Clustering Method and Gaussian Mixture Model Applied to Electroencephalogram of Anti-NMDA Receptor Encephalitis
碩士 === 國立交通大學 === 統計學研究所 === 106 === The electroencephalography (EEG) is a useful tool for research and diagnosis in many medical fields due to its characteristic of being related to human consciousness. The human brain is divided into several parts. The EEG can reflect the brain function of parieta...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2018
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| Online Access: | http://ndltd.ncl.edu.tw/handle/2g6t74 |
| Summary: | 碩士 === 國立交通大學 === 統計學研究所 === 106 === The electroencephalography (EEG) is a useful tool for research and diagnosis in many medical fields due to its characteristic of being related to human consciousness. The human brain is divided into several parts. The EEG can reflect the brain function of parietal lobe, frontal lobe, temporal lobe and occipital lobe. The Anti-NMDA receptor encephalitis is a disease that might be missed diagnosed in the earlier stage. In this study, we analyze the EEG data of an Anti-NMDA receptor encephalitis patient by applying a clustering method and the Gaussian mixture model. The characteristics of the EEG data are discussed.
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