A hybrid EEG and head motion system for smart home control for disabled people
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-022-04469-6.pdf
Reference41 articles.
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2. Agarwal M, Sivakumar R (2019) Blink: a fully automated unsupervised algorithm for eye-blink detection in EEG signals. In: 2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019. Institute of Electrical and Electronics Engineers Inc., pp 1113–1121. https://doi.org/10.1109/ALLERTON.2019.8919795
3. Almajidy RK, Le KS, Hofmann UG (2016) Novel near infrared sensors for hybrid BCI applications. In: Advanced Microscopy Techniques IV; and Neurophotonics II (2015), paper 95361H. The Optical Society, p 95361H. https://doi.org/10.1364/ecbo.2015.95361h
4. al-Qerem A, Kharbat F, Nashwan S et al (2020) General model for best feature extraction of EEG using discrete wavelet transform wavelet family and differential evolution. Int J Distrib Sens Netw 16:1550147720911009. https://doi.org/10.1177/1550147720911009
5. Alshebly YS, Nafea M (2019) Isolation of fetal ECG signals from abdominal ECG using wavelet analysis. IRBM. https://doi.org/10.1016/j.irbm.2019.12.002
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