Microcontroller - Based System for Electrogastrography Monitoring Through Wireless Transmission

Haddab, S.; Laghrouche, M.

doi:10.2478/v10048-009-0022-6

Abstract

Electrogastrography (EGG) is a non-invasive method for recording the electrical activity of the stomach. This paper presents a system designed for monitoring the EGG physiological variables of a patient outside the hospital environment. The signal acquisition is achieved by means of an ambulatory system carried by the patient and connected to him through skin electrodes. The acquired signal is transmitted via the Bluetooth to a mobile phone where the data are stored into the memory and then transferred via the GSM network to the processing and diagnostic unit in the hospital. EGG is usually contaminated by artefacts and other signals, which are sometimes difficult to remove. We have used a neural network method for motion artefacts removal and biological signal separation.

References

Tura, A., Badanai, M., Longo, O., Quareni, L. (2003). A medical wearable device with wireless Bluetooth based data transmission. Measurement Science Review, 3, 1-4.
Search in Google Scholar
Rasid, M.F.A., Woodward, B. (2005). Bluetooth telemedicine processor for multichannel biomedical signal transmission via mobile cellular networks. IEEE Transactions on Information Technology in Biomedicine, 9 (1), 35-43.10.1109/TITB.2004.840070
Search in Google Scholar
Chien, J.-R.C., Tai, C.C. (2004). A wireless Bluetooth device applied to a non-contact type breathing monitoring system. In IEEE International Conference on Networking, Sensing and Control, March 21-23, 2004, Vol. 1, 172-173.10.1109/ICNSC.2004.1297429
Search in Google Scholar
Chien, J.-R.C., Tai, C.C. (2006). Handheld electrocardiogram measurement instrument using a new peak quantification method algorithm built on a system-on-chip embedded system. Review of Scientific Instruments, 77 (9), 095106.10.1063/1.2349295
Search in Google Scholar
Woodward, B., Istepanian, R.S.H., Richards, C.I. (2001). Design of a telemedicine system using a mobile telephone. IEEE Transactions on Information Technology in Biomedicine, 5 (1), 13-15.10.1109/4233.908361
Search in Google Scholar
Rubel, P., Fayn, J., Nollo, G., Assanelli, D., Li, B., Restier, L., et al. (2005). Toward personal health in cardiology. Results from the EPI-MEDICS telemedicine project. Journal of Electrocardiology, 38 (4), 100-106.
Search in Google Scholar
Haddab, S., Bouchoucha, M., Cugnenc, P.-H., Barbier, J.-P. (1990). New method for electro gastrographic analysis. In Proceedings of Third Annual IEEE Symposium on Computer-Based Medical Systems, June 3-6, 1990, 418-425.10.1109/CBMSYS.1990.109426
Search in Google Scholar
Alvarez, W.C. (1922). The electrogastrogram and what it shows. Journal of the American Medical Association, 78, 1116-19.
Search in Google Scholar
Lin, Z., Eaker, E.Y., Sarosiek, I., McCallum, R.W. (1999). Gastric myoelectrical activity and gastric emptying in patients with functional dyspepsia. American Journal of Gastroenterology, 94, 2384-2389.10.1111/j.1572-0241.1999.01362.x
Search in Google Scholar
Verhagen, M.A.M.T., van Schelven, L.J., Samsom, M., Smout, A.J.P.M. (1999). Pitfalls in the analysis of electrogastrographic recordings. Gastroenterology, 117, 453-460.10.1053/gast.1999.0029900453
Search in Google Scholar
Huizinga, J.D., Robinson, T.L., Thomsen, L. (2000). The search for the origin of rhythmicity in intestinal contraction; from tissue to single cells. Neurogastroenterology and Motility, 12 (1), 3-9.10.1046/j.1365-2982.2000.00177.x
Search in Google Scholar
Hubka, P., Rosí, V., Ždiňák, J., Tyšler, M., Hulín, I. (2005). Independent component analysis of electrogastrographic signals. Measurement Science Review, 5, 21-24.
Search in Google Scholar
Simonian, H.P., Panganamamula, K., Chen, J.Z., Fisher, R.S., Parkman, H.P. (2003). Multichannel electro - gastrography (EGG) in symptomatic patients: A single center study. Neurogastroenterology and Motility, 15, 338.
Search in Google Scholar
Liang, J., Cheung, J., Chen, Z. (1997). Detection and deletion of motion artefacts in electrogastrogram using feature analysis and neural networks. Annals of Biomedical Engineering, 25, 850-857.10.1007/BF02684169
Search in Google Scholar
Chen, J., Lin, Z., Wu, Q., McCallum, R.W. (1995). Non-invasive identification of gastric contractions from surface electrogastrogram using back-propagation neural networks. Medica Engineering and Physics, 17, 219-225.10.1016/1350-4533(95)95713-K
Search in Google Scholar

Microcontroller - Based System for Electrogastrography Monitoring Through Wireless Transmission

Abstract

Paradigm

My account