Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis

The widespread use of Inertial Measurement Units (IMUs) has transformed human motion analysis, offering key advantages such as low cost, ease of use, broad acquisition range, and unobtrusiveness. IMUs are especially valuable in ecological settings, enabling applications in clinical outcome assessmen...

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collection Directory of Open Access Books
description The widespread use of Inertial Measurement Units (IMUs) has transformed human motion analysis, offering key advantages such as low cost, ease of use, broad acquisition range, and unobtrusiveness. IMUs are especially valuable in ecological settings, enabling applications in clinical outcome assessment (e.g., tele-rehabilitation), sports performance and injury prevention, and human–robot interaction. Recent advancements in miniaturization, performance, and integration have expanded their potential, especially when combined with artificial intelligence techniques like machine learning and deep learning. The Special Issue, titled “Recent Advances and Applications of Wearable Inertial Sensors in Motion Analysis”, features 18 high-quality publications—14 original research articles, 2 systematic reviews, and 2 communications—exploring the novel uses of wearable IMUs. A strong focus is placed on gait analysis, with contributions addressing trunk acceleration patterns, gait variability, fall risk assessment, and spatio-temporal parameter estimation, even in patients using assistive devices. IMUs also support accurate foot trajectory reconstruction and terrain identification. Other studies examine maternal gait during labor, cardiovascular stress during walking, and AI-enhanced gait phase prediction. Beyond gait, IMUs are used to analyze upper and lower body movements, post-COVID return to running, balance metrics via smartwatches, magnetic interference detection, and activity recognition through gesture analysis. Collectively, these works significantly advance wearable motion analysis research.
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institution Directory of Open Access Books
language eng
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
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spelling doab-20.500.12854ir-1656312025-08-12T10:01:58Z Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis Gastaldi, Laura Digo, Elisa Motion and gait analysis Clinical reports Wearable sensors, Medical decision making Health monitoring Fall risk Rehabilitation Biomechanics of sport Machine learning techniques Gesture recognition Industry Human–robot collaboration thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science The widespread use of Inertial Measurement Units (IMUs) has transformed human motion analysis, offering key advantages such as low cost, ease of use, broad acquisition range, and unobtrusiveness. IMUs are especially valuable in ecological settings, enabling applications in clinical outcome assessment (e.g., tele-rehabilitation), sports performance and injury prevention, and human–robot interaction. Recent advancements in miniaturization, performance, and integration have expanded their potential, especially when combined with artificial intelligence techniques like machine learning and deep learning. The Special Issue, titled “Recent Advances and Applications of Wearable Inertial Sensors in Motion Analysis”, features 18 high-quality publications—14 original research articles, 2 systematic reviews, and 2 communications—exploring the novel uses of wearable IMUs. A strong focus is placed on gait analysis, with contributions addressing trunk acceleration patterns, gait variability, fall risk assessment, and spatio-temporal parameter estimation, even in patients using assistive devices. IMUs also support accurate foot trajectory reconstruction and terrain identification. Other studies examine maternal gait during labor, cardiovascular stress during walking, and AI-enhanced gait phase prediction. Beyond gait, IMUs are used to analyze upper and lower body movements, post-COVID return to running, balance metrics via smartwatches, magnetic interference detection, and activity recognition through gesture analysis. Collectively, these works significantly advance wearable motion analysis research. 2025-08-12T10:01:55Z 2025-08-12T10:01:55Z 2025 book ONIX_20250812T110751_9783725842278_386 9783725842278 9783725842285 https://directory.doabooks.org/handle/20.500.12854/165631 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/11055 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-4228-5 10.3390/books978-3-7258-4228-5 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725842278 9783725842285 324 open access
spellingShingle Motion and gait analysis
Clinical reports
Wearable sensors, Medical decision making
Health monitoring
Fall risk
Rehabilitation
Biomechanics of sport
Machine learning techniques
Gesture recognition
Industry
Human–robot collaboration
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::P Mathematics and Science
Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis
title Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis
title_full Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis
title_fullStr Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis
title_full_unstemmed Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis
title_short Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis
title_sort recent advance and application of wearable inertial sensors in motion analysis
topic Motion and gait analysis
Clinical reports
Wearable sensors, Medical decision making
Health monitoring
Fall risk
Rehabilitation
Biomechanics of sport
Machine learning techniques
Gesture recognition
Industry
Human–robot collaboration
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::P Mathematics and Science
topic_facet Motion and gait analysis
Clinical reports
Wearable sensors, Medical decision making
Health monitoring
Fall risk
Rehabilitation
Biomechanics of sport
Machine learning techniques
Gesture recognition
Industry
Human–robot collaboration
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::P Mathematics and Science
url ONIX_20250812T110751_9783725842278_386