Low-cost multisensor integrated system for online walking gait detection

Yan, L; Wei, G; Hu, Z; Xiu, H; Wei, Y; Ren, L

Abstract

A three-dimensional motion capture system is a useful tool for analysing gait patterns during walking or exercising, and it is frequently applied in biomechanical studies. However, most of them are expensive. This study designs a low-cost gait detection system with high accuracy and reliability that is an alternative method/equipment in the gait detection field to the most widely used commercial system, the virtual user concept (Vicon) system. The proposed system integrates mass-produced low-cost sensors/chips in a compact size to collect kinematic data. Furthermore, an x86 mini personal computer (PC) running at 100 Hz classifies motion data in real-time. To guarantee gait detection accuracy, the embedded gait detection algorithm adopts a multilayer perceptron (MLP) model and a rule-based calibration filter to classify kinematic data into five distinct gait events: heel-strike, foot-flat, heel-off, toe-off, and initial-swing. To evaluate performance, volunteers are requested to walk on the treadmill at a regular walking speed of 4.2 km/h while kinematic data are recorded by a low-cost system and a Vicon system simultaneously. The gait detection accuracy and relative time error are estimated by comparing the classified gait events in the study with the Vicon system as a reference. The results show that the proposed system obtains a high accuracy of 99.66% with a smaller time error (32 ms), demonstrating that it performs similarly to the Vicon system in the gait detection field.

Citation

Yan, L., Wei, G., Hu, Z., Xiu, H., Wei, Y., & Ren, L. (2021). Low-cost multisensor integrated system for online walking gait detection. Journal of Sensors, 2021, 6378514. https://doi.org/10.1155/2021/6378514

• Journal Article Type: Article
• Acceptance Date: Jul 25, 2021
• Publication Date: Aug 14, 2021
• Deposit Date: Aug 23, 2021
• Publicly Available Date: Aug 23, 2021
• Journal: Journal of Sensors
• Print ISSN: 1687-725X
• Electronic ISSN: 1687-7268
• Publisher: Hindawi
• Volume: 2021
• Pages: 6378514
• DOI: https://doi.org/10.1155/2021/6378514
• Publisher URL: https://doi.org/10.1155/2021/6378514
• Related Public URLs: http://www.hindawi.com/journals/js/
• Additional Information: Additional Information : ** From Hindawi via Jisc Publications Router ** Licence for this article: https://creativecommons.org/licenses/by/4.0/ **Journal IDs: eissn 1687-7268; pissn 1687-725X **Article IDs: publisher-id: 6378514 **History: archival-date 14-08-2021; published 14-08-2021; accepted 25-07-2021; rev-recd 02-07-2021; submitted 21-04-2021; published 2021