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We present a novel method for automatic and robust detection of dominantfrequency (DF) in the electrogastrogram (EGG). Our new approach combines FastFourier Transform (FFT), Welch's method for spectral density estimation, andautocorrelation. The proposed combined method as well as other separateprocedures were tested on a freely available dataset consisted of EGGrecordings in 20 healthy individuals. DF was calculated in relation (1) to thefasting and postprandial states, (2) to the three recording locations, and (3)to the subjects' body mass index. For the estimation of algorithms performancein the presence of noise, we created a synthetic dataset by adding whiteGaussian noise to the artifact-free EGG waveform in one subject. The individualalgorithms and novel combined approach were evaluated in relation to thesignal-to-noise ratio (SNR) in range from -40 dB to 20 dB. Our results showedthat the novel combined method significantly outperformed the commonly usedapproach for DF calculation - FFT in noise presence when compared to thebenchmark data being was manually corrected by an expert. The novel methodoutperformed autocorrelation and Welch's method in accuracy. Additionally, wepresented a method for optimal window width selection when using Welch'sspectrogram that showed that for DF detection, window length of N/4 (300 s),where N is the length of EGG waveform in samples, performed the best whencompared to the benchmark data. The combined approach proved efficient forautomatic and robust calculation of dominant frequency on openly available EGGdataset recorded in healthy individuals and is promising approach for DFdetection.

Combined approach for automatic and robust calculation of dominant frequency of electrogastrogram