Akademik Veri Yönetim Sistemi
Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi, cilt.16, sa.3, ss.599-610, 2025 (TRDizin)
Dysphagia often makes eating and drinking painful, stressful, and socially isolating, potentially leading to malnutrition, dehydration, weight loss, and respiratory infections. In this study, the relationship between swallowing and brain signals was examined to contribute to the electrophysiological understanding of the imagination of swallowing and rehabilitation of dysphagia patients. To examine the swallowing event, three different experiments were conducted. The experiments included (i) natural water swallowing, (ii) swallowing saliva in an induced manner, and (iii) swallowing a sip of water in an induced manner. Visual cues on a computer monitor were used to induce the perception of swallowing and imagination. EEG data from 16 channels obtained during 15 trials of these experimental paradigms from 30 subjects (15 men) were subjected to different processes such as noise removal, selection of signal segments corresponding to the imagination of swallowing, extraction of frequency domain features, and statistical analysis. Eleven features such as spectral centroid, mean and median frequency, delta, theta, alpha and beta band powers, and relative band powers obtained from 16 channels (a total of 176 features) were first subjected to the Shapiro-Wilks normality test individually. As a result of this test, the statistical analyses were carried out with the help of repeated measures one-way ANOVA test for the features with normal distribution (spectral centroid from 11 channels), and the Friedman test for the features with non-normal distribution (spectral centroid from the remaining 5 channels and all other features from 16 channels). As a result of these tests, it is seen that 76.7% of all features yield statistically significant differences between 3 different swallowing approaches. We suggest that identifying discriminative EEG-based features could significantly contribute to the development of novel brain-machine interface applications for dysphagia rehabilitation.