Mancini Martina, Chiari Lorenzo, Holmstrom Lars, Salarian Arash, Horak Fay B
Department of Neurology, School of Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR, USA.
Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy.
Gait Posture. 2016 Jan;43:125-31. doi: 10.1016/j.gaitpost.2015.08.015. Epub 2015 Sep 25.
Anticipatory postural adjustments (APAs) prior to gait initiation have been largely studied in traditional, laboratory settings using force plates under the feet to characterize the displacement of the center of pressure. However clinical trials and clinical practice would benefit from a portable, inexpensive method for characterizing APAs. Therefore, the main objectives of this study were (1) to develop a novel, automatic IMU-based method to detect and characterize APAs during gait initiation and (2) to measure its test-retest reliability. Experiment I was carried out in the laboratory to determine the validity of the IMU-based method in 10 subjects with PD (OFF medication) and 12 control subjects. Experiment II was carried out in the clinic, to determine test-retest reliability of the IMU-based method in a different set of 17 early-to-moderate, treated subjects with PD (tested ON medication) and 17 age-matched control subjects. Results showed that gait initiation characteristics (both APAs and 1st step) detected with our novel method were significantly correlated to the characteristics calculated with a force plate and motion analysis system. The size of APAs measured with either inertial sensors or force plate was significantly smaller in subjects with PD than in control subjects (p<0.05). Test-retest reliability for the gait initiation characteristics measured with inertial sensors was moderate-to-excellent (0.56<ICC<0.82) for both groups. Our findings support the feasibility of automatically characterizing postural preparation and gait initiation with body-worn inertial sensors that would be practical for unsupervised clinical and home settings.
在传统的实验室环境中，人们主要通过使用置于脚下的测力板来研究步态起始前的预期姿势调整（APAs），以表征压力中心的位移。然而，临床试验和临床实践将受益于一种用于表征APAs的便携、廉价方法。因此，本研究的主要目标是：（1）开发一种基于惯性测量单元（IMU）的新型自动方法，用于在步态起始期间检测和表征APAs；（2）测量其重测信度。实验I在实验室中进行，以确定基于IMU的方法在10名帕金森病（PD）患者（未服药）和12名对照受试者中的有效性。实验II在临床环境中进行，以确定基于IMU的方法在另一组17名早中期接受治疗的PD患者（服药后测试）和17名年龄匹配的对照受试者中的重测信度。结果表明，用我们的新方法检测到的步态起始特征（包括APAs和第一步）与用测力板和运动分析系统计算出的特征显著相关。PD患者中，用惯性传感器或测力板测量的APAs大小明显小于对照受试者（p<0.05）。两组中，用惯性传感器测量的步态起始特征的重测信度为中度至优秀（0.56<组内相关系数<0.82）。我们的研究结果支持了使用可穿戴惯性传感器自动表征姿势准备和步态起始的可行性，这对于无监督的临床和家庭环境是切实可行的。
