EXTRACTION OF GASTRIC MYOELECTRIC ACTIVITY FROM FINGER PHOTOPLETHYSMOGRAPHIC SIGNAL

This paper is an experimental study to examine the possibility of extracting gastric myoelectric activity (GMA) from photoplethysmographic (PPG) signals. Diagnosing GMA is a clinically challenging task because of its invasive/cumbersome methods. It is known that the PPG consists of information related to heart rate, respiratory rate and phenomena. Here we take this thread further and see whether GMA can be extracted from PPG in a simpler way and without discomfort to the patients. Since PPG and GMA signals are nonstationary, we choose discrete wavelet transform (DWT) to separate the different frequency components. PPG and Electrogastrog-ram (EGG, a method of measuring GMA) signals were acquired simultaneously at the rate of 100 Hz from 8 healthy subjects for 30 minutes duration in fasting and postprandial states. Both the signals were decomposed using DWT up to the frequency range (0 - 0.1) Hz. A lower frequency oscillation (≈ 0.05 Hz) called slow wave was extracted from PPG signal which looks similar to the slow wave of GMA in both shape and frequency. Normalized cross-correlation technique was used for comparing the two signals. Cross-correlation values were found to be high (R ≥ 0.73, R = 1.0 indicates exact agreement) for all subjects without any significant change between fasting and postprandial states. The results suggest that there is a possibility of extracting gastric related information from PPG signals using appropriate signal processing techniques. In future this novel technique could be used as a diagnostic tool for gastrointestinal system disorders.