caa a22 4500 465783279 CHVBK 20180323112001.0 cr unu---uuuuu 170327e19901101xx s 000 0 eng 10.1007/BF02442603 doi (NATIONALLICENCE)springer-10.1007/BF02442603 Adaptive spectral analysis of cutaneous electrogastric signals using autoregressive moving average modelling [Elektronische Daten] [J. Chen, J. Vandewalle, W. Sansen, G. Vantrappen, J. Janssens] The recording of the human, gastric myoelectrical activity, by means of cutaneous electrodes is called electrogastrography (EGG). It provides a noninvasive method of studying electrogastric behaviour. The normal frequency of the gastric signal is about 0·05 Hz. However, sudden changes of its frequency have been observed and are generally considered to be related to gastric motility disorders. Thus, spectral analysis, especially online spectral analysis, can serve as a valuable tool for practical purposes. The paper presents a new method of the adaptive spectral analysis of cutaneous electrogastric signals using autoregressive moving average (ARMA) modelling. It is based on an adaptive ARMA filter and provides both time and frequency information of the signal. Its performance is investigated in comparison with the conventional FFT-based periodogram method. Its properties in tracking time-varying instantaneous frequencies are shown. Its applications to the running spectral analysis of cutaneous electrogastric signals are presented. The proposed adaptive ARMA spectral analysis method is easy to implement and is efficient in computations. The results presented in the paper show that this new method provides a better performance and is very useful for the online monitoring of cutaneous electrogastric signals. IFMBE, 1990 Autoregressive moving average modelling nationallicence Electrogastrography nationallicence Gastric motility nationallicence Gastric slow wave nationallicence Spectral analysis nationallicence Chen J. ESAT Laboratory, Department of Electrical Engineering, Katholieke Universititeit Leuven, Kard, Mercierlaan, 94, 3030, Leuven, Belgium aut Vandewalle J. ESAT Laboratory, Department of Electrical Engineering, Katholieke Universititeit Leuven, Kard, Mercierlaan, 94, 3030, Leuven, Belgium aut Sansen W. ESAT Laboratory, Department of Electrical Engineering, Katholieke Universititeit Leuven, Kard, Mercierlaan, 94, 3030, Leuven, Belgium aut Vantrappen G. Motility Laboratory, Department of Medical Research, UZ Gasthuisberg, 3000, Leuven, Belgium aut Janssens J. Motility Laboratory, Department of Medical Research, UZ Gasthuisberg, 3000, Leuven, Belgium aut Medical and Biological Engineering and Computing Kluwer Academic Publishers 28/6(1990-11-01), 531-536 0140-0118 28:6<531 1990 28 11517 https://doi.org/10.1007/BF02442603 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF02442603 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Chen J. ESAT Laboratory, Department of Electrical Engineering, Katholieke Universititeit Leuven, Kard, Mercierlaan, 94, 3030, Leuven, Belgium aut NATIONALLICENCE 700 1- Vandewalle J. ESAT Laboratory, Department of Electrical Engineering, Katholieke Universititeit Leuven, Kard, Mercierlaan, 94, 3030, Leuven, Belgium aut NATIONALLICENCE 700 1- Sansen W. ESAT Laboratory, Department of Electrical Engineering, Katholieke Universititeit Leuven, Kard, Mercierlaan, 94, 3030, Leuven, Belgium aut NATIONALLICENCE 700 1- Vantrappen G. Motility Laboratory, Department of Medical Research, UZ Gasthuisberg, 3000, Leuven, Belgium aut NATIONALLICENCE 700 1- Janssens J. Motility Laboratory, Department of Medical Research, UZ Gasthuisberg, 3000, Leuven, Belgium aut NATIONALLICENCE 773 0- Medical and Biological Engineering and Computing Kluwer Academic Publishers 28/6(1990-11-01), 531-536 0140-0118 28:6<531 1990 28 11517 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer