Body Movement-Based Controlling Through Passive RFID Integrated into Clothing

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Body Movement-Based Controlling Through Passive RFID Integrated into Clothing. / Mehmood, Adnan; He, Han; Chen, Xiaochen; Merilampi, Sari; Sydänheimo, Lauri ; Ukkonen, Leena ; Virkki, Johanna.

In: IEEE Journal of Radio Frequency Identification, 22.07.2020.

Research output: Contribution to journal › Article › Scientific › peer-review

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@article{e98e802ff33f40c98909e5795e0587a6,

title = "Body Movement-Based Controlling Through Passive RFID Integrated into Clothing",

abstract = "We present a passive ultra-high frequency (UHF) radiofrequency identification (RFID)-based strain sensor, which is designed for simple and efficient body movement monitoring. This RFID platform is fabricated from electro-textile materials and can thus be seamlessly integrated into our everyday clothing. The sensor platform has an integrated reference tag, in order to avoid the effects of reflections or external disturbances on the sensor tag performance. This sensor platform prototype has an on-body read range of 1 meter in a normal office environment with an off-the-shelf RFID reader. The wireless performance of the sensor tag has a significant change caused by arm elongation. Thus, the sensor functionality can be based on variation of the sensor tag's backscattered power percentage (P {\%}). Based on the preliminary results achieved in this study, this passive and cost-effective sensor platform could be an efficient future way to turn human gestures into inputs for digital devices.",

author = "Adnan Mehmood and Han He and Xiaochen Chen and Sari Merilampi and Lauri Syd{\"a}nheimo and Leena Ukkonen and Johanna Virkki",

note = "EXT={"}Merilampi, Sari{"}",

year = "2020",

month = "7",

day = "22",

doi = "10.1109/jrfid.2020.3010717",

language = "English",

journal = "IEEE Journal of Radio Frequency Identification",

issn = "2469-7281",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Body Movement-Based Controlling Through Passive RFID Integrated into Clothing

AU - Mehmood, Adnan

AU - He, Han

AU - Chen, Xiaochen

AU - Merilampi, Sari

AU - Sydänheimo, Lauri

AU - Ukkonen, Leena

AU - Virkki, Johanna

N1 - EXT="Merilampi, Sari"

PY - 2020/7/22

Y1 - 2020/7/22

N2 - We present a passive ultra-high frequency (UHF) radiofrequency identification (RFID)-based strain sensor, which is designed for simple and efficient body movement monitoring. This RFID platform is fabricated from electro-textile materials and can thus be seamlessly integrated into our everyday clothing. The sensor platform has an integrated reference tag, in order to avoid the effects of reflections or external disturbances on the sensor tag performance. This sensor platform prototype has an on-body read range of 1 meter in a normal office environment with an off-the-shelf RFID reader. The wireless performance of the sensor tag has a significant change caused by arm elongation. Thus, the sensor functionality can be based on variation of the sensor tag's backscattered power percentage (P %). Based on the preliminary results achieved in this study, this passive and cost-effective sensor platform could be an efficient future way to turn human gestures into inputs for digital devices.

AB - We present a passive ultra-high frequency (UHF) radiofrequency identification (RFID)-based strain sensor, which is designed for simple and efficient body movement monitoring. This RFID platform is fabricated from electro-textile materials and can thus be seamlessly integrated into our everyday clothing. The sensor platform has an integrated reference tag, in order to avoid the effects of reflections or external disturbances on the sensor tag performance. This sensor platform prototype has an on-body read range of 1 meter in a normal office environment with an off-the-shelf RFID reader. The wireless performance of the sensor tag has a significant change caused by arm elongation. Thus, the sensor functionality can be based on variation of the sensor tag's backscattered power percentage (P %). Based on the preliminary results achieved in this study, this passive and cost-effective sensor platform could be an efficient future way to turn human gestures into inputs for digital devices.

UR - https://www.mendeley.com/catalogue/ad2f0ffc-d356-3e3d-8564-e03d352e0ae5/

U2 - 10.1109/jrfid.2020.3010717

DO - 10.1109/jrfid.2020.3010717

M3 - Article

JO - IEEE Journal of Radio Frequency Identification

JF - IEEE Journal of Radio Frequency Identification

SN - 2469-7281

ER -

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