A Systematic Approach for Long-term Meditation EEG Overview

• Main Authors: Yi-ping Chang, 張逸屏
• Other Authors: Pei-Chen Lo
• Format: Others
• Language: en_US
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/84200235383481716930

碩士 === 國立交通大學 === 電機與控制工程系 === 90 === The aim of this thesis is to develop a systematic approach to provide an overview of long-term meditation EEG (electroencephalograph). This approach translates the long-term EEG raw record into a summary report which can be evaluated at a glance. The proposed method involves four key steps: (1) segmentation; (2) feature extraction (quantification); (3) classification; and (4) display for visualization. The first step is to break the EEG into segments of similar characteristics based on pre-specified criteria. Then the feature vector of each segment is extracted and classified. Thus, the segments with similar patterns are clustered into the same group. Finally, the results include two parts: (1) the chronological evolution of clusters, that is, the compressed temporal profile of the EEG record, and (2) the representative EEG waveform pattern of each cluster. In addition, the parameters in the clustering strategy are discussed. Some case studies using typical meditation EEG patterns are conducted in this thesis. This systematic approach could assist us in reviewing the long-term EEG of different states and further investigating the meditation process.