: Artificial Intelligence, Signal Processing, Information Systems and Management, Biomedical Engineering, Health Informatics, Radiology Nuclear Medicine and imaging
Keywords: Breast cancer, Mammography, Parenchymal analysis, Risk assessment, Texture analysis

Bibliographical note

EXT="Pertuz, Said"

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Exploring associations between the self-reported values, well-being, and health behaviors of finnish citizens: Cross-sectional analysis of more than 100,000 web-survey responses

Background: Understanding the relationship between personal values, well-being, and health-related behavior could facilitate the development of engaging, effective digital interventions for promoting well-being and the healthy lifestyles of citizens. Although the associations between well-being and values have been quite extensively studied, the knowledge about the relationship between health behaviors and values is less comprehensive. Objective: The aim of this study was to assess retrospectively the associations between self-reported values and commitment to values combined with self-reported well-being and health behaviors from a large cross-sectional dataset. Methods: We analyzed 101,130 anonymous responses (mean age 44.78 years [SD 13.82]; 78.88%, 79,770/101,130 women) to a Finnish Web survey, which were collected as part of a national health promotion campaign. The data regarding personal values were unstructured, and the self-reported value items were classified into value types based on the Schwartz value theory and by applying principal component analysis. Logistic and multiple linear regression were used to explore the associations of value types and commitment to values with well-being factors (happiness, communal social activity, work, and family-related distress) and health behaviors (exercise, eating, smoking, alcohol consumption, and sleep). Results: Commitment to personal values was positively related to happiness (part r2=0.28), communal social activity (part r2=0.09), and regular exercise (part r2=0.06; P<.001 for all). Health, Power (social status and dominance), and Mental balance (self-acceptance) values had the most extensive associations with health behaviors. Regular exercise, healthy eating, and nonsmoking increased the odds of valuing Health by 71.7%, 26.8%, and 40.0%, respectively (P<.001 for all). Smoking, unhealthy eating, irregular exercise, and increased alcohol consumption increased the odds of reporting Power values by 27.80%, 27.78%, 24.66%, and 17.35%, respectively (P<.001 for all). Smoking, unhealthy eating, and irregular exercise increased the odds of reporting Mental balance values by 20.79%, 16.67%, and 15.37%, respectively (P<.001 for all). In addition, lower happiness levels increased the odds of reporting Mental balance and Power values by 24.12% and 20.69%, respectively (P<.001 for all). Conclusions: The findings suggest that commitment to values is positively associated with happiness and highlight various, also previously unexplored, associations between values and health behaviors.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: BioMediTech, VTT Technical Research Centre of Finland, Northeastern University, College of Computer & Information Science, Bouvé College of Health Sciences, Duodecim Medical Publications Ltd.
Contributors: Honka, A. M., Helander, E., Pavel, M., Jimison, H., Mustonen, P., Korhonen, I., Ermes, M.
Publication date: 1 Apr 2019
Peer-reviewed: Yes

Publication information

Journal: Journal of Medical Internet Research
Volume: 21
Issue number: 4
Article number: e12170
ISSN (Print): 1439-4456
Ratings: 
  • Scopus rating (2019): CiteScore 3.9 SJR 1.187 SNIP 1.549
Original language: English
ASJC Scopus subject areas: Health Informatics
Keywords: Cross-sectional survey, Happiness, Health behavior, Healthy lifestyle, Value orientation

Bibliographical note

EXT="Jimison, Holly"
EXT="Honka, Anita Marianne"

Source: Scopus
Source ID: 85067296712

Research output: Contribution to journalArticleScientificpeer-review

Identification of motor symptoms related to Parkinson disease using motion-tracking sensors at home (KÄVELI): Protocol for an observational case-control study

Background: Clinical characterization of motion in patients with Parkinson disease (PD) is challenging: Symptom progression, suitability of medication, and level of independence in the home environment can vary across time and patients. Appointments at the neurological outpatient clinic provide a limited understanding of the overall situation. In order to follow up these variations, longer-term measurements performed outside of the clinic setting could help optimize and personalize therapies. Several wearable sensors have been used to estimate the severity of symptoms in PD; however, longitudinal recordings, even for a short duration of a few days, are rare. Home recordings have the potential benefit of providing a more thorough and objective follow-up of the disease while providing more information about the possible need to change medications or consider invasive treatments. Objective: The primary objective of this study is to collect a dataset for developing methods to detect PD-related symptoms that are visible in walking patterns at home. The movement data are collected continuously and remotely at home during the normal lives of patients with PD as well as controls. The secondary objective is to use the dataset to study whether the registered medication intakes can be identified from the collected movement data by looking for and analyzing short-term changes in walking patterns. Methods: This paper described the protocol for an observational case-control study that measures activity using three different devices: (1) a smartphone with a built-in accelerometer, gyroscope, and phone orientation sensor, (2) a Movesense smart sensor to measure movement data from the wrist, and (3) a Forciot smart insole to measure the forces applied on the feet. The measurements are first collected during the appointment at the clinic conducted by a trained clinical physiotherapist. Subsequently, the subjects wear the smartphone at home for 3 consecutive days. Wrist and insole sensors are not used in the home recordings. Results: Data collection began in March 2018. Subject recruitment and data collection will continue in spring 2019. The intended sample size was 150 subjects. In 2018, we collected a sample of 103 subjects, 66 of whom were diagnosed with PD. Conclusions: This study aims to produce an extensive movement-sensor dataset recorded from patients with PD in various phases of the disease as well as from a group of control subjects for effective and impactful comparison studies. The study also aims to develop data analysis methods to monitor PD symptoms and the effects of medication intake during normal life andoutside of the clinic setting. Further applications of these methods may include using them as tools for health care professionals to monitor PD remotely and applying them to other movement disorders.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: BioMediTech, Industrial Engineering and Management, Satakunta Central Hospital, University of Helsinki, Hospital Services, Turku University of Applied Science, Satakunta University of Applied Sciences
Contributors: Jauhiainen, M., Puustinen, J., Mehrang, S., Ruokolainen, J., Holm, A., Vehkaoja, A., Nieminen, H.
Publication date: 1 Mar 2019
Peer-reviewed: Yes

Publication information

Journal: Journal of Medical Internet Research
Volume: 21
Issue number: 3
Article number: e12808
ISSN (Print): 1439-4456
Ratings: 
  • Scopus rating (2019): CiteScore 3.9 SJR 1.187 SNIP 1.549
Original language: English
ASJC Scopus subject areas: Health Informatics
Keywords: Gait, Home monitoring, Mobile phone, Movement analysis, Parkinson disease, Smartphone, Wearable sensors
Source: Scopus
Source ID: 85067441033

Research output: Contribution to journalArticleScientificpeer-review

Robocasting of Bioactive SiO2-P2O5-CaO-MgO-Na2O-K2O Glass Scaffolds

Bioactive silicate glass scaffolds were fabricated by a robocasting process in which all the movements of the printing head were programmed by compiling a script (text file). A printable ink made of glass powder and Pluronic F-127, acting as a binder, was extruded to obtain macroporous scaffolds with a grid-like three-dimensional structure. The scaffold architecture was investigated by scanning electron microscopy and microtomographic analysis, which allowed quantifying the microstructural parameters (pore size 150-180 μm and strut diameter 300 μm). In vitro tests in simulated body fluid (SBF) confirmed the apatite-forming ability (i.e., bioactivity) of the scaffolds. The compressive strength (around 10 MPa for as-produced scaffolds) progressively decreased during immersion in SBF (3.3 MPa after 4 weeks) but remains acceptable for bone repair applications. Taken together, these results (adequate porosity and mechanical strength as well as bioactivity) support the potential suitability of the prepared scaffolds for bone substitution.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: BioMediTech, Politecnico di Torino, Innovation Center Iceland (ICI)
Contributors: Baino, F., Barberi, J., Fiume, E., Orlygsson, G., Massera, J., Verné, E.
Publication date: 2019
Peer-reviewed: Yes

Publication information

Journal: Journal of Healthcare Engineering
Volume: 2019
Article number: 5153136
ISSN (Print): 2040-2295
Ratings: 
  • Scopus rating (2019): SJR 0.42 SNIP 1.052
Original language: English
ASJC Scopus subject areas: Biotechnology, Surgery, Biomedical Engineering, Health Informatics
Electronic versions: 
Source: Scopus
Source ID: 85065603850

Research output: Contribution to journalArticleScientificpeer-review

Eigen Posture Based Fall Risk Assessment System Using Kinect

Postural Instability (PI) is a major reason for fall in geriatric population as well as for people with diseases or disorders like Parkinson's, stroke etc. Conventional stability indicators like Berg Balance Scale (BBS) require clinical settings with skilled personnel's interventions to detect PI and finally classify the person into low, mid or high fall risk categories. Moreover these tests demand a number of functional tasks to be performed by the patient for proper assessment. In this paper a machine learning based approach is developed to determine fall risk with minimal human intervention using only Single Limb Stance exercise. The analysis is done based on the spatiotemporal dynamics of skeleton joint positions obtained from Kinect sensor. A novel posture modeling method has been applied for feature extraction along with some traditional time domain and metadata features to successfully predict the fall risk category. The proposed unobstrusive, affordable system is tested over 224 subjects and is able to achieve 75% mean accuracy on the geriatric and patient population.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Signal Processing, Tata Consultancy Services India
Contributors: Tripathy, S. R., Chakravarty, K., Sinha, A.
Number of pages: 4
Pages: 1-4
Publication date: 26 Oct 2018

Host publication information

Title of host publication: 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Volume: 2018-July
Publisher: IEEE
Article number: 8513263
ISBN (Electronic): 9781538636466
ASJC Scopus subject areas: Signal Processing, Biomedical Engineering, Computer Vision and Pattern Recognition, Health Informatics
Keywords: BBS, Eigenpose, EMD, Fall risk, Index Terms-Kinect
Source: Scopus
Source ID: 85056666030

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Identification of Parkinson's Disease Utilizing a Single Self-recorded 20-step Walking Test Acquired by Smartphone's Inertial Measurement Unit

Parkinson's disease (PD) is a degenerative and long-term disorder of the central nervous system, which often causes motor symptoms, e.g., tremor, rigidity, and slowness. Currently, the diagnosis of PD is based on patient history and clinical examination. Technology-derived decision support systems utilizing, for example, sensor-rich smartphones can facilitate more accurate PD diagnosis. These technologies could provide less obtrusive and more comfortable remote symptom monitoring. The recent studies showed that motor symptoms of PD can reliably be detected from data gathered via smartphones. The current study utilized an open-access dataset named 'mPower' to assess the feasibility of discriminating PD from non-PD by analyzing a single self-administered 20-step walking test. From this dataset, 1237 subjects (616 had PD) who were age and gender matched were selected and classified into PD and non-PD categories. Linear acceleration (ACC) and gyroscope (GYRO) were recorded by built-in sensors of smartphones. Walking bouts were extracted by thresholding signal magnitude area of the ACC signals. Features were computed from both ACC and GYRO signals and fed into a random forest classifier of size 128 trees. The classifier was evaluated deploying 100-fold cross-validation and provided an accumulated accuracy rate of 0.7 after 10k validations. The results show that PD and non-PD patients can be separated based on a single short-lasting self-administered walking test gathered by smartphones' built-in inertial measurement units.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Faculty of Biomedical Sciences and Engineering, Research group: Personal Health Informatics-PHI, Unit of Neurology, Satakunta Central Hospital
Contributors: Mehrang, S., Jauhiainen, M., Pietilä, J., Puustinen, J., Ruokolainen, J., Nieminen, H.
Number of pages: 4
Pages: 2913-2916
Publication date: 26 Oct 2018

Host publication information

Title of host publication: 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Volume: 2018-July
Publisher: Institute of Electrical and Electronics Engineers Inc.
Article number: 8512921
ISBN (Electronic): 9781538636466
ASJC Scopus subject areas: Signal Processing, Biomedical Engineering, Computer Vision and Pattern Recognition, Health Informatics
Source: Scopus
Source ID: 85056600537

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

The Accuracy of Atrial Fibrillation Detection from Wrist Photoplethysmography. A Study on Post-Operative Patients

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. Although not life-threatening itself, AF significantly increases the risk of stroke and myocardial infarction. Current tools available for screening and monitoring of AF are inadequate and an unobtrusive alternative, suitable for long-term use, is needed. This paper evaluates an atrial fibrillation detection algorithm based on wrist photoplethysmographic (PPG) signals. 29 patients recovering from surgery in the post-anesthesia care unit were monitored. 15 patients had sinus rhythm (SR, 67.5± 10.7 years old, 7 female) and 14 patients had AF (74.8± 8.3 years old, 8 female) during the recordings. Inter-beat intervals (IBI) were estimated from PPG signals. As IBI estimation is highly sensitive to motion or other types of noise, acceleration signals and PPG waveforms were used to automatically detect and discard unreliable IBI. AF was detected from windows of 20 consecutive IBI with 98.45±6.89% sensitivity and 99.13±1.79% specificity for 76.34±19.54% of the time. For the remaining time, no decision was taken due to the lack of reliable IBI. The results show that wrist PPG is suitable for long term monitoring and AF screening. In addition, this technique provides a more comfortable alternative to ECG devices.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Faculty of Biomedical Sciences and Engineering, Research group: Sensor Technology and Biomeasurements (STB), PulseOn SA, Tampere University Hospital
Contributors: Tarniceriu, A., Harju, J., Yousefi, Z. R., Vehkaoja, A., Parak, J., Yli-Hankala, A., Korhonen, I.
Number of pages: 4
Pages: 4844-4847
Publication date: 26 Oct 2018

Host publication information

Title of host publication: 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Volume: 2018-July
Publisher: IEEE
Article number: 8513197
ISBN (Electronic): 9781538636466
ASJC Scopus subject areas: Signal Processing, Biomedical Engineering, Computer Vision and Pattern Recognition, Health Informatics

Bibliographical note

INT=tut-bmt, "Yousefi, Zeinab Rezaei"

Source: Scopus
Source ID: 85056672654

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Cybersecurity Attacks and Defences for Unmanned Smart Ships

By 2020, unmanned ships such as remotely controlled boats and autonomous vessels would become operational, marking a technological revolution for the maritime industry. Such ships are expected to serve needs ranging from coastal ferries to open sea cargo handling. In this paper we detail the security vulnerabilities of such unmanned ships. The attack surface as well as motivations for attack attempts also are discussed to provide a perspective of how and why attacks are undertaken. Finally defence strategies are proposed as countermeasures.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Research area: Information security, Computing Sciences, Ericsson, F-Secure
Contributors: Silverajan, B., Ocak, M., Nagel, B.
Number of pages: 6
Pages: 15-20
Publication date: 1 Jul 2018

Host publication information

Title of host publication: Proceedings - IEEE 2018 International Congress on Cybermatics : 2018 IEEE Conferences on Internet of Things, Green Computing and Communications, Cyber, Physical and Social Computing, Smart Data, Blockchain, Computer and Information Technology, iThings/GreenCom/CPSCom/SmartData/Blockchain/CIT 2018
Publisher: IEEE
ISBN (Electronic): 9781538679753
ASJC Scopus subject areas: Business, Management and Accounting (miscellaneous), Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, Hardware and Architecture, Information Systems and Management, Health Informatics, Communication
Keywords: Autonomous vehicles, IoT, Security, Smart Ships

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Secure Firmware Updates for IoT: A Survey

The evolution of the Internet to an ubiquitous computing environment where massive amounts of devices will be connected. Sharing, receiving and acting upon data has brought in a problem of security. There are as many firmware and software update procedures as there are manufacturers. Therefore it would be good if a common solution could be found. We looked for suitable mechanisms in the past three years, to be used in Internet of Things networks as well as an up and coming research and standardization work. Our findings show that there indeed are good options for firmware update mechanisms that use state-of-The-Art technologies to deliver updates in a secure manner. While not all the mechanisms were specifically targeting deployment scenarios found in the Internet of Things, we still believe the concept of such update mechanism is suitable also for IoT use and thus can be adapted trivially to IoT networks and devices. We also propose a generic four-element model for secure firmware updates.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Research area: Information security, Computing Sciences
Contributors: Kolehmainen, A.
Number of pages: 6
Pages: 112-117
Publication date: 1 Jul 2018

