Jose Luis Perez-Lasierra, Marina Azpíroz-Puente, José-Víctor Alfaro-Santafé, Alejandro-Jesús Almenar-Arasanz, Javier Alfaro-Santafé, Antonio Gómez-Bernal
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Titles, abstracts and full-length texts for studies were screened to be included.</p><p><strong>Results: </strong>A total of seven articles were finally included in this review. Despite some methodological variability among the included studies, IMUs demonstrated potential as effective tools for detecting sarcopenia when coupled with artificial intelligence (AI) models, which outperformed traditional statistical methods in classification accuracy. The findings suggest that gait variables related to the stance phase such as stance duration, double support time, and variations between feet, are key indicators of sarcopenia.</p><p><strong>Conclusions: </strong>IMUs could be useful tools for sarcopenia screening based on gait analysis, specifically when artificial intelligence is used to process the recorded data. 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Sarcopenia screening based on the assessment of gait with inertial measurement units: a systematic review.
Background: Gait variables assessed by inertial measurement units (IMUs) show promise as screening tools for aging-related diseases like sarcopenia. The main aims of this systematic review were to analyze and synthesize the scientific evidence for screening sarcopenia based on gait variables assessed by IMUs, and also to review articles that investigated which gait variables assessed by IMUs were related to sarcopenia.
Methods: Six electronic databases (PubMed, SportDiscus, Web of Science, Cochrane Library, Scopus and IEEE Xplore) were searched for journal articles related to gait, IMUs and sarcopenia. The search was conducted until December 5, 2023. Titles, abstracts and full-length texts for studies were screened to be included.
Results: A total of seven articles were finally included in this review. Despite some methodological variability among the included studies, IMUs demonstrated potential as effective tools for detecting sarcopenia when coupled with artificial intelligence (AI) models, which outperformed traditional statistical methods in classification accuracy. The findings suggest that gait variables related to the stance phase such as stance duration, double support time, and variations between feet, are key indicators of sarcopenia.
Conclusions: IMUs could be useful tools for sarcopenia screening based on gait analysis, specifically when artificial intelligence is used to process the recorded data. However, more development and research in this field is needed to provide an effective screening tool for doctors and health systems.
期刊介绍:
BMC Geriatrics is an open access journal publishing original peer-reviewed research articles in all aspects of the health and healthcare of older people, including the effects of healthcare systems and policies. The journal also welcomes research focused on the aging process, including cellular, genetic, and physiological processes and cognitive modifications.