Wei Meiqi, Meng Deyu, He Shichun, Lv Zongnan, Guo Hongzhi, Yang Guang, Wang Ziheng
Division of Computational Biology, Chinese Center of Exercise Epidemiology, Northeast Normal University, Renmin Street, Changchun, 130024, Jilin, China.
Department of Adolescent Physical Health, Chinese Center of Exercise Epidemiology, Northeast Normal University, Renmin Street, Changchun, 130024, Jilin, China.
Eur Geriatr Med. 2025 Feb;16(1):115-123. doi: 10.1007/s41999-024-01082-y. Epub 2024 Oct 25.
This study explores the effectiveness of 3D pose estimation technology in Yi Jin Jing (a traditional Chinese exercise) interventions for sarcopenic older individuals.
A randomized controlled trial involving 93 participants (mean age: 71.64 ± 7.09 years; 41 males and 52 females) divided into three groups: a face-to-face offline traditional training group (OFFG), a general remote online training group (ONG), and an AI-based online remote training group (AIONG).
Participants in each group underwent their respective training programs. The effectiveness of the interventions was measured using Appendicular Skeletal Muscle Mass Index, Grip Strength, 6-meter Walking Speed, Timed-Up-and-Go Test, and Quality of Life assessments.
Significant improvements were observed across all groups in ASMI, Grip Strength, 6-meter Walking Speed, TUGT, and QoL. However, there were no statistically significant differences between the groups in terms of the magnitude of these improvements. AIONG showed outcomes comparable to OFFG and ONG methods.
AI-based telerehabilitation with 3D pose estimation is a viable and effective alternative for remote exercise interventions. It offers precise guidance and enhances the quality of rehabilitation training, demonstrating outcomes comparable to traditional and general online methods.
本研究探讨三维姿势估计技术在易筋经(一种中国传统运动)干预肌肉减少症老年人中的有效性。
一项随机对照试验,涉及93名参与者(平均年龄:71.64±7.09岁;男性41名,女性52名),分为三组:面对面线下传统训练组(OFFG)、一般远程在线训练组(ONG)和基于人工智能的在线远程训练组(AIONG)。
每组参与者接受各自的训练计划。使用四肢骨骼肌质量指数、握力、6米步行速度、定时起立行走测试和生活质量评估来衡量干预措施的有效性。
所有组在ASMI、握力、6米步行速度、TUGT和生活质量方面均有显著改善。然而,在这些改善的程度方面,各组之间没有统计学上的显著差异。AIONG的结果与OFFG和ONG方法相当。
基于人工智能的三维姿势估计远程康复是远程运动干预的一种可行且有效的替代方法。它提供精确指导并提高康复训练质量,其效果与传统和一般在线方法相当。