A Comparative Study Between C4-A1 and EMG1-EMG2 Channels for RBD Sleep Disorder Detection by Analysing Normalized Beta Wave Power of EEG Signals

Background/Objectives: Rapid Eye Movement (REM) Sleep Behavior Disorder (RBD) is characterized by dream enactment due to reduced physiological muscle atonia during REM sleep and is clinically relevant as a potential prodromal marker for neurodegenerative disorders. This study aims to evaluate whether normalized beta-band power extracted from poly-somnographic signals can differentiate RBD subjects from healthy controls, and to compare the discriminative behavior of C4–A1 EEG versus EMG1–EMG2 channels during REM sleep. Methods: Polysomnographic recordings were obtained from the PhysioNet CAP Sleep Data-base. One-minute epochs were analyzed across sleep stages, with emphasis on REM. Signals were preprocessed to remove DC offset and were windowed with overlap prior to spectral estimation. Short time–frequency analysis of power spectral density (PSD) was applied to compute band-limited power in standard EEG frequency ranges (delta, theta, alpha, beta). Band power values were normalized by total spectral power to derive nor-malized indices. Comparative feature analysis was performed for C4–A1 and EMG1–EMG2 channels. Results: Normalized beta-band power during REM sleep showed clear separation between healthy subjects and RBD patients. In the C4–A1 channel, normalized beta power was higher in RBD than controls (controls: 0.0010–0.0049; RBD: 0.0076–0.014). In the EMG1–EMG2 channel, the difference was more pronounced (controls: 0.0020–0.0089; RBD: 0.053–0.0791). Conclusions: Normalized beta-band power, particularly during REM sleep, is a promising, low-complexity marker for RBD detection. The stronger separation in EMG1–EMG2 sug-gests that targeted channel selection may enhance practical screening pipelines for sleep disorder assessment.