Title :
Extraction and analysis of EEG features under electric stimulation
Author :
Yi Liu ; Xiaoming Wu ; Mingku Feng
Author_Institution :
Dept. of Electron. Inf. Eng., Guangdong Polytech. Normal Univ., Guangzhou, China
Abstract :
In the paper, the EEG features under electrical stimulation is studied. After analysis the data that collected in experiment by the method of wavelet entropy and complexity, we found that electrical stimulation can obviously change the complexity of brain signals, and the wavelet energy entropy of its brain signals have notable changes as well. According the result of coherence estimation, it is found that electrical stimulation has notable effects to brain. It provides a new method to study the influence to brain by electrical simulation that used in rehabilitation of hemiplegic patients with stroke.
Keywords :
bioelectric potentials; data analysis; diseases; electroencephalography; entropy; feature extraction; neurophysiology; patient rehabilitation; patient treatment; wavelet transforms; EEG feature analysis; EEG feature extraction; brain signal complexity; data analysis; electric stimulation; electroencephalography; hemiplegic patient rehabilitation; stroke; wavelet energy entropy; Brain modeling; Coherence; Complexity theory; Electrical stimulation; Electroencephalography; Entropy; Wavelet analysis; Coherence estimation; Complexity; EEG; Electrical simulation; Wavelet entropy;
Conference_Titel :
Medical Imaging Physics and Engineering (ICMIPE), 2013 IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4799-6305-8
DOI :
10.1109/ICMIPE.2013.6864546
