摘要目的:利用新型可穿戴式惯性运动捕捉设备描绘中老年人的精细运动特征，探索精细运动缺陷与整体认知功能及各认知维度之间的相关性。方法:于2022年11月至2023年4月招募≥50岁受试者。应用蒙特利尔认知评估量表(Montreal Cognitive Assessment Scale，MoCA)对受试者认知功能进行评估，以雷达图展示认知功能各维度受损情况，利用新型可穿戴式微机电系统(microelectromechanical system，MEMS)惯性传感器的动作捕捉技术自主研发计算机电子化精细运动评估系统，实现对双手精细运动的细节捕捉和量化评估，比较两组双手精细运动功能特征差异，应用斯皮尔曼相关分析和多因素逻辑回归探究精细运动缺陷和认知功能障碍之间的相关性。结果:共招募289例受试者，其中认知障碍组140例(48.4%)，非认知障碍组149例(51.6%)认知障碍组和非认知障碍组MoCA分数分别为(22.2±2.79)分和(27.7±1.19)分( P<0.001)。应用电子化评估系统对精细运动功能进行评估，结果显示，认知障碍组老年人在3项数字化测评任务的手功能运动参数均明显更差。斯皮尔曼相关分析证实精细运动功能缺陷和认知功能障碍具有相关性，在多因素逻辑回归模型中，对年龄、性别、受教育程度、工作类型、家庭收入、婚姻状态、躯体功能等潜在混杂因素进行校正后，两者之间仍具有相关性。 结论:本研究利用新型可穿戴式动作捕捉技术实现了对精细运动功能的数字化评估，并证实中老年人群的精细运动功能缺陷与认知功能障碍具有相关性。

abstractsObjective:To characterize fine motor function in middle-aged and elderly individuals utilizing a novel wearable inertial motion capture device.Additionally, it seeks to investigate the relationship between fine motor deficits and overall cognitive function, as well as various cognitive dimensions.Methods:Participants aged 50 years and older were recruited between November 2022 and April 2023.The Montreal Cognitive Assessment Scale(MoCA)was employed to evaluate the cognitive function of the subjects, and a radar chart was utilized to illustrate the extent of impairment across different cognitive dimensions.An independent computerized fine motor evaluation system was developed using the motion capture technology of a novel wearable microelectromechanical system(MEMS)inertial sensor, enabling a quantitative assessment of fine motor skills.The differences in fine motor function characteristics between the two groups were compared.Spearman's correlation analysis and multivariate logistic regression were conducted to examine the relationship between fine motor deficits and cognitive dysfunction.Results:A total of 289 participants were recruited, among whom 140(48.4%)were classified into the cognitive impairment group.The mean MoCA scores for the cognitive impairment group and the non-cognitive impairment group were 22.2 ± 2.79 and 27.7 ± 1.19, respectively( P<0.001).The electronic assessment of fine motor function revealed that the motion parameters of hand function in the cognitive impairment group were significantly poorer across all three numerical evaluation tasks.Spearman's correlation analysis demonstrated a robust correlation between deficits in fine motor function and cognitive dysfunction.Furthermore, in the multiple logistic regression model, after adjusting for potential confounding factors including age, gender, and education level, a significant association between cognitive dysfunction and fine motor dysfunction persisted. Conclusions:A novel wearable motion capture technology was employed to facilitate the digital assessment of fine motor function.The findings revealed a significant correlation between deficits in fine motor function and cognitive dysfunction among middle-aged and elderly populations.