Detection and classification of multidirectional steps for motor-cognitive training in older adults using shoe-mounted inertial sensors

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Vania Guimarães (Author) Other; Inês Sousa (Author) Other; Miguel V. Correia (Author) FEUP

Conference proceedings International

Title: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Pages: 6926-6929

41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019

23 July 2019 through 27 July 2019

Other information

Authenticus ID: P-00S-Q7D

DOI: 10.1109/EMBC.2019.8856851

Abstract (EN): Interactive games have the potential to mitigate or prevent gait impairments and cognitive decline in older adults. This study aimed at developing a novel real-time step detection and direction classification approach to be used in the evaluation of multidirectional steps and interaction while playing motor-cognitive games. Two shoe-mounted inertial sensors were used to capture foot motions, which were treated interchangeably after the application of a novel foot sagittal reflection method. A single multi-class classifier was able to distinguish step direction with an accuracy of 98.1%. Experimental results support the applicability of the solution in the context of interactive motor-cognitive training. © 2019 IEEE.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4