Self-determined sequence exercise program for elderly with sarcopenia: A Randomized controlled trial with clinical assistance from explainable artificial intelligence

ARCHIVES OF GERONTOLOGY AND GERIATRICS(2024)

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摘要
To improve and even reverse sarcopenia in elderly people, this study developed a self-determined sequence exercise program consisting of strength training exercise, Yijinjing exercise (a traditional Chinese exercise), and hybrid strength training with Yijinjing exercise. Ninety-four community-dwelling older adults screened for sarcopenia using the Asian Working Group for Sarcopenia criteria were randomly assigned to 24 weeks of a control group (CG, n = 30), self-determined sequence exercise program group (SDSG, n = 34) or strength training group (STG, n = 30). The study examined the effects of three interventions on participantsL3 skeletal muscle fat density, L3 skeletal muscle fat area, L3 skeletal muscle density, L3 skeletal muscle area, muscle fat infiltration, relative skeletal muscle mass index, and grip strength using a repeated-measures ANOVA to evaluate the experimental data. To evaluate the real effect of this model in reversing sarcopenia after the intervention, nine classification models were trained. Significant interaction effects were observed with grip strength, RSMI, L3 SMD, and L3 SMA. At the 24th week, participants' grip strength, L3 SMFA, L3 SMA, and RSMI were improved significantly in the SDSG and STG. The SDSG achieved significantly greater RSMI and grip strength than the STG and CG after the intervention. The self-determined sequence exercise program exhibited better performance than the single type of exercise modality in reversing sarcopenia and improving older adults' skeletal muscle area. Consequently, the stacking model is feasible to make a prediction as to whether or not sarcopenia may be reversed in older adults.
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关键词
Sarcopenia,Markov chain,Explainable machine learning,Exercise intervention,Chinese traditional exercise
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