Recognizing Manual Activities Using Wearable Inertial Measurement Units: Clinical Application for Outcome Measurement.
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ABSTRACT:
SUBMITTER: El Khoury G
PROVIDER: S-EPMC8125825 | biostudies-literature | 2021 May
REPOSITORIES: biostudies-literature
Publications
Recognizing Manual Activities Using Wearable Inertial Measurement Units: Clinical Application for Outcome Measurement.
El Khoury Ghady G Penta Massimo M Barbier Olivier O Libouton Xavier X Thonnard Jean-Louis JL Lefèvre Philippe P
Sensors (Basel, Switzerland) 20210507 9
The ability to monitor activities of daily living in the natural environments of patients could become a valuable tool for various clinical applications. In this paper, we show that a simple algorithm is capable of classifying manual activities of daily living (ADL) into categories using data from wrist- and finger-worn sensors. Six participants without pathology of the upper limb performed 14 ADL. Gyroscope signals were used to analyze the angular velocity pattern for each activity. The elabora ...[more]
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