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Eigen Posture Based Fall Risk Assessment System Using Kinect

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Eigen Posture Based Fall Risk Assessment System Using Kinect. / Tripathy, Soumya Ranjan; Chakravarty, Kingshuk; Sinha, Aniruddha.

40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Vol. 2018-July IEEE, 2018. p. 1-4 8513263.

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

Harvard

Tripathy, SR, Chakravarty, K & Sinha, A 2018, Eigen Posture Based Fall Risk Assessment System Using Kinect. in 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. vol. 2018-July, 8513263, IEEE, pp. 1-4, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Honolulu, United States, 18/07/18. https://doi.org/10.1109/EMBC.2018.8513263

APA

Tripathy, S. R., Chakravarty, K., & Sinha, A. (2018). Eigen Posture Based Fall Risk Assessment System Using Kinect. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 (Vol. 2018-July, pp. 1-4). [8513263] IEEE. https://doi.org/10.1109/EMBC.2018.8513263

Vancouver

Tripathy SR, Chakravarty K, Sinha A. Eigen Posture Based Fall Risk Assessment System Using Kinect. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Vol. 2018-July. IEEE. 2018. p. 1-4. 8513263 https://doi.org/10.1109/EMBC.2018.8513263

Author

Tripathy, Soumya Ranjan ; Chakravarty, Kingshuk ; Sinha, Aniruddha. / Eigen Posture Based Fall Risk Assessment System Using Kinect. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018. Vol. 2018-July IEEE, 2018. pp. 1-4

Bibtex - Download

@inproceedings{ffa05fceab4c452d9341c3f0a8f0fd5b,
title = "Eigen Posture Based Fall Risk Assessment System Using Kinect",
abstract = "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.",
keywords = "BBS, Eigenpose, EMD, Fall risk, Index Terms-Kinect",
author = "Tripathy, {Soumya Ranjan} and Kingshuk Chakravarty and Aniruddha Sinha",
year = "2018",
month = "10",
day = "26",
doi = "10.1109/EMBC.2018.8513263",
language = "English",
volume = "2018-July",
publisher = "IEEE",
pages = "1--4",
booktitle = "40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Eigen Posture Based Fall Risk Assessment System Using Kinect

AU - Tripathy, Soumya Ranjan

AU - Chakravarty, Kingshuk

AU - Sinha, Aniruddha

PY - 2018/10/26

Y1 - 2018/10/26

N2 - 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.

AB - 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.

KW - BBS

KW - Eigenpose

KW - EMD

KW - Fall risk

KW - Index Terms-Kinect

U2 - 10.1109/EMBC.2018.8513263

DO - 10.1109/EMBC.2018.8513263

M3 - Conference contribution

VL - 2018-July

SP - 1

EP - 4

BT - 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018

PB - IEEE

ER -