Abstract:Deep learning classifiers have demonstrated their ability to provide robust accuracy for the treatment of com- bined signals including electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) [1], [2]. In this work, an evolutionary deep learning strategy is applied to classify different cognitive workload states that surgeons experience during laparoscopic surgery. The proposed learning strategy is applied to train an Evolutionary Multilayer Perceptron Neural Network (E- MLPNN), … Show more
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