TY - GEN
T1 - Comparing different methods of gait speed estimation using wearable sensors in individuals with varying levels of mobility impairments
AU - Nunez, Erick H.
AU - Parhar, Sanjit
AU - Iwata, Isao
AU - Setoguchi, Soko
AU - Chen, Haoqian
AU - Daneault, Jean Francois
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - Wearable sensors, such as inertial measurement units (IMU), provide the ability to quantify gait parameters outside of traditional gait laboratory settings. Walking speed has been shown to be associated with morbidity and mortality. Therefore, the ability of a clinician to easily and inexpensively measure gait speed within their clinic or patients' home setting can improve patient management and care. This study highlights multiple methods used to estimate patient walking speeds based only on IMU data and minimal anthropometric data, and identifies the algorithm appearing to be the most robust; one relying on identifying swing phases of gait first.Clinical relevance - Providing a clinician with a simple, inexpensive and reliable protocol for measuring patients' gait speed and other parameters could offer prevention and individualized care.
AB - Wearable sensors, such as inertial measurement units (IMU), provide the ability to quantify gait parameters outside of traditional gait laboratory settings. Walking speed has been shown to be associated with morbidity and mortality. Therefore, the ability of a clinician to easily and inexpensively measure gait speed within their clinic or patients' home setting can improve patient management and care. This study highlights multiple methods used to estimate patient walking speeds based only on IMU data and minimal anthropometric data, and identifies the algorithm appearing to be the most robust; one relying on identifying swing phases of gait first.Clinical relevance - Providing a clinician with a simple, inexpensive and reliable protocol for measuring patients' gait speed and other parameters could offer prevention and individualized care.
UR - http://www.scopus.com/inward/record.url?scp=85091000874&partnerID=8YFLogxK
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U2 - 10.1109/EMBC44109.2020.9175341
DO - 10.1109/EMBC44109.2020.9175341
M3 - Conference contribution
AN - SCOPUS:85091000874
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3792
EP - 3798
BT - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
Y2 - 20 July 2020 through 24 July 2020
ER -