Supplementary Material for: Dual-Task Upper Extremity Motor Performance Measured by Video Processing as Cognitive-Motor Markers for Older Adults

Introduction: The use of dual-task model such as dual-task gait has been extensively studied to assess cognitive-motor performance among older adults. However, space restriction and safety factor limit its applications in remote assessment. To address the gap, we propose a video processing-based approach to remotely quantify cognitive-motor performance using a 20-second repetitive elbow flection-extension test with dual-task condition, called video-based motoric-cognitive meter (MCM). Methods: Eighteen older participants (age: 78.6±6.5 years) who were clinically diagnosed either as having mild cognitive impairment (MCI) or dementia were included in this study. Participants were asked to perform 20-second 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. Results: 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 (Minimum Mental State Examination, abbreviation: 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). Conclusion: 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.

引言：双任务步态等双任务模型已被广泛应用于老年人认知-运动表现的评估。然而，空间限制与安全因素制约了其在远程评估场景中的应用。为填补这一研究空白，本研究提出一种基于视频处理的方法，通过时长20秒的重复肘关节屈伸双任务测试，远程量化认知-运动表现，该方法被称为基于视频的运动-认知测量仪（motoric-cognitive meter，简称MCM）。
研究方法：本研究纳入18名老年受试者（年龄：78.6±6.5岁），经临床诊断为轻度认知障碍（mild cognitive impairment, MCI）或痴呆。受试者需完成时长20秒的重复肘关节屈伸运动，同时伴随记忆任务：从两位数开始倒序计数。测试过程中，通过摄像机记录前臂的所有运动轨迹。作为对照，本研究采用经过临床验证的腕部可穿戴传感器，该设备可量化上肢运动学参数。
研究结果：结果显示，本研究提出的基于视频的MCM所提取的双任务上肢运动表现，与经临床验证的基于传感器的MCM之间具有良好的一致性（相关系数r≥0.530，组内相关系数ICC2,1≥0.681）。此外，基于视频的MCM的部分指标（屈伸时间、伸展时间及屈伸总时长）与临床认知量表——简易精神状态检查表（Minimum Mental State Examination，缩写MMSE）之间存在中等程度的相关性（|r|≥0.496）。同时，部分双任务上肢运动表现指标（运动速度、屈伸时间、伸展时间及屈伸总时长）与双任务步态速度呈显著相关（|r|≥0.557），而双任务步态速度此前已被证实与认知障碍相关。最后，在线性回归分析中，所选的双任务运动表现指标（屈伸时间）能够有效预测MMSE评分，且具有统计学意义（校正决定系数adjusted R²=0.306，p=0.025）。
结论：本研究提出一种基于视频处理的方法，可通过简便的上肢功能测试分析双任务上肢运动表现。研究结果表明，相较于基于传感器的MCM，本研究提出的基于视频的MCM具有同时效度；且双任务上肢运动表现与临床验证的认知标志物（MMSE评分及双任务步态速度）存在关联。未来研究可进一步探索该方案的敏感性，以推动其在远程医疗应用中实现老年人认知-运动表现的远程评估。