Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

ABSTRACT:

Background

Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies.

Objective

The

SUBMITTER: Kluge F 

PROVIDER: S-EPMC11097052 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature