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.