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The timely prediction of fall risks can help identify older adults prone to falls and implement preventive interventions. Recent advancements in wearable sensor-based technologies and big data analysis have spurred the development of accurate, affordable, and easy-to-use approaches to fall risk assessment. The objective of this study was to systematically assess the current state of wearable sensor-based technologies for fall risk assessment among community-dwelling older adults. Twenty-five of 614 identified research articles were included in this review. A comprehensive comparison was conducted to evaluate these approaches from several perspectives. In general, these approaches provide an accurate and effective surrogate for fall risk assessment. The accuracy of fall risk prediction can be influenced by various factors such as sensor location, sensor type, features utilized, and data processing and modeling techniques. Features constructed from the raw signals are essential for predictive model development. However, more investigations are needed to identify distinct, clinically interpretable features and develop a general framework for fall risk assessment based on the integration of sensor technologies and data modeling.<\/jats:p>","DOI":"10.3390\/s22186752","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:18:32Z","timestamp":1662610712000},"page":"6752","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":77,"title":["A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9543-4367","authenticated-orcid":false,"given":"Manting","family":"Chen","sequence":"first","affiliation":[{"name":"School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6668-7947","authenticated-orcid":false,"given":"Hailiang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Design, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China"}]},{"given":"Lisha","family":"Yu","sequence":"additional","affiliation":[{"name":"Shenzhen Enstech Technology Co., Ltd., Shenzhen 518000, China"}]},{"given":"Eric Hiu Kwong","family":"Yeung","sequence":"additional","affiliation":[{"name":"Department of Physiotherapy, The University of Hong Kong-Shenzhen Hospital, Shenzhen 518000, China"}]},{"given":"Jiajia","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518000, China"}]},{"given":"Kwok-Leung","family":"Tsui","sequence":"additional","affiliation":[{"name":"Grado Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA"}]},{"given":"Yang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518000, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,7]]},"reference":[{"key":"ref_1","unstructured":"(2022, June 10). 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