@inproceedings{96907a16a88d4173800862356c6c9212,
title = "Combination of genetic algorithm and hidden markov model for EEG-based automatic sleep staging",
abstract = "In this paper, we propose a strategy that combines Genetic Algorithm (GA) and HMM to improve the recognition rate of sleep staging. The GA is used to train a better codebook for HMM. With this method, the accuracy and efficiency of sleep medical diagnosis can be expected to be improved. Moreover, some features used in other research are selected as supporting features. These features are used to train the HMM model and then fed into the trained HMM for recognition. Unlike the existing research on sleep staging by HMM, in which the modeling of HMM is independent of the special properties of the sleep stage transition, the HMM in this study is adjusted to meet these properties. The experimental results show that the proposed method greatly enhances the recognition rate compared with other existing research.",
author = "Liang, {Sheng Fu} and Chen, {Ching Fa} and Zeng, {Jian Hong} and Pan, {Shing Tai}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 2nd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2013 ; Conference date: 12-12-2013 Through 14-12-2013",
year = "2014",
doi = "10.1007/978-3-319-04573-3_109",
language = "English",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "891--898",
editor = "Cheng-Yi Chen and Cheng-Fu Yang and Jengnan Juang",
booktitle = "Proceedings of the 2nd International Conference on Intelligent Technologies and Engineering Systems, ICITES 2013",
address = "Germany",
}