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

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Stella Ansah, Diliang Chen
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引用次数: 1

Abstract

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.
基于可穿戴步态分析的活动识别研究综述
摘要步态分析已被公认为有助于实现人类活动识别的有效方法;然而,目前还没有关于在识别过程中使用步态分析的可穿戴活动识别方法的综述研究。本研究从可穿戴传感器类型、数据分割、特征提取和分类方法等方面,总结并比较了不同的基于可穿戴步态分析(WGA)的活动识别方法。还讨论了当前研究的局限性以及该领域未来研究的潜在机会。
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来源期刊
CiteScore
2.70
自引率
8.30%
发文量
15
审稿时长
8 weeks
期刊介绍: nternational Journal on Smart Sensing and Intelligent Systems (S2IS) is a rapid and high-quality international forum wherein academics, researchers and practitioners may publish their high-quality, original, and state-of-the-art papers describing theoretical aspects, system architectures, analysis and design techniques, and implementation experiences in intelligent sensing technologies. The journal publishes articles reporting substantive results on a wide range of smart sensing approaches applied to variety of domain problems, including but not limited to: Ambient Intelligence and Smart Environment Analysis, Evaluation, and Test of Smart Sensors Intelligent Management of Sensors Fundamentals of Smart Sensing Principles and Mechanisms Materials and its Applications for Smart Sensors Smart Sensing Applications, Hardware, Software, Systems, and Technologies Smart Sensors in Multidisciplinary Domains and Problems Smart Sensors in Science and Engineering Smart Sensors in Social Science and Humanity
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