期刊
BIO-MEDICAL MATERIALS AND ENGINEERING
卷 23, 期 6, 页码 513-531出版社
IOS PRESS
DOI: 10.3233/BME-130773
关键词
Statistical signal characterization; FFT spectrum; Parkinson tremor; essential tremor; accelerometer signals; discrimination
资金
- Sultan Qaboos University [IG/ENG/ECED/11/04]
- DAAD (German Academic Exchange Service)
- German Research Council (Deutsche Forschungsgemeinschaft, DFG) [SFB 855]
A new technique for discrimination of Parkinson tremor from essential tremor is presented in this paper. This technique is based on Statistical Signal Characterization (SSC) of the spectrum of the accelerometer signal. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. Two sets of data are used. The training set, which consists of 21 essential-tremor (ET) subjects and 19 Parkinson-disease (PD) subjects, is used to obtain the threshold value of the classification factor differentiating between the two subjects. The test data set, which consists of 20 ET and 20 PD subjects, is used to test the technique and evaluate its performance. Three of twelve newly derived SSC parameters show good discrimination results. Specific results of those three parameters on training data and test data are shown in detail. A linear combination of the effects of those parameters on the discrimination results is also included. A total discrimination accuracy of 90% is obtained.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据