APPLICATION OF SELF ORGANIZING MAP FOR CORRELATION HUNTING BETWEEN ALPHA BAND POWER OF EEG SIGNALS AND OTHER PHYSIOLOGICAL PARAMETERS DURING MUSLIM PRAYER (SALAT)

Abstract

This study investigates a new approach to determine the correlations between alpha ([Formula: see text]) electroencephalography (EEG) and other physiological parameters during Muslim prayer (Salat) utilizing the self organizing map (SOM). The powerfulness of SOM in visualizing, understanding, and exploring the complexity in multivariable data can be used to determine the relationships between the input variables. Thirty healthy Muslim male subjects were recruited in the study. Their electroencephalogram (EEG), electrocardiogram (ECG), respiration rate (RSP), and oxygen saturation (SPO2) were continuously recorded using computer-based data acquisition system (MP150, BIOPAC Systems Inc., Camino Goleta, California). Three maps were constructed to determine the correlations in pre-baseline, during Salat, and post-baseline conditions utilizing SOM. The visualized results during Salat indicated that, alpha power (P[Formula: see text]) showed significant positive correlation in the occipital and parietal electrodes with the normalized unit of high-frequency HF (n.u.) power of heart rate variability (HRV) components (as a parasympathetic index), heart rate (HR), and RSP. Significant negative correlation was also observed between P[Formula: see text] with the normalized unit of low-frequency LF (n.u.) power and LF/HF of HRV (as sympathetic indices). SPO2 showed no correlation with P[Formula: see text]. While the results in pre-baseline and post-baseline conditions also did not show any correlation between the variables. The SOM proves that it can be successfully employed as a powerful technique in correlation analysis. The results were presented and compared with a previous study. Thus, it can be applied successfully in various biomedical engineering applications.