TY  - JOUR
PY  - 2022//
TI  - WISP, wearable inertial sensor for online wheelchair propulsion detection
JO  - Sensors (Basel)
A1  - Callupe Luna, Jhedmar
A1  - Martinez Rocha, Juan
A1  - Monacelli, Eric
A1  - Foggea, Gladys
A1  - Hirata, Yasuhisa
A1  - Delaplace, Stéphane
SP  - 4221
EP  - 4221
VL  - 22
IS  - 11
N2  - Manual wheelchair dance is an artistic recreational and sport activity for people with disabilities that is becoming more and more popular. It has been reported that a significant part of the dance is dedicated to propulsion. Furthermore, wheelchair dance professionals such as Gladys Foggea highlight the need for monitoring the quantity and timing of propulsions for assessment and learning. This study addresses these needs by proposing a wearable system based on inertial sensors capable of detecting and characterizing propulsion gestures. We called the system WISP. Within our initial configuration, three inertial sensors were placed on the hands and the back. Two machine learning classifiers were used for online bilateral recognition of basic propulsion gestures (forward, backward, and dance). Then, a conditional block was implemented to rebuild eight specific propulsion gestures. Online paradigm is intended for real-time assessment applications using sliding window method. Thus, we evaluate the accuracy of the classifiers in two configurations: "three-sensor" and "two-sensor". <br><br>RESULTS showed that when using "two-sensor" configuration, it was possible to recognize the propulsion gestures with an accuracy of 90.28%. Finally, the system allows to quantify the propulsions and measure their timing in a manual wheelchair dance choreography, showing its possible applications in the teaching of dance.<p />  <p>Language: en</p>
LA  - en
SN  - 1424-8220
UR  - http://dx.doi.org/10.3390/s22114221
ID  - ref1
ER  -