Abstract
Emotion assessment in stroke patients gives meaningful information to physiotherapists to identify the appropriate method for treatment. This study was aimed to classify the emotions of stroke patients by applying bispectrum features in electroencephalogram (EEG) signals. EEG signals from three groups of subjects, namely stroke patients with left brain damage (LBD), right brain damage (RBD), and normal control (NC), were analyzed for six different emotional states. The estimated bispectrum mapped in the contour plots show the different appearance of nonlinearity in the EEG signals for different emotional states. Bispectrum features were extracted from the alpha (8–13) Hz, beta (13–30) Hz and gamma (30–49) Hz bands, respectively. The k-nearest neighbor (KNN) and probabilistic neural network (PNN) classifiers were used to classify the six emotions in LBD, RBD and NC. The bispectrum features showed statistical significance for all three groups. The beta frequency band was the best performing EEG frequency-sub band for emotion classification. The combination of alpha to gamma bands provides the highest classification accuracy in both KNN and PNN classifiers. Sadness emotion records the highest classification, which was 65.37% in LBD, 71.48% in RBD and 75.56% in NC groups.
Highlights
Stroke is one of the highest causes of death in Malaysia, with more than 40,000 survivors are managing their health today [1]
Bispectrum features were extracted from the EEG signals in three groups of subjects (LBD, right brain damage (RBD), and normal control (NC)) for the analysis of six emotions, namely anger (A), disgust (D), fear (F), happiness (H), sadness (S), and surprise (SU)
The importance of emotion assessment of stroke patients stems from the need to seek information on the severity of emotional impairment symptoms
Summary
Stroke is one of the highest causes of death in Malaysia, with more than 40,000 survivors are managing their health today [1]. Stroke is caused by the insufficient supply of oxygen to the brain, damaging damage brain cells. Past studies have been carried out to investigate emotional changes in stroke patients as the influence of their physiological phenomenon [3,4,5]. These studies revealed that emotions and thoughts are seen as interactive reactions and are intimately related to the health and physiological problems
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