美国 APDM 步态与平衡分析系统 Mobility Lab

摘要 · 中文整理：商用可穿戴传感系统是替代昂贵实验室设备进行临床步态评估的一种有前景的方案，但其对步态受损者的测量准确性尚未得到充分确认。本研究考察了 APDM Opal 可穿戴传感系统在健康对照者与慢性脑卒中个体中测量时空步态参数的效度与信度。受试者在仪器化步道上以不同速度条件各完成三次 10 米步行测试。步速与步幅指标达到优秀信度，但存在系统性低估；跨步时间与单步时间指标达到优秀信度且无显著误差；步态相位时长指标达到中等至优秀信度。本研究支持将 Opal 可穿戴传感器普遍用于获取脑卒中后步态障碍的定量测量指标。

原文摘要：Commercial wearable sensor systems are a promising alternative to costly laboratory equipment for clinical gait evaluation, but their accuracy for individuals with gait impairments is not well established. We investigated the validity and reliability of the APDM Opal wearable sensor system to measure spatiotemporal gait parameters for healthy controls and individuals with chronic stroke. Participants completed the 10 m walk test over an instrumented mat three times in different speed conditions. Gait speed and stride length measures achieved excellent reliability, though systematically underestimated. Stride and step time measures achieved excellent reliability with no significant errors. Gait phase duration measures achieved moderate-to-excellent reliability. This study supports general use of Opal wearable sensors to obtain quantitative measures of post-stroke gait impairment.

关键词：可穿戴传感器、步态分析、脑卒中、效度、信度、时空步态参数、步态不对称性

研究目标：解决商用可穿戴传感系统在步态受损（尤其是慢性脑卒中）人群中准确性不明的问题，明确行走速度与步长不对称程度如何影响 APDM Opal 系统时空步态参数的效度与信度。

主要结论：Opal 可穿戴传感器总体上可用于获取脑卒中后步态障碍的定量指标：步速与步幅信度优秀但分别被系统性低估 0.11 m/s 与 0.12 m，跨步时间与单步时间信度优秀且无显著误差，步态相位时长信度为中等至优秀、相对误差 4.13%～21.59%；对中重度不对称或步速慢于 0.80 m/s 的个体，测值需谨慎解释。

创新点：不是笼统给出一个效度结论，而是把步行速度条件与步长不对称程度作为显式自变量分层检验，首次界定了该商用系统在脑卒中人群中的失效边界（步速 0.80 m/s 阈值与中重度不对称），并区分了可校正的系统性偏差与不可校正的随机误差。

后续建议：针对步速低于 0.80 m/s 的重度受损人群优化事件检测算法，降低步态相位时长的相对误差；建立随步速与不对称程度变化的动态校正模型，替代单一固定偏差校正；在急性期与亚急性期脑卒中患者中重复验证，考察效度是否随恢复阶段变化；纳入使用助行器或踝足矫形器的患者，评估辅助器具对传感器事件检测的干扰；将验证场景从 10 米直线步行扩展到转身、上下楼梯等复杂任务与日常自由行走

APA 引文：Lanotte, F., Shin, S. Y., O'Brien, M. K., & Jayaraman, A. (2023). Validity and reliability of a commercial wearable sensor system for measuring spatiotemporal gait parameters in a post-stroke population: the effects of walking speed and asymmetry. Physiological Measurement, 44(8), 085005. https://doi.org/10.1088/1361-6579/aceecf

仪器引用：We investigated the validity and reliability of the APDM Opal wearable sensor system to measure spatiotemporal gait parameters for healthy controls and individuals with chronic stroke. Participants completed the 10 m walk test over an instrumented mat three times in different speed conditions.

