Effect of electrode contact area on the information content of the recorded electrogastrograms: An analysis based on Rényi entropy and Teager-Kaiser Energy

[1] Swobodnik W, Soloway RS, Ditschuneit H (Eds). Gallstone disease: pathophysiology and therapeutic approaches. Springer Science & Business Media, 2012.Search in Google Scholar

[2] Siegel MA, Jacobson JJ, Braun RJ. Diseases of the Gastrointestinal Tract, Chapter 14. In: Burket's Oral Medicine: Diagnosis & Treatment. Greenberg MS, Glick M (Eds). BC Decker, Inc. 2003;389-406.Search in Google Scholar

[3] Neuman MR. The Electrical Engineering Handbook. Richard C. Dorf (Ed). CRC Press LLC, 2000.Search in Google Scholar

[4] Yin J, Chen JD. Electrogastrography: methodology, validation and applications. Journal of Neurogastroenterology and Motility. 2013;19(1):5-17.10.5056/jnm.2013.19.1.5Search in Google Scholar

[5] Gopu G, Neelaveni R, Porkumaran K. Investigation of digestive system disorders using Electrogastrogram. Computer and Communication Engineering, 2008. ICCCE 2008. 201-205.10.1109/ICCCE.2008.4580596Search in Google Scholar

[6] Borowska M. Entropy-based algorithms in the analysis of biomedical signals. Studies in Logic, Grammar and Rhetoric. 2015;43(1):21-32.10.1515/slgr-2015-0039Search in Google Scholar

[7] Rosso OA. Entropy changes in brain function. International Journal of Psychophysiology. 2007;64(1):75-80.10.1016/j.ijpsycho.2006.07.010Search in Google Scholar

[8] Ahmad SA, Chappell PH. Moving approximate entropy applied to surface electromyographic signals. Biomedical Signal Processing and Control. 2008 Jan 31;3(1):88-93.10.1016/j.bspc.2007.10.003Search in Google Scholar

[9] Hassan M, Terrien J, Marque C, et al. Comparison between approximate entropy, correntropy and time reversibility: Application to uterine electromyogram signals. Medical Eng Phys. 2011;33(8):980-986.10.1016/j.medengphy.2011.03.010Search in Google Scholar

[10] Sun R, Song R, Tong KY. Complexity analysis of EMG signals for patients after stroke during robot-aided rehabilitation training using fuzzy approximate entropy. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2014;22(5):1013-1019.10.1109/TNSRE.2013.2290017Search in Google Scholar

[11] Bromiley PA, Thacker NA, Bouhova-Thacker E. Shannon entropy, Rényi entropy, and information. Statistics and Inf. Series (2004-004). 2004.Search in Google Scholar

[12] Castner DG, Ratner BD. Biomedical surface science: Foundations to frontiers. Surface Science. 2002;500(1-3):28-60.10.1016/S0039-6028(01)01587-4Search in Google Scholar

[13] Kvedalen E. Signal processing using the Teager energy operator and other nonlinear operators. Thesis. University of Oslo Department of Informatics. 2003.Search in Google Scholar

[14] Kasicka-Jonderko A, Jonderko K, Krusiec-Swidergol B, et al. Comparison of multichannel electrogastrograms obtained with the use of three different electrode types. J Smooth Muscle Res. 2006;42(2-3):89-101.10.1540/jsmr.42.8917001115Search in Google Scholar

[15] Taji B, Shirmohammadi S, Groza V, etc. Impact of skin-electrode interface on electrocardiogram measurements using conductive textile electrodes. IEEE Transactions on Instrumentation and Measurement. 2014;63(6):1412-1422.10.1109/TIM.2013.2289072Search in Google Scholar

[16] Mintchev M, Stickel A, Bowes K. Impact of different electrode surface areas on validity of human electrogastrograms. Medical and Biological Engineering and Computing. 1997;35(1):66-68.10.1007/BF02510395Search in Google Scholar

[17] Mintchev MP, Bowes KL. Computer simulation of the effect of changing abdominal thickness on the electrogastrogram. Med Eng Phys. 1998;20(3):177-181.10.1016/S1350-4533(98)00019-8Search in Google Scholar

[18] Kim JH, Pullan AJ, Bradshaw LA, et al. Influence of body parameters on gastric bioelectric and biomagnetic fields in a realistic volume conductor. Physiol Meas. 2012;33(4):545-556.10.1088/0967-3334/33/4/545335996322415019Search in Google Scholar

[19] Riezzo G, Russo F, Indrio F. Electrogastrography in adults and children: the strength, pitfalls, and clinical significance of the cutaneous recording of the gastric electrical activity. Biomed Res Int. 2013;2013:282757.10.1155/2013/282757367765823762836Search in Google Scholar

[20] Parkman HP, Hasler WL, Barnett JL, et al. Electrogastrography: a document prepared by the gastric section of the American Motility Society Clinical GI Motility Testing Task Force. Neurogastroenterol Motil. 2003;15(2):89-102.10.1046/j.1365-2982.2003.00396.x12680908Search in Google Scholar

[21] Schrödinger E. What is life?: With mind and matter and autobiographical sketches. Cambridge University Press; 1992.10.1017/CBO9781139644129Search in Google Scholar

[22] Alagumariappan P, Rajagopal A, Krishnamurthy K. Complexity Analysis on Normal and Abnormal Electrogastrograms Using Tsallis Entropy. In: 3rd International Electronic and Flipped Conference on Entropy and Its Applications 2016. Multidisciplinary Digital Publishing Institute.10.3390/ecea-3-A003Search in Google Scholar

[23] Principe JC. Information theoretic learning: Rényi's entropy and kernel perspectives. Springer Science & Business Media; 2010.10.1007/978-1-4419-1570-2Search in Google Scholar

[24] Kaiser JF. On a simple algorithm to calculate the 'energy' of a signal. International Conference on Acoustics, Speech, and Signal Processing. Albuquerque, NM. 1990;(vol1):381-38.Search in Google Scholar

[25] Solnik S, DeVita P, Rider P, et al. Teager-Kaiser Operator improves the accuracy of EMG onset detection independent of signal-tonoise ratio. Acta Bioeng Biomech. 2008;10(2):65-68.Search in Google Scholar

[26] Lauer RT, Prosser LA. Use of the Teager-Kaiser energy operator for muscle activity detection in children. Ann Biomed Eng. 2009;37(8):1584-1593.10.1007/s10439-009-9727-9276313619484385Search in Google Scholar