Abstract:

Objective To explore the application effect of multimodal somatosensory exercise based on artificial intelligence technology in home rehabilitation exercise for elderly patients with chronic obstructive pulmonary disease（COPD），so as to promote COPD patients to participate in home rehabilitation exercise. Methods Using the convenient sampling method，80 elderly patients with COPD admitted to the Department of Respiratory Medicine of a tertiary A hospital in Urumqi from November 2023 to February 2024 were selected as the research subjects. According to the random number table method，they were divided into a control group and an experimental group，with 40 cases in each group. The control group adopted the traditional exercise training method，and the experimental group adopted the multi-modal somatosensory movement based on artificial intelligence technology for exercise intervention，with 5 times a week，and the intervention was implemented for 12 weeks. The pulmonary function index，modified Medical Research Council scale score，physical fitness level，Chronic Obstructive Pulmonary Disease Assessment Test scale score and exercise compliance of the 2 groups were compared before intervention and 12 weeks after intervention. Results 77 patients completed the study，with 39 in the experimental group and 38 in the control group. The forced vital capacity，forced expiratory volume in one second，forced expiratory volume in one second to forced vital capacity ratio，physical fitness level and exercise compliance of the experimental group were higher than those of the control group，while the modified British Medical Research Council scale score and Chronic Obstructive Pulmonary Disease Assessment Test score were lower than those of the control group. The differences were statistically significant（P<0.05）. Conclusion Somatosensory exercise based on artificial intelligence technology can improve the lung function of the patients with COPD，improve the exercise compliance and physical fitness indicators of elderly patients and improve the quality of life of the patients.

Key words: Pulmonary Disease，Chronic Obstructive, Aged, Artificial Intelligence, Exercise Training, Pulmonary Rehabilitation, Nursing Care

摘要：

目的 探讨基于人工智能的体感运动在老年慢性阻塞性肺疾病（简称“慢阻肺”）患者居家康复运动中的应用效果，以促进老年慢阻肺患者的肺功能康复。方法 采用便利抽样法，选取2023年11月—2024年2月乌鲁木齐市某三级甲等医院呼吸内科收治的80例老年慢阻肺患者为研究对象，采用随机数字表法将其分为试验组与对照组（每组各40例）。试验组采用基于人工智能的体感运动进行干预，每周5次，干预12周；对照组采用传统的运动训练方式。比较干预前和干预12周后两组肺功能指标、改良英国医学研究委员会呼吸困难量表得分、体适能水平、慢阻肺评估测试评分及运动依从性。结果 有77例慢阻肺患者完成该研究，其中，试验组39例，对照组38例。试验组第1秒用力呼气容积、用力肺活量、第1秒用力呼气容积占用力肺活量比值、体适能水平、运动依从性均优于对照组，而改良英国医学研究委员会呼吸困难量表得分、慢阻肺评估测试评分均低于对照组，两组比较，差异均有统计学意义（P<0.05）。结论 基于人工智能的体感运动可改善老年慢阻肺患者的肺功能，提高其运动依从性、体适能水平及生活质量。

关键词: 肺疾病，慢性阻塞性, 老年人, 人工智能, 运动训练, 肺康复, 护理