摘要 · 中文整理：本研究采用探索性因子分析识别 ISway 评估所测量的相互独立的平衡功能域，并在多发性硬化患者与神经功能正常对照之间、以及有跌倒史与无跌倒史的多发性硬化患者之间比较模型导出的各功能域。探索性因子分析在多发性硬化人群中产生了 3 个彼此区分的平衡功能域：1）摇摆幅值与速度，2）左右向摇摆频率与 Jerk，3）前后向摇摆频率与 Jerk。

原文摘要：This study used EFA to identify independent domains of balance measured during the ISway assessment and compared the model-derived domains between PwMS and neurotypical controls and between PwMS with and without a history of falls. The EFA produced 3 distinct balance domains in MS: 1) sway amplitude and velocity, 2) ML sway frequency and jerk, and 3) AP sway frequency and jerk.

关键词：平衡、姿势、跌倒、多发性硬化、康复

研究目标：解决 ISway 输出的姿势摇摆指标数量多、彼此高度相关、临床难以解释的问题，识别相互独立的平衡功能域，并确定哪些功能域与多发性硬化患者的平衡缺损及跌倒史相关。

主要结论：ISway 测得的摇摆指标可归纳为 3 个相互独立的平衡功能域——摇摆幅值与速度、左右向摇摆频率与 Jerk、前后向摇摆频率与 Jerk，共解释 85.44% 的方差；多发性硬化患者、尤其是有跌倒史者，在摇摆幅值与速度这一功能域上表现出不成比例的损害，而两个频率与 Jerk 域未见显著组间差异。

创新点：把 ISway 的 22 项高维摇摆指标用探索性因子分析压缩为 3 个正交、临床可解释的平衡功能域，并在此结构上做组间比较，避免了逐指标多重比较带来的假阳性；同时识别出跌倒风险主要关联幅值与速度域，为姿势控制评估提供了降维后的靶向指标。

后续建议：开展前瞻性随访，检验摇摆幅值与速度域能否预测未来跌倒而非仅回顾性区分跌倒史；在中重度残疾的多发性硬化队列中重复因子结构，验证 3 域模型的稳定性；用验证性因子分析在独立样本上确认该结构，而非停留在探索性阶段；增加闭眼、窄支撑面、泡沫面等更具挑战的站立条件，考察功能域结构是否随任务难度变化；将平衡功能域与针对性康复训练方案配对，验证域特异性干预的有效性

APA 引文：Monaghan, P. G., Monaghan, A. S., Hooyman, A., Fling, B. W., Huisinga, J. M., & Peterson, D. S. (2023). Utilizing the ISway to identify and compare balance domain deficits in people with multiple sclerosis. Archives of Physical Medicine and Rehabilitation, 104(9), 1456-1464. https://doi.org/10.1016/j.apmr.2023.02.018

仪器引用：Quantitative balance measures were obtained via Mobility Lab's ISway protocol and Opal inertial sensors (50 Hz; APDM Inc., Portland, OR.). Outcomes were derived from an inertial sensor placed on the fifth lumbar vertebrae. Participants completed three 30-second ISway trials, and sway measures were averaged across the three trials. Foot placement was standardized using the APDM base of support plate to ensure consistent stance width.

摘要 · 中文整理：仪器化步态垫系统一直被视为测量时空步态参数的金标准方法之一。但其便携式步道把行走限制在一块很小的区域内，能够采集到的步态周期数量也因此受限。可穿戴惯性传感器是一种潜在的替代方案，允许更自然的行走行为，且受空间限制更少。本初步研究的目的是在较大年龄儿童中，建立体表佩戴传感器相对于便携式步道系统的同期效度。结果支持可穿戴惯性传感器在 2 分钟步行测试中测量 7 岁及以上儿童步速、步频、步态周期时长与步幅的效度。

原文摘要：Instrumented gait mat systems have been regarded as one of the gold standard methods for measuring spatiotemporal gait parameters. However, their portable walkways confine walking to a restricted area and limit the number of gait cycles collected. Wearable inertial sensors are a potential alternative that allow more natural walking behavior and have fewer space restrictions. The objective of this pilot study was to establish the concurrent validity of body-worn sensors against the portable walkway system in older children. These results support the validity of wearable inertial sensors in measuring gait speed, cadence, gait cycle duration, and stride length in children 7 years old and above during a 2-min walking test.