Host publication information

Title of host publication: Proceedings - IEEE 2018 International Congress on Cybermatics : 2018 IEEE Conferences on Internet of Things, Green Computing and Communications, Cyber, Physical and Social Computing, Smart Data, Blockchain, Computer and Information Technology, iThings/GreenCom/CPSCom/SmartData/Blockchain/CIT 2018
Publisher: IEEE
ISBN (Electronic): 9781538679753
ASJC Scopus subject areas: Business, Management and Accounting (miscellaneous), Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, Hardware and Architecture, Information Systems and Management, Health Informatics, Communication
Keywords: Firmware updates, IoT, Lifecycle Management

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

The effect of percutaneous transluminal angioplasty of superficial femoral artery on pulse wave features

We aimed to analyze the effects of percutaneous transluminal angioplasty (PTA) of the superficial femoral artery (SFA) on arterial pulse waves (PWs). Altogether 24 subjects i.e. 48 lower limbs were examined including 26 treated lower limbs having abnormal ankle-to-brachial pressure index (ABI) (ABI<0.9 or ABI>1.3) and 22 non-treated lower limbs. The measurements were conducted in pre-, peri- and post-treatment phases as well as in follow-up visit after 1 month. Both ABI and toe pressures measured by standard equipment were used as reference values. PW-derived parameters include ratios of different peaks of the PW and time differences between them as well as aging index. Both treated and non-treated limbs were compared in pre- and post-treatment as well as follow-up visit conditions. The results were evaluated in terms of statistical tests, Bland-Altman-plots, free-marginal multirater κ-analysis and multiple linear regression analysis. PTA was found to cause small changes to the studied PW-derived parameters of the treated limb which were observed immediately after the treatment, but the changes were more pronounced in the follow-up visit. In addition, we observed that the endovascular instrumentation itself does not cause significant changes to the PW-derived parameters. The results show that PW-analysis could be a useful tool for monitoring the treatment-effect of the PTA. However, because the pre-treatment differences of the treated and non-treated limb were small, further studies with subjects having no arterial diseases are required. The study demonstrates the potential of the PW analysis in monitoring vascular abnormalities.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Faculty of Biomedical Sciences and Engineering, Research group: Sensor Technology and Biomeasurements (STB), Tampere University Hospital
Contributors: Peltokangas, M., Suominen, V., Vakhitov, D., Verho, J., Korhonen, J., Lekkala, J., Vehkaoja, A., Oksala, N.
Number of pages: 9
Pages: 274-282
Publication date: 1 May 2018
Peer-reviewed: Yes

Publication information

Journal: Computers in Biology and Medicine
Volume: 96
ISSN (Print): 0010-4825
Ratings: 
  • Scopus rating (2018): CiteScore 4.4 SJR 0.57 SNIP 1.169
Original language: English
ASJC Scopus subject areas: Computer Science Applications, Health Informatics
Keywords: Atherosclerosis, Electromechanical sensors, Peripheral arterial disease, Photoplethysmography, Pulse wave measurements
Electronic versions: 
URLs: 
Source: Scopus
Source ID: 85045471212

Research output: Contribution to journalArticleScientificpeer-review

Detection of beat-to-beat intervals from wrist photoplethysmography in patients with sinus rhythm and atrial fibrillation after surgery

Wrist photoplethysmography (PPG) allows unobtrusive monitoring of the heart rate (HR). PPG is affected by the capillary blood perfusion and the pumping function of the heart, which generally deteriorate with age and due to the presence of cardiac arrhythmia. The performance of wrist PPG in monitoring beat-to-beat HR in older patients with arrhythmia has not been reported earlier. We monitored PPG from wrist in 18 patients recovering from surgery in the post-anesthesia care unit, and evaluated the inter-beat interval (IBI) detection accuracy against ECG based R-to-R intervals (RRI). Nine subjects had sinus rhythm (SR, 68.0y ± 10.2y, 6 males) and nine subjects had atrial fibrillation (AF, 71.3y ± 7.8y, 4 males) during the recording. For the SR group, 99.44% of the beats were correctly identified, 2.39% extra beats were detected, and the mean absolute error (MAE) was 7.34 ms. For the AF group, 97.49% of the heartbeats were correctly identified, 2.26% extra beats were detected, and the MAE was 14.31 ms. IBI from the PPG were hence in close agreement with the ECG reference in both groups. The results suggest that wrist PPG provides a comfortable alternative to ECG during low motion and can be used for long-term monitoring and screening of AF episodes.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Faculty of Biomedical Sciences and Engineering, PulseOn SA, Tampere University Hospital, Pulseon Oy, Centre Suisse d'Electronique et de Microtechnique SA
Contributors: Tarniceriu, A., Harju, J., Vehkaoja, A., Parak, J., Delgado-Gonzalo, R., Renevey, P., Yli-Hankala, A., Korhonen, I.
Number of pages: 4
Pages: 133-136
Publication date: 6 Apr 2018

Host publication information

Title of host publication: 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018
Publisher: IEEE
ISBN (Electronic): 9781538624050
Source: Scopus
Source ID: 85050860184

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

A novel technique for analysis of postural information with wearable devices

These days, as many jobs involve sitting behind desks and working with computers for extended periods, more and more people are suffering from back problems. Maintenance of an appropriate posture may prevent future back problems. There are various medical methods for studying postures abnormalities of the back but most of these methods are limited to be utilized in diagnostics and follow-up of treatment and not used in a continuous or in a preventive manner. Therefore, designing and developing methods for measuring, analyzing and reporting of posture information, aimed for prevention of future back problems is of fundamental interest. In this work, a proof-of-concept system, including five accelerometer sensor units is presented. Additionally, an index, which we call spine inclination index (SII), is introduced and used for converting the raw data to meaningful presentable information. Initial evaluation includes measurements with six subjects. Subjects were asked to mimic accentuated kyphotic, straight and accentuated lordotic postures while sitting. Our results show that the designed device and SII index are able to distinguish between different postures very well. In addition, since this device measures the inclination angle of different spinal postures, its output can be directly compared with other widely used methods.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Faculty of Biomedical Sciences and Engineering, VTT Technical Research Centre of Finland, Tampere University Hospital
Contributors: Jeyhani, V., Mahdiani, S., Viik, J., Oksala, N., Vehkaoja, A.
Number of pages: 4
Pages: 30-33
Publication date: 2 Apr 2018

Host publication information

Title of host publication: 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2018
Publisher: IEEE
ISBN (Electronic): 9781538611098
ASJC Scopus subject areas: Health Informatics, Instrumentation, Computer Networks and Communications, Human-Computer Interaction, Biomedical Engineering
Source: Scopus
Source ID: 85049665171

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Improving hospital services based on patient experience data: Current feedback practices and future opportunities

Patient feedback is considered important for healthcare organizations. However, measurement and analysis of patient reported data is useful only if gathered insights are transformed into actions. This article focuses on gathering and utilization of patient experience data at hospitals with the aim of supporting the development of patient-centered services. The study was designed to explore both current practices of collecting and utilizing patient feedback at hospitals as well as future feedback-related opportunities. Nine people working at different hierarchical levels of three university hospitals in Finland participated in in-depth interviews. Findings indicate that current feedback processes are poorly planned and inflexible. Some feedback data are gathered, but not systematically utilized. Currently, it is difficult to obtain a comprehensive picture of the situation. One future hope was to increase the amount of patient feedback to be able to better generalize and utilize the data. Based on the findings the following recommendations are given: attention to both patients' and healthcare staff's perspectives when collecting feedback, employing a coordinated approach for collecting and utilizing patient feedback, and organizational transformation towards a patient-centric culture.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Industrial and Information Management, Research group: Center for Innovation and Technology Research, Aalto University, Hospital for Children and Adolescents
Contributors: Kaipio, J., Stenhammar, H., Immonen, S., Litovuo, L., Axelsson, M., Lantto, M., Lahdenne, P.
Number of pages: 5
Pages: 266-270
Publication date: 1 Jan 2018

Host publication information

Title of host publication: Building Continents of Knowledge in Oceans of Data : The Future of Co-Created eHealth - Proceedings of MIE 2018
Publisher: IOS Press
ISBN (Electronic): 9781614998518

Publication series

Name: Studies in Health Technology and Informatics
Volume: 247
ISSN (Print): 0926-9630
ISSN (Electronic): 1879-8365
ASJC Scopus subject areas: Biomedical Engineering, Health Informatics, Health Information Management
Keywords: Feedback, Formative feedback, Hospital nursing staff, Hospital-patient relations, Patient satisfaction, Patient-centered care
Electronic versions: 
Source: Scopus
Source ID: 85046541040

