Turkish Journal of Medical Sciences




To investigate whether electroencephalographic (EEG) frequency bands are applicable in distinguishing abnormal respiratory events such as obstructive apnea and hypopnea in patients with sleep apnea. Materials and methods: The polysomnographic recordings of 20 patients were examined retrospectively. EEG record segments were taken from C4-A1 and C3-A2 channels and were analyzed with software that uses digital signal processing methods, developed by the study team. Percentage values of delta, theta, alpha, and beta frequency bands were evaluated through discriminant and receiver-operator curve (ROC) analysis to distinguish between apneas and hypopneas. Results: For the C4-A1 channel, delta (%) provided the highest discriminative value (AUC = 0.563; P < 0.001); on the other hand, alpha (%) gave the lowest discriminative value (AUC = 0.519; P = 0.041). Likewise, whereas for the C3-A2 channel delta (%) gave the highest discriminative value (AUC = 0.565; P < 0.001), alpha produced the lowest discriminative value (AUC = 0.501; P = 0.943). Conclusion: As a result of discriminant analysis, the accurate classification rate of hypopneas was 44.8% and the accurate classification of obstructive apneas was 63.5%. Of the 4 frequency bands, the most significant was delta. The predictive values were not at significance level.


Sleep apnea, digital signal processing, electroencephalography, receiver-operator curve characteristics

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