A CNN-RNN hybrid beat LSTM, GRU, CNN, and TCN models at segmenting EEG into blink and non-blink time points, with best scores of 95.8% in healthy subjects and 75.8% in Parkinson's patients.
Automatic spike detection based on adap- tive template matching for extracellular neural recordings,
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Detecting Blinks in Healthy and Parkinson's EEG: A Deep Learning Perspective
A CNN-RNN hybrid beat LSTM, GRU, CNN, and TCN models at segmenting EEG into blink and non-blink time points, with best scores of 95.8% in healthy subjects and 75.8% in Parkinson's patients.