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Comparison of non-invasive blood pressure monitoring using modified arterial applanation tonometry with intra-arterial measurement

Intermittent non-invasive blood pressure measurement with tourniquets is slow, can cause nerve and skin damage, and interferes with other measurements. Invasive measurement cannot be safely used in all conditions. Modified arterial tonometry may be an alternative for fast and continuous measurement. Our aim was to compare arterial tonometry sensor (BPro®) with invasive blood pressure measurement to clarify whether it could be utilized in the postoperative setting. 28 patients who underwent elective surgery requiring arterial cannulation were analyzed. Patients were monitored post-operatively for 2 h with standard invasive monitoring and with a study device comprising an arterial tonometry sensor (BPro®) added with a three-dimensional accelerometer to investigate the potential impact of movement. Recordings were collected electronically. The results revealed inaccurate readings in method comparison between the devices based on recommendations by Association for the Advancement of Medical Instrumentation (AAMI). On a Bland–Altman plot, the bias and precision between these two methods was 19.8 ± 16.7 (Limits of agreement − 20.1 to 59.6) mmHg, Spearman correlation coefficient r = 0.61. For diastolic pressure, the difference was 4.8 ± 7.7 (LoA − 14.1 to 23.6) mmHg (r = 0.72), and for mean arterial pressure it was 11.18 ± 11.1 (LoA − 12.1 to 34.2) mmHg (r = 0.642). Our study revealed inaccurate agreement (AAMI) between the two methods when measuring systolic and mean blood pressures during post-operative care. The readings for diastolic pressures were inside the limits recommended by AAMI. Movement increased the failure rate significantly (p <0.001). Thus, arterial tonometry is not an appropriate replacement for invasive blood pressure measurement in these patients.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Faculty of Biomedical Sciences and Engineering, Research area: Microsystems, Research area: Measurement Technology and Process Control, Tampere University Hospital, CamsoS Consulting Ltd., University of Tampere, Medical School
Contributors: Harju, J., Vehkaoja, A., Kumpulainen, P., Campadello, S., Lindroos, V., Yli-Hankala, A., Oksala, N.
Number of pages: 10
Pages: 13–22
Publication date: 2018
Peer-reviewed: Yes
Early online date: 19 Jan 2017

Publication information

Journal: Journal of Clinical Monitoring and Computing
Volume: 32
Issue number: 1
ISSN (Print): 1387-1307
Ratings: 
  • Scopus rating (2018): CiteScore 3.4 SJR 0.772 SNIP 0.938
Original language: English
ASJC Scopus subject areas: Health Informatics, Critical Care and Intensive Care Medicine, Anesthesiology and Pain Medicine
Keywords: Arterial pressure, Blood pressure monitors, Monitoring, intraoperative
Source: Scopus
Source ID: 85009915371

Research output: Contribution to journalArticleScientificpeer-review

The Digi-NewB project for preterm infant sepsis risk and maturity analysis

It is known from the literature that the careful analysis of the heart rate variability of a preterm infant can be used as a predictor of sepsis. The Digi-NewB project aims at collecting a database of at least 750 preterm infants including physiological signals, video and clinical observations. These data are used to design a decision support system for the early detection of sepsis and for the evaluation of the infant maturity. The preparation of the data for the exploratory analysis has turned out to be time-consuming. 190 infants have been recorded by March 2018 and of these, the R-R interval analysis of the ECG signals has been completed of 136 infants. The results of the project are still preliminary but seven heart rate variability parameters have been found to be different in preterm and full-term infants with a P value less than 0.01. The video analysis algorithm detecting the presence of personnel or relatives reached 96.8% of sensitivity and 95.1% of specificity.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Research group: Personal Health Informatics-PHI, Research group: Sleep and Sensory Signal Analysis Group-SSSAG, Faculty of Biomedical Sciences and Engineering, Rennes University Hospital
Contributors: Värri, A., Kallonen, A., Helander, E., Ledesma Figueroa, A., Pladys, P.
Number of pages: 4
Pages: 330-333
Publication date: 2018
Peer-reviewed: Yes

Publication information

Journal: Finnish Journal of eHealth and eWelfare
Volume: 10
Issue number: 2-3
ISSN (Print): 1798-0798
Original language: English
ASJC Scopus subject areas: Health Informatics, Pediatrics, Perinatology, and Child Health
Keywords: decision support systems, artificial intelligence, preterm infant, sepsis risk, Health informatics

Research output: Contribution to journalArticleScientificpeer-review

Detection of spine structures with Bioimpedance Probe (BIP) Needle in clinical lumbar punctures

Lumbar puncture is a relatively safe procedure, but some serious, even fatal, complications can occur. Needle guidance can increase puncture accuracy, decrease the number of attempts, and make the procedure easier. We tested the feasibility of a bioimpedance-based tissue-sensing technology for needle guidance in clinical use. The Bioimpedance Probe (BIP) Needle has a removable BIP stylet enabling measurement of bioimpedance spectra during the procedure. The BIP Needle is connected to a measurement device that uses tissue-classification software, and the device provides audiovisual feedback when it detects cerebrospinal fluid (CSF). We performed spinal anesthesia with the BIP Needle in 45 patients. The device performance and needle tip location were verified by an experienced anesthesiologist confirming CSF leakage. The device detected CSF in all cases (sensitivity of 100 %). Six cases with false detections lowered the specificity to 81 %, but in practice, most of these were easy to differentiate from true detections because their duration was short and they occurred during backward movement of the needle. The epidural spectrum differentiated as fatty tissue from surrounding tissues, but the ligamentum flavum was not clearly detectable in the data. The BIP Needle is a reliable tool for detecting CSF in lumbar puncture. It can make the puncture procedure smoother, as repeated CSF flow tests are avoided. The correct needle tip location is immediately detected, thus unnecessary needle movements close to spinal nerves are prevented. Physicians could benefit from the information provided by the BIP Needle, especially in patients with obesity or anatomic alterations.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Department of Electronics and Communications Engineering, Injeq Ltd., Tampereen Lääkärikeskus Ltd, Tampere University Hospital, Pirkanmaan sairaanhoitopiiri, University of Tampere, Medical School
Contributors: Halonen, S., Annala, K., Kari, J., Jokinen, S., Lumme, A., Kronström, K., Yli-Hankala, A.
Number of pages: 8
Pages: 1065–1072
Publication date: Oct 2017
Peer-reviewed: Yes
Early online date: 4 Aug 2016

Publication information

Journal: Journal of Clinical Monitoring and Computing
Volume: 31
Issue number: 5
ISSN (Print): 1387-1307
Ratings: 
  • Scopus rating (2017): CiteScore 3 SJR 0.712 SNIP 0.978
Original language: English
ASJC Scopus subject areas: Medicine(all), Health Informatics, Critical Care and Intensive Care Medicine, Anesthesiology and Pain Medicine
Keywords: Bioimpedance, Cerebrospinal fluid, Epidural, Monitoring, Needle guidance, Spinal anesthesia

Bibliographical note

INT=elt,"Halonen, Sanna"

Source: Scopus
Source ID: 84982883669

Research output: Contribution to journalArticleScientificpeer-review

A Proxy-Based Solution for Asynchronous Telemedical Systems

Asynchronous telemedicine systems face many challenges related to information security as the patient's sensitive information and data on medicine dosage is transmitted over a network when monitoring patients and controlling asynchronous telemedical IoT devices. This information may be modified or spied on by a malicious adversary. To make asynchronous telemedicine systems more secure, the authors present a proxy-based solution against data modification and spying attacks in web-based telemedical applications. By obfuscating the executable code of a web application and by continuously dynamically changing obfuscation, the authors' solution makes it more difficult for a piece of malware to attack its target. They use a constructive research approach. They characterize the threat and present an outline of a proposed solution. The benefits and limitations of the proposed solution are discussed. Cyber-Attacks targeted at the information related to patient's care are a serious threat in today's telemedicine. If disregarded, these attacks have negative implications on patient safety and quality of care.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Research group: Software Engineering and Intelligent Systems, Pervasive Computing
Contributors: Rauti, S., Lahtiranta, J., Parisod, H., Hyrynsalmi, S., Salanterä, S., Aromaa, M. E., Smed, J., Leppänen, V.
Number of pages: 14
Pages: 70-83
Publication date: 1 Jul 2017
Peer-reviewed: Yes

