Rahimi Fariborz, Duval Christian, Jog Mandar, Bee Carina, South Angela, Jog Monica, Edwards Roderick, Boissy Patrick
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:5833-8. doi: 10.1109/IEMBS.2011.6091443.
While many studies have reported on the use of kinematic analysis on well-controlled, in-laboratory mobility tasks, few studies have examined the challenges of recording dynamic mobility in home environments. This preliminary study evaluated whole body mobility in eleven patients with Parkinson disease (H&Y 2-4). Patients were recorded in their home environment during scripted and non-scripted mobility tasks while wearing a full-body kinematic recording system using 11 inertial motion sensors (IMU). Data were analyzed with principal component analysis (PCA) in order to identify kinematic variables which best represent mobility tasks. Results indicate that there was a large degree of variability within subjects for each task, across tasks for individual subjects, and between scripted and non-scripted tasks. This study underscores the potential benefit of whole body multi-sensor kinematic recordings in understanding the variability in task performance across patients during daily activity which may have a significant impact on rehabilitation assessment and intervention.
虽然许多研究报告了在控制良好的实验室移动任务中使用运动学分析，但很少有研究探讨在家庭环境中记录动态移动的挑战。这项初步研究评估了11名帕金森病患者（H&Y 2-4级）的全身移动性。患者在家庭环境中进行脚本化和非脚本化移动任务时，佩戴使用11个惯性运动传感器（IMU）的全身运动学记录系统进行记录。数据采用主成分分析（PCA）进行分析，以识别最能代表移动任务的运动学变量。结果表明，每个任务在受试者内部、个体受试者的不同任务之间以及脚本化和非脚本化任务之间都存在很大程度的变异性。这项研究强调了全身多传感器运动学记录在理解日常活动中患者任务表现变异性方面的潜在益处，这可能对康复评估和干预产生重大影响。
