Improvement of Sleep Spindle Detection by Aggregation Techniques
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-31635-8_27
Reference18 articles.
1. Ahmed, B., Redissi, A., Tafreshi, R.: An automatic sleep spindle detector based on wavelets and the teager energy operator. In: 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2596–2599, September 2009
2. Born, J., Rasch, B., Gais, S.: Sleep to remember. Neuroscientist 12(5), 410–424 (2006). https://doi.org/10.1177/1073858406292647 . pMID: 16957003
3. Devuyst, S., Dutoit, T., Stenuit, P., Kerkhofs, M.: Automatic sleep spindles detection – overview and development of a standard proposal assessment method. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1713–1716, August 2011
4. Duman, F., Erdamar, A., Erogul, O., Telatar, Z., Yetkin, S.: Efficient sleep spindle detection algorithm with decision tree. Expert Syst. Appl. 36(6), 9980–9985 (2009). http://www.sciencedirect.com/science/article/pii/S0957417409001055
5. Gais, S., Mölle, M., Helms, K., Born, J.: Learning-dependent increases in sleep spindle density. J. Neurosci. 22(15), 6830–6834 (2002). http://www.jneurosci.org/content/22/15/6830
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