Publication information

Journal: International Journal of E-health and Medical Communication
Volume: 8
Issue number: 3
Article number: 5
ISSN (Print): 1947-315X
Ratings: 
  • Scopus rating (2017): CiteScore 0.62 SJR 0.129 SNIP 0.403
Original language: English
ASJC Scopus subject areas: Computer Science Applications, Health Informatics
Keywords: Asynchronous Telemedicine, Man-in-The-Middle Attacks, Obfuscation, Telemedical IoT Devices, Web Application Security
Source: Scopus
Source ID: 85020175149

Research output: Contribution to journalArticleScientificpeer-review

Computer aided diagnosis of acoustic neuroma: A neural network perspective

Acoustic neuroma is a benign brain tumour, if not identified and diagnosed at early stages can result in loss of hearing. In this study Multilayer Perceptron (MLP) a feedforward Artificial Neural Network model (ANN), has been investigated for segmentation and detection of acoustic neuroma at early stages using medical resonance imaging (MRI). The proposed methodology comprises of two phases. In first phase, regions in the MRI images were classified and segmented as affected (neuroma) or normal areas. The classification was performed on pixel level using MLP. During this phase Region of Interest (ROI) was created through domain-specific knowledge. The MLP was then trained using 1490 random samples. In the second phase acoustic neuroma was detected in MRI images. The statistical analyses were subsequently performed on the pixel level to calculate the current size of detected neuroma and to provide suggestive deadlines for treatment using the growth rate of the tumour. The methodology presented in this research is more efficient compared to state-of-The art practices. The proposed technique not only detects acoustic neuroma but also highlights its location and boundaries and estimates the size of neuroma. Moreover, the computational time associated with detection and size prediction is much less in comparison to the other existing techniques. Exceptional results were obtained with an over-All accuracy of 94.12% in the detection of Acoustic Neuroma during final experimentation.

General information

Publication status: Published
MoE publication type: A2 Review article in a scientific journal
Organisations: Signal Processing, Research group: 3D MEDIA, University of Engineering and Technology, Peshawar, University of Warwick, Institute of Mechatronics Engineering
Contributors: Anwar, S., Izhar-Ul-Haq, I., Qadir, M. U., Ali, I., Razzaq, S., Ahmad, B., Shah, K., Shah, S. A., Khan, M. T.
Number of pages: 7
Pages: 371-377
Publication date: 1 Apr 2017
Peer-reviewed: Yes

Publication information

Journal: JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
Volume: 7
Issue number: 2
ISSN (Print): 2156-7018
Ratings: 
  • Scopus rating (2017): SJR 0.184 SNIP 0.359
Original language: English
ASJC Scopus subject areas: Radiology Nuclear Medicine and imaging, Health Informatics
Keywords: Acoustic Neuroma, Image Processing, Machine Vision, Magnetic Resonance Image (MRI), Multi-Layer Perceptron, Segmentation

Bibliographical note

INT=sgn,"Razzaq, Shadman"

Source: Scopus
Source ID: 85019743481

Research output: Contribution to journalReview ArticleScientificpeer-review

Bayes Forest: A data-intensive generator of morphological tree clones

Detailed and realistic tree form generators have numerous applications in ecology and forestry. For example, the varying morphology of trees contributes differently to formation of landscapes, natural habitats of species, and eco-physiological characteristics of the biosphere. Here, we present an algorithm for generating morphological tree "clones" based on the detailed reconstruction of the laser scanning data, statistical measure of similarity, and a plant growth model with simple stochastic rules. The algorithm is designed to produce tree forms, i.e., morphological clones, similar (and not identical) in respect to tree-level structure, but varying in fine-scale structural detail. Although we opted for certain choices in our algorithm, individual parts may vary depending on the application, making it a general adaptable pipeline. Namely, we showed that a specific multipurpose procedural stochastic growth model can be algorithmically adjusted to produce the morphological clones replicated from the target experimentally measured tree. For this, we developed a statistical measure of similarity (structural distance) between any given pair of trees, which allows for the comprehensive comparing of the tree morphologies by means of empirical distributions describing the geometrical and topological features of a tree. Finally, we developed a programmable interface to manipulate data required by the algorithm. Our algorithm can be used in a variety of applications for exploration of the morphological potential of the growth models (both theoretical and experimental), arising in all sectors of plant science research.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Mathematics, Research group: Inverse Problems, Department of Computer Science, Aalto University
Contributors: Potapov, I., Järvenpää, M., Åkerblom, M., Raumonen, P., Kaasalainen, M.
Publication date: 2017
Peer-reviewed: Yes

Publication information

Journal: GigaScience
Volume: 6
Issue number: 10
Article number: gix079
ISSN (Print): 2047-217X
Ratings: 
  • Scopus rating (2017): CiteScore 9.2 SJR 5.022 SNIP 1.857
Original language: English
ASJC Scopus subject areas: Health Informatics, Computer Science Applications
Keywords: Empirical distributions, Large scale data, Morphological clone, Quantitative structure tree model, Stochastic data driven model, Terrestrial laser scanning
Electronic versions: 

Bibliographical note

EXT="Järvenpää, Marko"

Source: Scopus
Source ID: 85032857287

Research output: Contribution to journalArticleScientificpeer-review

Mobile Microservice Architecture for Patients Self-Care

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Industrial and Information Management
Contributors: Ruokolainen, J.
Number of pages: 1
Pages: 106
Publication date: 2017

Host publication information

Title of host publication: The Practice of Patient Centered Care : Empowering and Engaging Patients in the Digital Era
Publisher: IOS Press
ISBN (Electronic): 9781614998235

Publication series

Name: Studies in Health Technology and Informatics
Volume: 244
ISSN (Print): 0926-9630
ISSN (Electronic): 1879-8365
ASJC Scopus subject areas: Biomedical Engineering, Health Informatics, Health Information Management
Keywords: bluetooth, Health self-care, service oriented architecture
Electronic versions: 

Bibliographical note

jufoid=67818

Source: Scopus
Source ID: 85031719393

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

A software tool for studying the size and shape of human cardiomyocytes

Background and objectives Due to development of imaging systems the amount of digital images obtained in the biological field has been growing in recent years. These images contain information that is not directly measurable, e.g. the area covered by a single cell. In most of the current imaging programs the regions of interest (ROI), e.g. individual cells, need to be manually outlined. Automation of processing and analyzing the images would ease researchers’ workload and provide results that are more reliable. In this work our goal was to write software that automatically segments human cardiomyocytes from images, calculates their areas and variations in the direction of the largest and smallest spread. Results We developed software that eased the workload of biomedical laboratory personnel such that they do not have to do manual image segmentation or learn to use software that requires programming skills. The software made a correct segmentation in most of the cases and outperformed the intensity oriented baseline method written in ImageJ in 95% of comparisons. The baseline method estimated cell- and background areas by averaging dark background and bright foreground areas. Conclusions Our software can be used in the calculation of cell areas and extents in the case where immunolabeled cells are imaged with a fluorescent microscope. In the future the functionality of the program could be extended with machine learning methods that use the user actions as teaching material in the cases where automatic segmentation fails.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Tampere University Hospital, BioMediTech
Contributors: Rasku, J., Ojala, M., Pölönen, R. P., Joutsijoki, H., Gizatdinova, Y., Laurikkala, J., Kartasalo, K., Aalto-Setälä, K., Juhola, M.
Number of pages: 6
Pages: 134-139
Publication date: 1 Sep 2016
Peer-reviewed: Yes

Publication information

Journal: Biomedical Signal Processing and Control
Volume: 30
ISSN (Print): 1746-8094
Ratings: 
  • Scopus rating (2016): CiteScore 4.6 SJR 0.674 SNIP 1.725
Original language: English
ASJC Scopus subject areas: Health Informatics, Signal Processing
Keywords: Cardiomyocyte, Segmentation, Threshold
Source: Scopus
Source ID: 84978280164

Research output: Contribution to journalArticleScientificpeer-review

Which wavelength is the best for arterial pulse waveform extraction using laser speckle imaging?

