An adaptive neuro-fuzzy inference system for sleep spindle detection

Sheng Fu Liang, Chih En Kuo, Yu Han Hu, Chun Yu Chen, Yu Hung Li

研究成果: Paper同行評審

4 引文 斯高帕斯(Scopus)

摘要

In this paper, an adaptive neuro-fuzzy inference system (ANFIS) for sleep spindle detection was developed. Two input variables including teager energy operator (TEO) and sigma index analyses of the EEG signals were extracted. 1180 training samples (0.5 s) of 15 subjects were used to ANFIS training, include 397 spindle and 783 non-spindle waveform. Then the 1519 epochs (30s) of other 15 subjects were used to evaluate the performance of ANFIS. The overall sensitivity and specificity of the ANFIS are 94.09% and 96.76%, respectively. Although the overall false positive rate is 38.58%, spindle and non-spindle successful detection rate could almost reach 90% for each subject. This method can integrate with various PSG systems for sleep monitoring in cognitive enhancements or sleep efficiency.

原文English
頁面369-373
頁數5
DOIs
出版狀態Published - 2012 十二月 1
事件2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012 - Taichung, Taiwan
持續時間: 2012 十一月 162012 十一月 18

Other

Other2012 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2012
國家Taiwan
城市Taichung
期間12-11-1612-11-18

All Science Journal Classification (ASJC) codes

  • Logic

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