Gait events detection using inertial sensors, Apple Watch, and the G-WALK reference system

H. J. Navarro, S. A. Salinas, W. J. Arenas, S. A. Sotelo, C. L. Rueda, M. E. Otero, M. A. Altuve, W. J. Jaimes

Producción científica: Capítulo del libro/informe/acta de congresoPonencia publicada en las memorias del evento con ISBNrevisión exhaustiva

2 Citas (Scopus)

Resumen

The main challenge in developing gait analysis systems is to ensure accuracy in the detection of gait eve nts. To achieve this, the development of algorithms that detect these events is critical. Besides, knowledge of the places where the events appear on the sensor signals is important. In this study, a method to detect two gait cycle events, in healthy subjects walking at their natural speed, was developed. Angular velocity signals acquired from three devices were used to evaluate the method. The devices were the G-WALK (Reference device), two Inertial Measurement Unit (IMU), and two Apple Watch. Experimental results demonstrated the ability of the method to detect initial contact or heel-strike (HS) and pre-balance or toe-off (TO) events, regardless of the location of the sensor.

Idioma originalInglés
Título de la publicación alojada2021 Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges, GMEPE/PAHCE 2021
EditorialIEEE Computer Society
ISBN (versión digital)9781728170534
DOI
EstadoPublicada - 15 mar. 2021
Evento2021 Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges, GMEPE/PAHCE 2021 - Virtual, Sevilla, Espana
Duración: 15 mar. 202120 mar. 2021

Serie de la publicación

NombrePan American Health Care Exchanges, PAHCE
Volumen2021-May
ISSN (versión impresa)2327-8161
ISSN (versión digital)2327-817X

Conferencia

Conferencia2021 Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges, GMEPE/PAHCE 2021
País/TerritorioEspana
CiudadVirtual, Sevilla
Período15/03/2120/03/21

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© 2021 IEEE.

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