<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Gait analysis has been recognized as an efficient method to help realize human activity recognition; however, there is currently no existing review study focused on wearable activity recognition methods that employ gait analysis in the recognition process. In this study, different wearable-gait-analysis-based (WGA-based) activity recognition methods were summarized and compared from the aspects of wearable sensor types, data segmentation, feature extraction, and classification methods. The limitations of the current research and potential opportunities for future research in this field are also discussed.</p>
</abstract>

Gait analysis has been recognized as an efficient method to help realize human activity recognition; however, there is currently no existing review study focused on wearable activity recognition methods that employ gait analysis in the recognition process. In this study, different wearable-gait-analysis-based (WGA-based) activity recognition methods were summarized and compared from the aspects of wearable sensor types, data segmentation, feature extraction, and classification methods. The limitations of the current research and potential opportunities for future research in this field are also discussed.

Wearable-Gait-Analysis-Based Activity Recognition: A Review

Department of Electrical and Computer Engineering

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Wearable-Gait-Analysis-Based Activity Recognition: A Review"}

Gait analysis has been recognized as an efficient method to help realize human activity recognition; however, there is currently no existing review study...

Wearable-Gait-Analysis-Based Activity Recognition: A Review

Article Category: Article

Online veröffentlicht: 04. Jan. 2023

Seitenbereich: -

Eingereicht: 31. März 2022

DOI: https://doi.org/10.2478/ijssis-2022-0021

Schlüsselwörter
human activity recognition, gait analysis, wearable sensors, data segmentation, knowledge-driven feature extraction

© 2022 Stella Ansah et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Wearable-Gait-Analysis-Based Activity Recognition: A Review

Article Category: Article

Online veröffentlicht: 04. Jan. 2023

Seitenbereich: -

Eingereicht: 31. März 2022

DOI: https://doi.org/10.2478/ijssis-2022-0021

Schlüsselwörterhuman activity recognition, gait analysis, wearable sensors, data segmentation, knowledge-driven feature extraction

© 2022 Stella Ansah et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
human activity recognition, gait analysis, wearable sensors, data segmentation, knowledge-driven feature extraction