Effectiveness of a Hybrid Exercise Program on the Physical Abilities of Frail Elderly and Explainable Artificial-Intelligence-Based Clinical Assistance

Deyu Meng, Hongzhi Guo, Siyu Liang, Zhibo Tian, Ran Wang, Guang Yang and Ziheng Wang
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Deyu Meng: Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China
Hongzhi Guo: Graduate School of Human Sciences, Waseda University, Tokorozawa 169-8050, Japan
Siyu Liang: Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China
Zhibo Tian: Sports Marketing Research Group, Sports College, Dankook University, Gyeonggi-do, Yongin-si 16890, Korea
Ran Wang: Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China
Guang Yang: Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China
Ziheng Wang: Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun 130024, China

IJERPH, 2022, vol. 19, issue 12, 1-15

Abstract: Background: Due to the low physical fitness of the frail elderly, current exercise program strategies have a limited impact. Eight-form Tai Chi has a low intensity, but high effectiveness in the elderly. Inspired by it, we designed an exercise program that incorporates eight-form Tai Chi, strength, and endurance exercises, to improve physical fitness and reverse frailty in the elderly. Additionally, for the ease of use in clinical practice, machine learning simulations were used to predict the frailty status after the intervention. Methods: For 24 weeks, 150 frail elderly people completed the experiment, which comprised the eight-form Tai Chi group (TC), the strength and endurance training group (SE), and a comprehensive intervention combining both TC and SE (TCSE). The comparison of the demographic variables used one-way ANOVA for continuous data and the chi-squared test for categorical data. Two-way repeated measures analysis of variance (ANOVA) was performed to determine significant main effects and interaction effects. Eleven machine learning models were used to predict the frailty status of the elderly following the intervention. Results: Two-way repeated measures ANOVA results before the intervention, group effects of ten-meter maximum walking speed (10 m MWS), grip strength (GS), timed up and go test (TUGT), and the six-minute walk test (6 min WT) were not significant. There was a significant interaction effect of group × time in ten-meter maximum walking speed, grip strength, and the six-minute walk test. Post hoc tests showed that after 24 weeks of intervention, subjects in the TCSE group showed the greatest significant improvements in ten-meter maximum walking speed ( p < 0.05) and the six-minute walk test ( p < 0.05) compared to the TC group and SE group. The improvement in grip strength in the TCSE group (4.29 kg) was slightly less than that in the SE group (5.16 kg). There was neither a significant main effect nor a significant interaction effect for TUGT in subjects. The stacking model outperformed other algorithms. Accuracy and the F1-score were 67.8% and 71.3%, respectively. Conclusion: A hybrid exercise program consisting of eight-form Tai Chi and strength and endurance exercises can more effectively improve physical fitness and reduce frailty among the elderly. It is possible to predict whether an elderly person will reverse frailty following an exercise program based on the stacking model.

Keywords: frail; Tai Chi; strength training; endurance training; machine learning (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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