Del Din Silvia, Patel Shyamal, Cobelli Claudio, Bonato Paolo
Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital, Boston, MA 02114, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:5839-42. doi: 10.1109/IEMBS.2011.6091444.
Clinical assessment scales to evaluate motor abilities in stroke survivors could be used to individualize rehabilitation interventions thus maximizing motor gains. Unfortunately, these scales are not widely utilized in clinical practice because their administration is excessively time-consuming. Wearable sensors could be relied upon to address this issue. Sensor data could be unobtrusively gathered during the performance of motor tasks. Features extracted from the sensor data could provide the input to models designed to estimate the severity of motor impairments and functional limitations. In previous work, we showed that wearable sensor data collected during the performance of items of the Wolf Motor Function Test (a clinical scale designed to assess functional capability) can be used to estimate scores derived using the Functional Ability Scale, a clinical scale focused on quality of movement. The purpose of the study herein presented was to investigate whether the same dataset could be used to estimate clinical scores derived using the Fugl-Meyer Assessment scale (a clinical scale designed to assess motor impairments). Our results showed that Fugl-Meyer Assessment Test scores can be estimated by feeding a Random Forest with features derived from wearable sensor data recorded during the performance of as few as a single item of the Wolf Motor Function Test. Estimates achieved using the proposed method were marked by a root mean squared error as low as 4.7 points of the Fugl-Meyer Assessment Test scale.
用于评估中风幸存者运动能力的临床评估量表可用于使康复干预个体化，从而最大限度地提高运动功能恢复。不幸的是，这些量表在临床实践中并未得到广泛应用，因为其使用过程过于耗时。可依赖可穿戴传感器来解决这一问题。在进行运动任务时，可以不引人注意地收集传感器数据。从传感器数据中提取的特征可为旨在估计运动障碍严重程度和功能限制的模型提供输入。在之前的工作中，我们表明，在执行沃尔夫运动功能测试（一种旨在评估功能能力的临床量表）项目期间收集的可穿戴传感器数据，可用于估计使用功能能力量表得出的分数，该量表是一种关注运动质量的临床量表。本文所述研究的目的是调查同一数据集是否可用于估计使用 Fugl-Meyer 评估量表（一种旨在评估运动障碍的临床量表）得出的临床分数。我们的结果表明，通过向随机森林输入从在执行沃尔夫运动功能测试的单个项目期间记录的可穿戴传感器数据中提取的特征，可估计 Fugl-Meyer 评估测试分数。使用所提出方法获得的估计值的均方根误差低至 Fugl-Meyer 评估测试量表的 4.7 分。
