Eighteen older participants (age: 78.6 ± 6.5 years) who were clinically diagnosed as having either mild cognitive impairment or dementia were included in this study. Participants were asked to perform 20-s repetitive elbow flexion-extension exercise with a memory exercise by counting backward from a two-digit number. During the test, all movements of the forearm were recorded by a video camera. As a comparator, a validated wrist-worn sensor was used, which allowed quantifying upper extremity kinematics.
The results showed a good agreement (r ≥ 0.530 and ICC2,1 ≥ 0.681) between the derived dual-task upper extremity motor performance from the proposed video-based MCM and a clinically validated sensor-based MCM. We also observed moderate correlations (r ≥ 0.496) between some measures of video-based MCM (flexion time, extension time, and flexion-extension time) and clinical cognitive scale (Mini-Mental State Examination [MMSE]). Additionally, some measures of dual-task upper extremity motor performance (speed, flexion time, extension time, and flexion-extension time) were associated with dual-task gait speed (r ≥ 0.557), which has been found to be correlated with cognitive impairment. Lastly, the selected dual-task motor performance metric (flexion time) was sensitive to predict MMSE scores in linear regression analyses with statistical significance (adjusted R2 = 0.306, p = 0.025).
This study proposes a video processing-based approach to analyze dual-task upper extremity motor performance from a simple and convenient upper extremity function test. The results indicate concurrent validity of the proposed video-based MCM compared with the sensor-based MCM, and associations between dual-task upper extremity motor performance and clinically validated cognitive markers (MMSE scores and dual-task gait). Future studies are warranted to explore sensitivity of this solution to promote remote assessment of cognitive-motor performance among older adults in telehealth applications.
方法:这项研究纳入了18名年龄较大的参与者(年龄:78.6±6.5岁),他们被临床诊断为轻度认知障碍(MCI)或痴呆。要求参与者通过从两位数数字向后计数,进行20秒的重复性肘部屈伸运动和记忆运动。在测试过程中,前臂的所有运动均由摄像机记录.作为一个比较器,使用了经过验证的手腕穿戴传感器,这允许量化上肢运动学。
结果:结果显示,从基于视频的MCM和临床验证的基于传感器的MCM得出的双任务上肢运动性能之间具有良好的一致性(r≥0.530和ICC2,1≥0.681)。我们还观察到基于视频的MCM(屈曲时间,延长时间,和屈伸时间)和临床认知量表(最低精神状态检查,缩写:MMSE)。此外,双任务上肢电机性能的一些衡量标准(速度,屈曲时间,延长时间,和屈伸时间)与双任务步态速度(|r|≥0.557)相关,已发现与认知障碍有关。最后,在线性回归分析中,选定的双任务运动表现指标(屈曲时间)对预测MMSE评分敏感,具有统计学意义(校正后的R2=0.306,p=0.025).
结论:本研究提出了一种基于视频处理的方法,从简单方便的上肢功能测试中分析双任务上肢运动表现。结果表明,与基于传感器的MCM相比,基于视频的MCM的并发有效性。以及双任务上肢运动表现和临床验证的认知标志物(MMSE评分和双任务步态)之间的关联。未来的研究有必要探索这种解决方案的敏感性,以促进远程医疗应用中老年人认知运动表现的远程评估。