Abstract
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.
Original language | English |
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Title of host publication | 2021 Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges, GMEPE/PAHCE 2021 |
Publisher | IEEE Computer Society |
ISBN (Electronic) | 9781728170534 |
DOIs | |
State | Published - 15 Mar 2021 |
Event | 2021 Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges, GMEPE/PAHCE 2021 - Virtual, Sevilla, Spain Duration: 15 Mar 2021 → 20 Mar 2021 |
Publication series
Name | Pan American Health Care Exchanges, PAHCE |
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Volume | 2021-May |
ISSN (Print) | 2327-8161 |
ISSN (Electronic) | 2327-817X |
Conference
Conference | 2021 Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges, GMEPE/PAHCE 2021 |
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Country/Territory | Spain |
City | Virtual, Sevilla |
Period | 15/03/21 → 20/03/21 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
Keywords
- Apple Watch
- gait cycle
- inertial measurement unit.