Author:
Fatima Ghania,Farooq Omar,Singh Shikha
Reference17 articles.
1. Huang, C. S., Lin, C. L., Ko, L. W., Liu, S. Y., Sua, T. P., & Lin, C. T. (2013). A hierarchical classification system for sleep stage scoring via forehead EEG signals. In Proceeding of 2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind and Brain, CCMB 2013—2013 IEEE Symposium Series on Computer Intelligence SSCI (pp. 1–5).
2. Anderer, P., Gruber, G., Parapatics, S., & Dorffner, G. (2007). Automatic sleep classification according to Rechtschaffen and Kales. In Proceedings of Annual International Conference IEEE Engineering in Medicine and Biology (pp. 3994–3997).
3. Smith, J. R., Funke, W. F., Yeo, W. C., & Ambuehl, R. A. (1975). Detection of human sleep EEG waveforms. Electroencephalography and Clinical Neurophysiology, 38, 435–437.
4. Fish, D. R., Allen, P. J., & Blackie, J. D. (1988). A new method for the quantitative analysis of sleep spindles during continuous overnight EEG recordings. Journal of Sleep Research, 70, 273–277.
5. Huupponen, E., Värri, A., Himanen, S. L., Hasan, J., Lehtokangas, M., & Saarinen, J. (2000). Optimization of sigma amplitude threshold in sleep spindle detection. Journal of Sleep Research, 9(4), 327–334.