计算机自动识别足底压力信号功率谱：帕金森病患者与对照组的步态分析

背景：基于帕金森的步态研究是当前的热点之一，但是很少有人从足底压力入手来研究帕金森病患者行走中的步态特点。 目的：从帕金森患者和对照组步态数据中提取特征进行对比，以期为计算机自动识别打下基础。同时希望从患者的步态中提取规律，通过信号处理的方法，帮助解释这种受扰动的步态。 方法：在分析足底压力时应用自回归(AR)模型，利用Yule-Walker方程进行功率谱的计算。在进行对比时，定义了相对分离指数用来测量功率谱在某一频率时的分离程度。分析来源于Ga, Ju 和Si的3组观察指标，分别包含18，25，29名正常对照以及29，29，35例帕金森病患者。 结果与结论：通过计算得到了帕金森病患者和正常对照的Yule-Walker功率谱密度分布图，可以发现，谱线的分布、密度、疏密程度有明显的差别。帕金森病患者的谱线排列紧密且彼此相似度高，正常对照的谱线排列疏松且彼此差异较大。

Foot sole pressure signal power spectra based on computer recognition: Gait analysis between Parkinson s patients and controls

BACKGROUND: Gait of Parkinson s disease (PD) is a research focus. However, few studies explored the gait features from the pressures of sole of foot. OBJECTIVE: To compare extracted features from the foot-pressure signals in PD patients and control subjects and realize automatic recognition by computer, so as to extract the pattern of walking in PD and help explain the disturbed gait through signal processing. METHODS: Autoregressive (AR) model was applied to the analysis of foot-pressure based on Yule-Walker equation for the calculation of power spectra. In the comparison process, we also gave our own definition to Associated Discrete Index in order to measure the discrete degree at a same frequency. The data from three research groups: Ga, Ju and Si were analyzed. The database included 18, 25, 29 control subjects and 29, 29, 35 PD patients respectively. RESULTS AND CONCLUSION: In different framework, obvious difference between PD patient and control subject through t-test was observed in spectral line distribution, and density. Spectral line of PD patients was dense with similar appearance compared with normal controls.