A multi-wavelengths analysis for pulse waveform extraction using laser speckle is conducted. The proposed system consists of three coherent light sources (532 nm, 635 nm, 850 nm). A bench-test composed of a moving skin-like phantom (silicone membrane) is used to compare the results obtained from different wavelengths. The system is able to identify a skin-like phantom vibration frequency, within physiological values, with a minimum error of 0.5 mHz for the 635 nm and 850 nm wavelengths and a minimum error of 1.3 mHz for the 532 nm light wavelength using a FFT-based algorithm. The phantom velocity profile is estimated with an error ranging from 27% to 9% using a bidimensional correlation coefficient-based algorithm. An in vivo trial is also conducted, using the 532 nm and 635 nm laser sources. The 850 nm light source has not been able to extract the pulse waveform. The heart rate is identified with a minimum error of 0.48 beats per minute for the 532 nm light source and a minimal error of 1.15 beats per minute for the 635 nm light source. Our work reveals that a laser speckle-based system with a 532 nm wavelength is able to give arterial pulse waveform with better results than those given with a 635 nm laser.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Department of Electronics and Communications Engineering, Research group: Computational Biophysics and Imaging Group, LARIS-Laboratoire Angevin de Recherche en Ingénierie des Systèmes, Center for Mathematics Probability and Statistics
Contributors: Vaz, P., Pereira, T., Figueiras, E., Correia, C., Humeau-Heurtier, A., Cardoso, J.
Number of pages: 8
Pages: 188-195
Publication date: Mar 2016
Peer-reviewed: Yes

Publication information

Journal: Biomedical Signal Processing and Control
Volume: 25
ISSN (Print): 1746-8094
Ratings: 
  • Scopus rating (2016): CiteScore 4.6 SJR 0.674 SNIP 1.725
Original language: English
ASJC Scopus subject areas: Health Informatics, Signal Processing
Keywords: Arterial pulse waveform, Correlation, Fast Fourier transform, Laser speckle, Multi-spectral
Source: Scopus
Source ID: 84950341719

Research output: Contribution to journalArticleScientificpeer-review

Random Value Impulse Noise Removal Based on Most Similar Neighbors

A novel filter based on four most similar neighbors (MSN) is proposed in this paper which considers all the pixels of the sliding window except the central pixel after taking the first order absolute differences from the central pixel. The proposed filter is composed of two steps: noise detection followed by filtering. In noise detection, first order absolute differences are calculated and sorted in ascending order. Clusters of equal sizes are formed based on most similar pixels and then fuzzy rules are applied to detect the noise present in the current pixel. Threshold parameters are set adaptively. In filtering phase, median based fuzzy filter is used to restore the corrupted pixels. Experimental results show that the proposed filter outperforms several state-of-the-art filers for random value impulse noise removal in an image.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Department of Electronics and Communications Engineering, International Islamic University Islamabad
Contributors: Habib, M., Rasheed, S., Hussain, A., Ali, M.
Number of pages: 5
Pages: 329-333
Publication date: 26 Feb 2016

Host publication information

Title of host publication: 2015 13th International Conference on Frontiers of Information Technology (FIT)
Publisher: IEEE
ISBN (Print): 9781467396660
ASJC Scopus subject areas: Health Informatics, Computer Science Applications, Signal Processing
Keywords: fuzzy logic, Image processing, impulse noise, noise removal

Bibliographical note

INT=elt,"Ali, Mubashir"

Source: Scopus
Source ID: 84964689604

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Department of Signal Processing, Research Community on Data-to-Decision (D2D), Harvard Medical School, Queen's University, Belfast, Northern Ireland
Contributors: De Matos Simoes, R., Mitsiades, C., Williamson, K. E., Emmert-Streib, F.
Number of pages: 8
Pages: 1216-1223
Publication date: 16 Dec 2015

Host publication information

Title of host publication: 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Publisher: IEEE
ISBN (Electronic): 978-1-4673-6799-8
ASJC Scopus subject areas: Software, Artificial Intelligence, Health Informatics, Biomedical Engineering
Keywords: data feature space inflation, feature selection, gene pair expression ratio, muscle-invasive, non muscleinvasive, Urothelial cancer
Source: Scopus
Source ID: 84962439353

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Security aspects of e-Health systems migration to the cloud

As adoption of e-health solutions advances, new computing paradigms - such as cloud computing - bring the potential to improve efficiency in managing medical health records and help reduce costs. However, these opportunities introduce new security risks which can not be ignored. Based on our experience with deploying part of the Swedish electronic health records management system in an infrastructure cloud, we make an overview of major requirements that must be considered when migrating e-health systems to the cloud. Furthermore, we describe in-depth a new attack vector inherent to cloud deployments and present a novel data confidentiality and integrity protection mechanism for infrastructure clouds. This contribution aims to encourage exchange of best practices and lessons learned in migrating public e-health systems to the cloud.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Security Lab, SICS
Contributors: Michalas, A., Paladi, N., Gehrmann, C.
Number of pages: 7
Pages: 212-218
Publication date: 1 Jan 2015

Host publication information

Title of host publication: 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services, Healthcom 2014
Publisher: Institute of Electrical and Electronics Engineers Inc.
Article number: 7001843
ISBN (Electronic): 9781479966448
ASJC Scopus subject areas: Health Information Management, Computer Networks and Communications, Health Informatics
Keywords: Cloud Computing, e-Health, EHR Protection, Security, Storage Protection
Source: Scopus
Source ID: 84921793286

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

User acceptance of electronic health records: A post-implementation study

Health organisations have faced a challenge in the transition from paper-based archiving systems to electronic health record systems. The potential of new technologies exists if medical personnel accept the information system as part of their work routine. This paper analyses electronic health record system acceptance with a post-implementation study in a regional hospital in south-eastern Finland. Quantitative data was collected with a mail survey and it was analysed with partial least squares structural equation modelling. The results suggest that a system's complexity and problems with reliability negatively influence its usefulness and decrease the willingness of personnel to use the system. Indicated with perceived behavioural control, the personnel have the necessary abilities for system usage, and the control has no influence on usage intention or actual usage of the system.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Department of Electronics and Communications Engineering
Contributors: Sintonen, S., Mäkelä, K., Miettinen, R.
Number of pages: 14
Pages: 162-175
Publication date: 2015
Peer-reviewed: Yes

Publication information

Journal: International Journal of Healthcare Technology and Management
Volume: 15
Issue number: 2
ISSN (Print): 1368-2156
Ratings: 
  • Scopus rating (2015): CiteScore 1 SJR 0.139 SNIP 0.202
Original language: English
ASJC Scopus subject areas: Health Informatics, Leadership and Management
Keywords: electronic health records, usage intention., user acceptance
Source: Scopus
Source ID: 84958543336

Research output: Contribution to journalArticleScientificpeer-review

On computation of calcium cycling anomalies in cardiomyocytes data

Induced pluripotent stem cell (iPSC) lines derived from skin fibroblasts of patients suffering from cardiac disorders were differentiated to cardiomyocytes and used to generate a data set of Ca2+ transients of 136 recordings. The objective was to separate normal signals for later medical research from abnormal signals. We constructed a signal analysis procedure to detect peaks representing calcium cycling in signals and another procedure to classify them into either normal or abnormal peaks. Using machine learning methods we classified signals into normal or abnormal signals on the basis of peak findings in them. We compared classification results obtained to those made visually by an expert biotechnologist who assessed the signals independent of the computer method. Classification accuracies of around 85% indicated high congruence between two modes denoting the high capability and usefulness of computer based processing for the present data.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: BioMediTech, Augmented Human Activities (AHA), Integrated Technologies for Tissue Engineering Research (ITTE)
Contributors: Juhola, M., Joutsijoki, H., Varpa, K., Saarikoski, J., Rasku, J., Iltanen, K., Laurikkala, J., Hyyro, H., Avalos-Salguero, J., Siirtola, H., Penttinen, K., Aalto-Setala, K.
Number of pages: 4
Pages: 1444-1447
Publication date: 2 Nov 2014

Host publication information

Title of host publication: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Publisher: Institute of Electrical and Electronics Engineers Inc.
Article number: 6943872
ISBN (Electronic): 9781424479290
ASJC Scopus subject areas: Health Informatics, Computer Science Applications, Biomedical Engineering
Keywords: Calcium cycling, cardiomyocytes, classification, signal analysis
Source: Scopus
Source ID: 84929461388

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

[COMMODE] a large-scale database of molecular descriptors using compounds from PubChem

