Open AccessSynthetized inertial measurement units (IMUs) to evaluate the placement of wearable sensors on human body for motion recognition
Author(s) -
Hoareau Damien,
Jodin Gurvan,
Chantal PierreAntoine,
Bretin Sara,
Prioux Jacques,
Razan Florence
Publication year - 2022
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/tje2.12137
Subject(s) - units of measurement , inertial measurement unit , inertial frame of reference , computer science , wearable computer , motion (physics) , computer vision , artificial intelligence , workload , human motion , motion capture , simulation , embedded system , physics , quantum mechanics , operating system
Abstract Movement data from athletes are useful to quantify performance or more specifically the workload. Inertial measurement units (IMUs) are useful sensors to quantify body movements. Sensor placement on human body is still an open question that this paper focuses on. A method that develops synthesized inertial data is proposed for determining optimal sensors placement. Comparison between virtual and real inertial data is achieved. Training motion recognition algorithm on synthesized and real inertial data exhibits less than 7% difference. This method highlights the ability of the numerical model to determine relevant sensor placement of IMUs on human body for motion recognition algorithm using virtual sensors.