Estimating Upper-Limb Impairment Level in Stroke Survivors Using Wearable Inertial Sensors and a Minimally-Burdensome Motor Task
Estimating Upper-Limb Impairment Level in Stroke Survivors Using Wearable Inertial Sensors and a Minimally-Burdensome Motor Task
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DOI：
10.1109/tnsre.2020.2966950
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发表时间：
2020-03-01
影响因子：
4.9
通讯作者：
Lee, Sunghoon Ivan
中科院分区：
文献类型：
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作者：
Oubre, Brandon;Daneault, Jean-Francois;Lee, Sunghoon Ivan
上肢轻瘫是中风后最常见的运动障碍。目前自动评估上肢损伤的解决方案给患者及其护理人员带来了许多严重的负担，这些负担妨碍了频繁的评估。在这项工作中，我们提出了一种方法来估计上肢损伤中风幸存者使用两个可穿戴的惯性传感器，手腕和胸骨，和一个最小的繁重的运动任务。23名无、轻度或中度上肢损伤的卒中幸存者进行了两次重复的1 - 2分钟长的连续、随机（即，无模式），跨越整个运动范围的自主上肢运动。采用独特的运动分解技术，将三维上肢运动时间序列分割成一系列一维子运动。一个无监督的聚类算法和监督回归模型被用来估计Fugl-Meyer评估（FMA）分数的基础上提取这些子运动的特征。我们的回归模型估计FMA分数的归一化均方根误差为18.2%（r（2）=0.70），并且需要少至一分钟的运动数据来产生合理的估计性能。这些结果支持了频繁监测中风幸存者康复结果的可能性，最终能够制定个性化的康复计划。
Upper-limb paresis is the most common motor impairment post stroke. Current solutions to automate the assessment of upper-limb impairment impose a number of critical burdens on patients and their caregivers that preclude frequent assessment. In this work, we propose an approach to estimate upper-limb impairment in stroke survivors using two wearable inertial sensors, on the wrist and the sternum, and a minimally-burdensome motor task. Twenty-three stroke survivors with no, mild, or moderate upper-limb impairment performed two repetitions of one-to-two minute-long continuous, random (i.e., patternless), voluntary upper-limb movements spanning the entire range of motion. The three-dimensional time-series of upper-limb movements were segmented into a series of one-dimensional submovements by employing a unique movement decomposition technique. An unsupervised clustering algorithm and a supervised regression model were used to estimate Fugl-Meyer Assessment (FMA) scores based on features extracted from these submovements. Our regression model estimated FMA scores with a normalized root mean square error of 18.2% (r(2)=0.70) and needed as little as one minute of movement data to yield reasonable estimation performance. These results support the possibility of frequently monitoring stroke survivors' rehabilitation outcomes, ultimately enabling the development of individually-tailored rehabilitation programs.