Background: Molecular descriptors have been extensively used in the field of structure-oriented drug design and structural chemistry. They have been applied in QSPR and QSAR models to predict ADME-Tox properties, which specify essential features for drugs. Molecular descriptors capture chemical and structural information, but investigating their interpretation and meaning remains very challenging.Results: This paper introduces a large-scale database of molecular descriptors called COMMODE containing more than 25 million compounds originated from PubChem. About 2500 DRAGON-descriptors have been calculated for all compounds and integrated into this database, which is accessible through a web interface at http://commode.i-med.ac.at.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Research Community on Data-to-Decision (D2D), Oncotyrol, Institute for Bioinformatics and Translational Research, Innsbruck Medical University, Computational Biology and Machine Learning Lab., Faculty of Medicine, Health and Life Sciences, Queen's University, Belfast, Northern Ireland
Contributors: Dander, A., Mueller, L. A. J., Gallasch, R., Pabinger, S., Emmert-Streib, F., Graber, A., Dehmer, M.
Publication date: 13 Nov 2013
Peer-reviewed: Yes

Publication information

Journal: Source Code for Biology and Medicine
Volume: 8
Article number: 22
ISSN (Print): 1751-0473
Ratings: 
  • Scopus rating (2013): CiteScore 1.37 SJR 0.529 SNIP 0.46
Original language: English
ASJC Scopus subject areas: Information Systems, Computer Science Applications, Information Systems and Management, Health Informatics
Keywords: Chemical databases, Molecular descriptors, PubChem, QSAR, QSPR
Source: Scopus
Source ID: 84887399081

Research output: Contribution to journalArticleScientificpeer-review

Mobile mental wellness training for stress management: Feasibility and design implications based on a one-month field study

Background: Prevention and management of work-related stress and related mental problems is a great challenge. Mobile applications are a promising way to integrate prevention strategies into the everyday lives of citizens. Objective: The objectives of this study was to study the usage, acceptance, and usefulness of a mobile mental wellness training application among working-age individuals, and to derive preliminary design implications for mobile apps for stress management. Methods: Oiva, a mobile app based on acceptance and commitment therapy (ACT), was designed to support active learning of skills related to mental wellness through brief ACT-based exercises in the daily life. A one-month field study with 15 working-age participants was organized to study the usage, acceptance, and usefulness of Oiva. The usage of Oiva was studied based on the usage log files of the application. Changes in wellness were measured by three validated questionnaires on stress, satisfaction with life (SWLS), and psychological flexibility (AAQ-II) at the beginning and at end of the study and by user experience questionnaires after one week's and one month's use. In-depth user experience interviews were conducted after one month's use to study the acceptance and user experiences of Oiva. Results: Oiva was used actively throughout the study. The average number of usage sessions was 16.8 (SD 2.4) and the total usage time per participant was 3 hours 12 minutes (SD 99 minutes). Significant pre-post improvements were obtained in stress ratings (mean 3.1 SD 0.2 vs mean 2.5 SD 0.1, P=.003) and satisfaction with life scores (mean 23.1 SD 1.3 vs mean 25.9 SD 0.8, P=.02), but not in psychological flexibility. Oiva was perceived easy to use, acceptable, and useful by the participants. A randomized controlled trial is ongoing to evaluate the effectiveness of Oiva on working-age individuals with stress problems. Conclusions: A feasibility study of Oiva mobile mental wellness training app showed good acceptability, usefulness, and engagement among the working-age participants, and provided increased understanding on the essential features of mobile apps for stress management. Five design implications were derived based on the qualitative findings: (1) provide exercises for everyday life, (2) find proper place and time for challenging content, (3) focus on self-improvement and learning instead of external rewards, (4) guide gently but do not restrict choice, and (5) provide an easy and flexible tool for self-reflection.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Augmented Human Activities (AHA), VTT Technical Research Centre of Finland, Jyväskylän yliopisto
Contributors: Ahtinen, A., Mattila, E., Välkkynen, P., Kaipainen, K., Vanhala, T., Ermes, M., Sairanen, E., Myllymäki, T., Lappalainen, R.
Publication date: Jul 2013
Peer-reviewed: Yes

Publication information

Journal: Journal of Medical Internet Research
Volume: 15
Issue number: 7
Article number: e11
ISSN (Print): 1439-4456
Ratings: 
  • Scopus rating (2013): CiteScore 5.3 SJR 1.899 SNIP 2.216
Original language: English
ASJC Scopus subject areas: Health Informatics
Keywords: Acceptance and commitment therapy, Design, Field studies, Mental health, Mobile phone, Stress, User experience
Source: Scopus
Source ID: 84883413359

Research output: Contribution to journalArticleScientificpeer-review

Indirect measurement of the vascular endothelial glycocalyx layer thickness in human submucosal capillaries with a plug-in for ImageJ

Background: The thickness of vascular endothelial glycocalyx layer can be measured indirectly during a spontaneous leukocyte passage from oral submucosal capillaries in humans. The subsequent differences in red blood cell (RBC) column widths, before a spontaneous white blood cell passage (pre-WBC) and after a spontaneous WBC passage (post-WBC) can be used in off-line analysis to measure glycocalyx thickness: [pre-WBC width - post-WBC width]/2. We created and validated a semi-automatic plug-in for ImageJ to measure the endothelial glycocalyx layer thickness. Methods: Video clips presenting human sublingual microvasculature were created with a side-stream dark field imaging device. Spontaneous leukocyte passages in capillaries were analyzed from video clips with ImageJ. The capillary glycocalyx layer thickness was measured by the indirect approach with two manual and two semi-automatic methods. Results: There were no statistically significant differences between glycocalyx layer thicknesses measured with different methods, even though small inter-method differences in RBC column thicknesses could be detected. Inter-rater differences were systematically smaller with both semi-automatic methods. Intra-rater coefficient of variation [CV] (95% CI) was largest when measurements were made completely manually [9.2% (8.4-10.0)], but improved significantly with automatic image enhancement prior to manual measurement [7.2% (6.4-8.0)]. CV could be improved further when using semi-automatic analysis with an in-frame median filter radius of 1 pixel [5.8% (5.0-6.6)], or a median filter radius of 2 pixels [4.3% (3.5-5.1)]. Conclusions: Semi-automatic analysis of glycocalyx decreased the intra-rater CV and the inter-rater differences compared to the manual method. On average, each of the four methods yielded equal results for the glycocalyx thickness. Being the only feasible bed side method in most clinical scenarios, indirect measurement of glycocalyx thickness with orthogonal polarization spectral imaging or side-stream dark field imaging device and our plug-in can advance the study of glycocalyx layer pathology in man.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Integrated Technologies for Tissue Engineering Research (ITTE), Helsinki University Central Hospital, University of Helsinki, Uppsala University, Tampere University Hospital
Contributors: Liuhanen, S., Sallisalmi, M., Pettilä, V., Oksala, N., Tenhunen, J.
Number of pages: 10
Pages: 38-47
Publication date: Apr 2013
Peer-reviewed: Yes

Publication information

Journal: Computer Methods and Programs in Biomedicine
Volume: 110
Issue number: 1
ISSN (Print): 0169-2607
Ratings: 
  • Scopus rating (2013): CiteScore 2.28 SJR 0.628 SNIP 1.459
Original language: English
ASJC Scopus subject areas: Computer Science Applications, Software, Health Informatics
Keywords: Endothelial surface layer, Glycocalyx, Imagej, Open source, Side-stream dark field
Source: Scopus
Source ID: 84875094399

Research output: Contribution to journalArticleScientificpeer-review

Three-dimensional skeletonization and symbolic description in vascular imaging: Preliminary results

Objective: A general method was developed to analyze and describe tree-like structures needed for evaluation of complex morphology, such as the cerebral vascular tree. Clinical application of the method in neurosurgery includes planning of the surgeon's intraoperative gestures. Method: We have developed a 3D skeletonization method adapted to tubular forms with symbolic description. This approach implements an iterative Dijkstra minimum cost spanning tree, allowing a branch-by-branch skeleton extraction. The proposed method was implemented using the laboratory software platform (ArtiMed). The 3D skeleton approach was tested on simulated data and preliminary trials on clinical datasets mainly based on magnetic resonance image acquisitions. Results: A specific experimental evaluation plan was designed to test the skeletonization and symbolic description methods. Accuracy was tested by calculating the positioning error, and robustness was verified by comparing the results on a series of 18 rotations of the initial volume. Accuracy evaluation showed a Haussdorff's distance always smaller than 17 voxels and Dice's similarity coefficient greater than 70 %. Conclusion: Our method of symbolic description enables the analysis and interpretation of a vascular network obtained from angiographic images. The method provides a simplified representation of the network in the form of a skeleton, as well as a description of the corresponding information in a tree-like view.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Frontier Photonics, LAGIS CNRS UMR 8146 Université Lille 1, Univ Lille Nord de France, Lille University Hospital
Contributors: Verscheure, L., Peyrodie, L., Dewalle, A. S., Reyns, N., Betrouni, N., Mordon, S., Vermandel, M.
Number of pages: 14
Pages: 233-246
Publication date: Mar 2013
Peer-reviewed: Yes