关键词：加速度计、可穿戴技术、儿科

研究目标：解决仪器化步态垫采集空间受限、可采集步态周期数少的问题，明确体表佩戴惯性传感器能否在儿童 2 分钟步行测试中替代便携式步道系统测量时空步态参数。

主要结论：对 7～17 岁儿童而言，体表佩戴的惯性传感器在测量步速、步频、步态周期时长与步幅方面可作为仪器化步态垫的可行替代方案；但双支撑时间存在系统性不一致，其偏差显著受体重、年龄、身高与行走节奏影响，原因可能在于两套系统对足跟着地与足尖离地事件的判定方式不同。

创新点：首次在儿童人群中，通过定制同步电缆实现 Mobility Lab 与 GAITRite 的硬件级触发同步，从而在同一次 2 分钟步行中逐趟配对两套系统的测值；并采用贝叶斯多元线性回归对偏差的协变量（性别、年龄、身高、体重、步速）建模，而非仅报告平均一致性。

后续建议：扩大样本量并纳入脑瘫、肌营养不良等病理步态儿童，检验效度结论在异常步态下是否成立；针对双支撑相的系统性偏差，建立以体重、身高、步速为输入的校正模型并做独立验证；比较足背与踝部等不同传感器放置方案在低龄儿童中的效度差异；将测试延伸到 6 分钟步行或日常自由行走场景，评估长时间采集下的漂移与疲劳效应；补充同一受试者跨日重复测量，报告重测信度而非仅同期效度

APA 引文：Shieh, V., Zampieri, C., Sansare, A., Collins, J., Bulea, T. C., & Jain, M. (2022). Validation of body-worn sensors for gait analysis during a 2-min walk test in children. Journal for the Measurement of Physical Behavior, 5(2), 111-119. https://doi.org/10.1123/jmpb.2021-0035

仪器引用：Each child wore a total of three APDM Opal inertial sensors; one positioned on the lower back at the S2 level and on the dorsal aspect of each foot, which has demonstrated better validity than placement at the ankle. ... Simultaneously, we wirelessly acquired and analyzed inertial-based spatiotemporal data through the MobilityLab (version 2) software. ... For synchronization of both data collection systems, we created a custom cable with a 6-pin mini-din and 3.5-mm auxiliary cable. MobilityLab was set to release an output trigger to the GAITRite data acquisition computer upon the start of the test. ... We used the iWalk module, which is designed for straight line walking, and set the custom timing to 2 min.

摘要 · 中文整理：帕金森病会导致步态与平衡功能进行性恶化，这种恶化可以通过计算机化设备加以测量。我们利用帕金森病生物标志物计划的纵向数据库，以确定基线步态与平衡测量指标能否预测未来的症状进展速率。我们分别纳入了具有 6、12、18、24 个月随访的 230、222、164、177 名帕金森病受试者，并将进展定义为以下临床参数的恶化：MDS-UPDRS 总分、蒙特利尔认知评估、PDQ-39 移动性分量表、左旋多巴等效日剂量、Schwab-England 评分以及全局复合结局。我们建立岭回归模型，独立估计每一项步态或平衡指标、或指标组合对进展的预测能力。每个岭回归模型的准确率通过交叉验证计算，即用 90% 的数据估计岭回归模型，再在留出的 10% 数据上检验。尽管模型对 6 个月随访时的结局变化有一定预测力（准确率在 66%～71% 之间），但在这一短暂随访期内结局变量并未发生变化（MDS-UPDRS 总分变化中位数为 0，左旋多巴等效日剂量变化为 0）。在 12、18 和 24 个月的随访期，模型未能预测变化（留出集准确率在 42% 至 60% 之间）。我们的结论是，在基线进行的这一组计算机化步态与平衡测量指标，不大可能有助于预测帕金森病未来的疾病进展。研究人员必须继续寻找进展预测因子，以提升疾病修饰性临床试验的效能。

