DocumentCode :
1720317
Title :
Classification of fNIRS data using wavelets and support vector machine during speed and force imagination
Author :
Xu, Baolei ; Fu, Yunfa ; Miao, Lei ; Wang, Zhidong ; Li, Hongyi
Author_Institution :
State Key Lab. of Robot., SIA, Shenyang, China
fYear :
2011
Firstpage :
1224
Lastpage :
1229
Abstract :
In this paper, we present a method for classifying functional near-infrared spectroscopy (fNIRS) data using wavelets and support vector machine (SVM). fNIRS data is acquired by ETG-4000 during speed and force imagination. Probes location is around C3 and C4 in 10-20 international system. After preprocessing the data using NIRS-SPM, we decompose it with `db5´ wavelet for 9 levels to do a multiresolution analysis (MRA). Then, the approximation and detail signal at every level are used for SVM classification using libSVM toolbox. The results show that frequency band between 0.02 and 0.08Hz is important for classification, especially frequency band between 0.02 and 0.04Hz. This finding is useful for building an fNIRS-based brain computer interface (BCI) system.
Keywords :
brain-computer interfaces; infrared spectra; medical image processing; pattern classification; support vector machines; ETG-4000; NIRS-SPM; SVM classification; db5 wavelet; fNIRS data classification; fNIRS-based brain computer interface; force imagination; functional near-infrared spectroscopy data classification; international system; libSVM toolbox; multiresolution analysis; speed imagination; support vector machine; Accuracy; Approximation methods; Electroencephalography; Force; Multiresolution analysis; Robots; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on
Conference_Location :
Karon Beach, Phuket
Print_ISBN :
978-1-4577-2136-6
Type :
conf
DOI :
10.1109/ROBIO.2011.6181455
Filename :
6181455
Link To Document :
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