Publication information

Journal: INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
Volume: 8
Issue number: 2
ISSN (Print): 1861-6410
Ratings: 
  • Scopus rating (2013): CiteScore 1.85 SJR 0.557 SNIP 1.164
Original language: English
ASJC Scopus subject areas: Surgery, Radiology Nuclear Medicine and imaging, Health Informatics
Keywords: 3D skeletonization, Angiography, Medical imaging, Symbolic description, Vascular network
Source: Scopus
Source ID: 84878844318

Research output: Contribution to journalArticleScientificpeer-review

An image guided treatment platform for prostate cancer photodynamic therapy

This study describes a multimodality images based platform to drive photodynamic therapies of prostate cancer using WST 11 TOOKAD Soluble drug. The platform integrates a pre-treatment planning tool based on magnetic resonance imaging and a per-treatment guidance tool based on transrectal ultrasound images. Evaluation of the platform on clinical data showed that prediction of the therapy outcome was possible with an accuracy of 90 %.

General information

Publication status: Published
MoE publication type: A4 Article in a conference publication
Organisations: Frontier Photonics, Lille University Hospital - CHRU, Inserm
Contributors: Betrouni, N., Colin, P., Puech, P., Villers, A., Mordon, S.
Number of pages: 4
Pages: 370-373
Publication date: 2013

Host publication information

Title of host publication: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Article number: 6609514
ISBN (Print): 9781457702167
ASJC Scopus subject areas: Computer Vision and Pattern Recognition, Signal Processing, Biomedical Engineering, Health Informatics
Source: Scopus
Source ID: 84886469344

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Elastic image registration for guiding focal laser ablation of prostate cancer: Preliminary results

Purpose: To guide ultrasound-driven prostate photodynamic therapy using information from MRI-based treatment planning. Methods: Robust points matching (RPM) and thin plate splines (TPS) are used to solve correspondences and to map optimally positioned landmarks from MR images to transrectal ultrasound (TRUS) images. The algorithm uses a reduced number of anatomical markers that are initialized on the images. Results: Both phantom and patient data were used to evaluate precision and robustness of the method. Mean registration error (±standard deviation) was of 2.18. ±. 0.25. mm and 1.55. ±. 0.31. mm for patient prostate and urethra, respectively. Repeated tests with different markers initialization conditions showed that the quality of registration was neither influenced by the number of markers nor to the human observer. Conclusion: This method allows for satisfyingly accurate and robust non rigid registration of MRI and TRUS and provides practitioners with substantial help in mapping treatment planning from pre-operative MRI to interventional TRUS.

General information

Publication status: Published
MoE publication type: A1 Journal article-refereed
Organisations: Frontier Photonics, Univ Paris 06, Centre National de la Recherche Scientifique (CNRS), Pierre & Marie Curie University - Paris 6, Institut de Recherche pour le Developpement (IRD), Inria, Institut National de la Sante et de la Recherche Medicale (Inserm), Univ Sorbonne, CNRS,ICM,UMR S 1127,UMR 7225,U1127, INSERM,Inria Paris Rocquencourt,Inst Cerveau & Mo, Lille University Hospital - CHRU, CHU Angers, Univ Lille Nord de France
Contributors: Makni, N., Puech, P., Colin, P., Azzouzi, A., Mordon, S., Betrouni, N.
Number of pages: 11
Pages: 213-223
Publication date: Oct 2012
Peer-reviewed: Yes

Publication information

Journal: Computer Methods and Programs in Biomedicine
Volume: 108
Issue number: 1
ISSN (Print): 0169-2607
Ratings: 
  • Scopus rating (2012): CiteScore 2.08 SJR 0.489 SNIP 1.52
Original language: English
ASJC Scopus subject areas: Computer Science Applications, Software, Health Informatics
Keywords: Image-guided interventions, Magnetic resonance imaging, Non rigid registration, PDT, Prostate cancer, Transrectal ultrasound imaging
Source: Scopus
Source ID: 84865711653

Research output: Contribution to journalArticleScientificpeer-review

Bioprofiling over Grid for eHealthcare

A trend in modern medicine is towards individualization of healthcare and, potentially, grid computing can play an important role in this by allowing sharing of resources and expertise to improve the quality of care. In this paper, we present a new test bed, the BIOPATTERN Grid, which aims to fulfil this role in the long term. The main objectives in this paper are 1) to report the development of the BIOPATTERN Grid, for biopattern analysis and bioprofiling in support of individualization of healthcare. The BIOPATTERN Grid is designed to facilitate secure and seamless sharing of geographically distributed bioprofile databases and to support the analysis of bioprofiles to combat major diseases such as brain diseases and cancer within a major EU project, BIOPATTERN (www.biopattern.org); 2) to illustrate how the BIOPATTERN Grid could be used for biopattern analysis and bioprofiling for early detection of dementia and for brain injury assessment on an individual basis. We highlight important issues that would arise from the mobility of citizens in the EU, such as those associated with access to medical data, ethical and security; and 3) to describe two grid services which aim to integrate BIOPATTERN Grid with existing grid projects on crawling service and remote data acquisition which is necessary to underpin the use of the test bed for biopattern analysis and bioprofiling.

General information

Publication status: Published
MoE publication type: Not Eligible
Organisations: Digitaali- ja tietokonetekniikka, University of Plymouth, Technical University of Crete, Institute for Signal Processing, Tampere University of Technology, Synapsis S.r.l. in Computer Science, University of Pisa
Contributors: Sun, L., Hu, P., Goh, C., Hamadicharef, B., Ifeachor, E., Barbounakis, I., Zervakis, M., Nurminen, N., Varri, A., Fontanelli, R., Di Bona, S., Guerri, D., La Manna, S., Cerbioni, K., Palanca, E., Starita, A.
Number of pages: 12
Pages: 205-216
Publication date: 1 Jan 2006
Peer-reviewed: Yes

Publication information

Journal: STUDIES IN HEALTH TECHNOLOGY AND INFORMATICS
Volume: 120
ISSN (Print): 0926-9630
Ratings: 
  • Scopus rating (2006): SJR 0.226 SNIP 0.428
Original language: English
ASJC Scopus subject areas: Biomedical Engineering, Health Informatics, Health Information Management
Keywords: Biopattern analysis, Bioprofiling, Brain Injury, Crawling service, Dementia, Grid computing, Healthcare, HealthGrid, Remote data acquisition
Source: Scopus
Source ID: 33750960479

Research output: Contribution to journalArticleScientificpeer-review

Chapter 3.9-a computer-assisted visual sleep scoring program

The sleep analysis and scoring program WSCORE was developed under the European Neurological Network (ENN) project. The purpose was to implement an analysis and scoring system for ambulatory and standard polysomnography. In addition to visual Rechtschaffen & Kales scoring the program offers a possibility of free form visual scoring. It contains also analysis modules for Periodic Leg Movement Disorder, Hjort parameters, heart rate and EMG amplitude. A FTP client module was built into the program so that it can be used as a telemedicine application.

General information

Publication status: Published
MoE publication type: Not Eligible
Organisations: Digital Media Institute, Deltamed
Contributors: Värri, A., Koivuluoma, M., Morvan, C.
Number of pages: 13
Pages: 285-297
Publication date: 1 Jan 2000
Peer-reviewed: Yes

Publication information

Journal: STUDIES IN HEALTH TECHNOLOGY AND INFORMATICS
Volume: 78
ISSN (Print): 0926-9630
Ratings: 
  • Scopus rating (2000): SJR 0.227 SNIP 0.32
Original language: English
ASJC Scopus subject areas: Biomedical Engineering, Health Informatics, Health Information Management
Source: Scopus
Source ID: 0034564762

Research output: Contribution to journalArticleScientificpeer-review