IEEE Trans Neural Syst Rehabil Eng. 2013 Nov;21(6):999-1005. doi: 10.1109/TNSRE.2013.2268251. Epub 2013 Jun 18.
Gait analysis is a valuable tool for obtaining quantitative information on motor deficits in Parkinson's disease (PD). Since the characteristic gait patterns of PD patients may not be fully identified by brief examination in a clinic, long-term, and unobtrusive monitoring of their activities is essential, especially in a nonclinical setting. This paper describes a single accelerometer-based gait analysis system for the assessment of ambulatory gait properties. Acceleration data were recorded continuously for up to 24 h from normal and PD subjects, from which gait peaks were picked out and the relationship between gait cycle and vertical gait acceleration was evaluated. By fitting a model equation to the relationships, a quantitative index was obtained for characterizing the subjects' walking behavior. The averaged index for PD patients with gait disorder was statistically smaller than the value for normal subjects. The proposed method could be used to evaluate daily gait characteristics and thus contribute to a more refined diagnosis and treatment of the disease.
步态分析是一种获取帕金森病（PD）运动缺陷定量信息的有效工具。由于 PD 患者的特征性步态模式可能无法通过诊所的简短检查完全识别，因此对其活动进行长期、非干扰性监测至关重要，尤其是在非临床环境中。本文描述了一种基于单个加速度计的步态分析系统，用于评估非卧床步态特性。从正常和 PD 受试者中连续记录长达 24 小时的加速度数据，从中提取步态峰值，并评估步态周期与垂直步态加速度之间的关系。通过将模型方程拟合到这些关系中，获得了一个定量指标，用于描述受试者的行走行为。患有步态障碍的 PD 患者的平均指标在统计学上小于正常受试者的值。该方法可用于评估日常步态特征，从而有助于更精细地诊断和治疗该疾病。
