Detection of Foot Motions for Interaction With Exergames Using Shoe-Mounted Inertial Sensors

• Type: Article in International Scientific Journal
• Date: 2023

Authors

Guimaraes, V (Author) Other; Sousa, I (Author) Other; Correia, M. V. (Author) FEUP

Journal

Title: IEEE Transactions on Human-Machine Systems

Vol. 53 No. 1

Pages: 895-904

ISSN: 2168-2291

Publisher: IEEE

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00Y-RZP

DOI: 10.1109/thms.2023.3292902

Abstract (EN): Inertial sensors are widely used to measure human movement. Although inertial sensors have been successfully applied to exergaming in the past, the problem of detecting foot motions to interact with stepping exergames is still largely understudied. In this work, we developed a new method to detect and classify step directions relying on inertial sensor data captured by two shoe-mounted inertial sensors. Drawing on previous results, we developed a single multiclass classifier to distinguish front, back, side, and center steps originating from any of these positions. Since some of these steps exhibit similar displacement patterns, the previous step position was also considered as an input to the classifier. The method was tested on a group of young and older adults, achieving an accuracy of 93.1%. Performance remained consistent throughout the acquisition time due to the introduction of a novel calibration approach designed to handle sensor orientation drift over time. This study provided the first insights into the potential of inertial sensors to detect the foot motions required to interact with stepping exergames. Experimental results support their application in a real scenario.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10