原文摘要：Parkinson's disease (PD) results in progressively worsening gait and balance dysfunction that can be measured using computerized devices. We utilized the longitudinal database of the Parkinson's Disease Biomarker Program to determine if baseline gait and balance measures predict future rates of symptom progression. We included 230, 222, 164, and 177 PD subjects with 6, 12, 18, and 24 months of follow-up, respectively, and we defined progression as worsening of the following clinical parameters: MDS-UPDRS total score, Montreal Cognitive Assessment, PDQ-39 mobility subscale, levodopa equivalent daily dose, Schwab and England score, and global composite outcome. We developed ridge regression models to independently estimate how each gait or balance measure, or combination of measures, predicted progression. The accuracy of each ridge regression model was calculated by cross-validation in which 90% of the data were used to estimate the ridge regression model which was then tested on the 10% of data left out. While the models modestly predicted change in outcomes at the 6-month follow-up visit (accuracy in the range of 66-71%) there was no change in the outcome variables during this short follow-up (median change in MDS-UPDRS total score = 0 and change in LEDD = 0). At follow-up periods of 12, 18, and 24 months, the models failed to predict change (accuracy in the held-out sets ranged from 42 to 60%). We conclude that this set of computerized gait and balance measures performed at baseline is unlikely to help predict future disease progression in PD. Research scientists must continue to search for progression predictors to enhance the performance of disease modifying clinical trials.

关键词：帕金森病、步态、平衡、疾病进展、临床试验

研究目标：解决帕金森病疾病修饰性临床试验中缺乏进展预测因子的问题，检验用 APDM Mobility Lab 在基线测得的 iTUG 与 iSway 步态平衡指标能否预测未来 6 至 24 个月的症状进展速率。

主要结论：APDM iSway（版本 1 与版本 2）与 iTUG 程序在基线测得的这组计算机化步态与平衡指标，无法预测 12、18、24 个月随访时以标准临床结局衡量的未来症状进展速率；6 个月时 66%～71% 的准确率并无实质意义，因为该期间结局变量本身几乎没有变化。研究者仍需继续寻找有效的进展预测因子。

创新点：在大规模多中心纵向队列上对 iTUG 的 96 项与 iSway 的 46 项（及重算后的 33 项）高维指标做系统化的预测力检验，采用岭回归加留出集交叉验证的严格框架；并且明确报告了阴性结果，同时指出短随访期高准确率因结局无变化而不可解释，为该类数字指标的应用边界提供了重要的反面证据。

后续建议：把单次诊室内测量改为日常生活环境下的连续佩戴监测，考察生态学指标是否具有更强预测力；引入纵向变化率（多时点斜率）而非仅用基线值作为预测因子；将步态平衡指标与影像、体液生物标志物及遗传数据联合建模，检验多模态组合的增量预测价值；改用非线性机器学习方法并在独立外部队列上验证，排除岭回归线性假设导致的漏检；在进展更快的亚型（如姿势不稳-步态障碍型）中单独分析，避免整体队列稀释亚组信号

APA 引文：Dewey, D. C., Chitnis, S., McCreary, M. C., Gerald, A., Dewey, C. H., Pantelyat, A., Dawson, T. M., Rosenthal, L. S., & Dewey, R. B., Jr. (2022). APDM gait and balance measures fail to predict symptom progression rate in Parkinson's disease. Frontiers in Neurology, 13, 1041014. https://doi.org/10.3389/fneur.2022.1041014

仪器引用：gait and balance testing with the APDM Mobility Lab (version 1) using two programs, the instrumented Timed Up and Go (iTUG) test and the instrumented test of postural sway (iSway). The iTUG calculates 96 unique variables describing gait, turns, sit to stand, and turn to sit transitions. The iSway produces 46 unique parameters describing the sway of the body in static stance. After affixing sensors to the wrists, ankles, lumbar area and chest, for the iTUG, patients stand from a chair, walk 6 meters, turn, walk back to the chair, and sit. For the iSway, patients stand for 30 s on a firm surface with their arms crossed and feet spaced 26 cm apart. For each test program, subjects completed three trials, and the median value of each parameter was used for analysis.