Enhancement of the non-invasive electroenterogram to identify intestinal pacemaker activity

Surface recording of electroenterogram (EEnG) is a non-invasive method for monitoring intestinal myoelectrical activity. However, surface EEnG is seriously affected by a variety of interferences: cardiac activity, respiration, very low frequency components and movement artefacts. The aim of this study is to eliminate respiratory interference and very low frequency components from external EEnG recording by means of empirical mode decomposition (EMD), so as to obtain more robust indicators of intestinal pacemaker activity from external EEnG signal. For this purpose, 11 recording sessions were performed in an animal model under fasting conditions and in each individual session the myoelectrical signal was recorded simultaneously in the intestinal serosa and the external abdominal surface in physiological states. Various parameters have been proposed for evaluating the efficacy of the method in reducing interferences: the signal-to-interference ratio (S/I ratio), attenuation of the target and interference signals, the normal slow wave percentage and the stability of the dominant frequency (DF) of the signal. The results show that the S/I ratio of the processed signals is significantly greater than the original values (9.66±4.44 dB vs. 1.23±5.13 dB), while the target signal was barely attenuated (-0.63±1.02 dB). The application of the EMD method also increased the percentage of the normal slow wave to 100% in each individual session and enabled the stability of the DF of the external signal to be increased considerably. Furthermore, the variation coefficient of the DF derived from the external processed signals is comparable to the coefficient obtained using internal recordings. Therefore the EMD method could be a very useful tool to improve the quality of external EEnG recording in the low frequency range, and therefore to obtain more robust indicators of the intestinal pacemaker activity from non invasive EEnG recordingsThe authors would like to thank D Alvarez-Martinez, Dr C Vila and the Veterinary Unit of the Research Centre of 'La Fe' University Hospital (Valencia, Spain), where the surgical interventions and recording sessions were carried out, and the R+D+I Linguistic Assistance Office at the UPV for their help in revising this paper. This research study was sponsored by the Ministerio de Ciencia y Tecnologia de Espana (TEC2007-64278) and by the Universidad Politecnica de Valencia, as part of a UPV research and development Grant Programme.Ye Lin, Y.; Garcia Casado, FJ.; Prats Boluda, G.; Ponce, JL.; Martínez De Juan, JL. (2009). Enhancement of the non-invasive electroenterogram to identify intestinal pacemaker activity. PHYSIOLOGICAL MEASUREMENT. 30(9):885-902. https://doi.org/10.1088/0967-3334/30/9/002S885902309Amaris, M. A., Sanmiguel, C. P., Sadowski, D. C., Bowes, K. L., & Mintchev, M. P. (2002). Digestive Diseases and Sciences, 47(11), 2480-2485. doi:10.1023/a:1020503908304Bass, P., & Wiley, J. N. (1965). Electrical and extraluminal contractile-force activity of the duodenum of the dog. The American Journal of Digestive Diseases, 10(3), 183-200. doi:10.1007/bf02233747Bradshaw, L. A., Allos, S. H., Wikswo, J. P., & Richards, W. O. (1997). Correlation and comparison of magnetic and electric detection of small intestinal electrical activity. American Journal of Physiology-Gastrointestinal and Liver Physiology, 272(5), G1159-G1167. doi:10.1152/ajpgi.1997.272.5.g1159Camilleri, M., Hasler, W. L., Parkman, H. P., Quigley, E. M. M., & Soffer, E. (1998). Measurement of gastrointestinal motility in the GI laboratory. Gastroenterology, 115(3), 747-762. doi:10.1016/s0016-5085(98)70155-6Chen, J. D. Z., & Lin, Z. (1993). Adaptive cancellation of the respiratory artifact in surface recording of small intestinal electrical activity. Computers in Biology and Medicine, 23(6), 497-509. doi:10.1016/0010-4825(93)90097-kChen, J., & McCallum, R. W. (1991). Electrogastrography: measuremnt, analysis and prospective applications. Medical & Biological Engineering & Computing, 29(4), 339-350. doi:10.1007/bf02441653Chen, J. D. Z., Schirmer, B. D., & McCallum, R. W. (1993). Measurement of electrical activity of the human small intestine using surface electrodes. IEEE Transactions on Biomedical Engineering, 40(6), 598-602. doi:10.1109/10.237682Garcia-Casado, J., Martinez-de-Juan, J. L., & Ponce, J. L. (2005). Noninvasive Measurement and Analysis of Intestinal Myoelectrical Activity Using Surface Electrodes. IEEE Transactions on Biomedical Engineering, 52(6), 983-991. doi:10.1109/tbme.2005.846730Gordon, A. D. (1987). A Review of Hierarchical Classification. Journal of the Royal Statistical Society. Series A (General), 150(2), 119. doi:10.2307/2981629Huang, N. E., Shen, Z., Long, S. R., Wu, M. C., Shih, H. H., Zheng, Q., … Liu, H. H. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 454(1971), 903-995. doi:10.1098/rspa.1998.0193Irimia, A., & Bradshaw, L. A. (2005). Artifact reduction in magnetogastrography using fast independent component analysis. Physiological Measurement, 26(6), 1059-1073. doi:10.1088/0967-3334/26/6/015Lammers, W. J. E. P., & Stephen, B. (2008). Origin and propagation of individual slow waves along the intact feline small intestine. Experimental Physiology, 93(3), 334-346. doi:10.1113/expphysiol.2007.039180Liang, H. (2001). Adaptive independent component analysis of multichannel electrogastrograms. Medical Engineering & Physics, 23(2), 91-97. doi:10.1016/s1350-4533(01)00019-4Liang, J., Cheung, J. Y., & Chen, J. D. Z. (1997). Detection and deletion of motion artifacts in electrogastrogram using feature analysis and neural networks. Annals of Biomedical Engineering, 25(5), 850-857. doi:10.1007/bf02684169Liang, H., Lin, Z., & McCallum, R. W. (2000). Artifact reduction in electrogastrogram based on empirical mode decomposition method. Medical & Biological Engineering & Computing, 38(1), 35-41. doi:10.1007/bf02344686Zhi-Yue Lin, Chen, Z., & Jian De. (1994). Time-frequency representation of the electrogastrogram-application of the exponential distribution. IEEE Transactions on Biomedical Engineering, 41(3), 267-275. doi:10.1109/10.284945Lin, Z. Y., & Chen, J. D. Z. (1994). Recursive running DCT algorithm and its application in adaptive filtering of surface electrical recording of small intestine. Medical & Biological Engineering & Computing, 32(3), 317-322. doi:10.1007/bf02512529Lin, Z., & Chen, J. D. Z. (1995). Comparison of three running spectral analysis methods for electrogastrographic signals. Medical & Biological Engineering & Computing, 33(4), 596-604. doi:10.1007/bf02522520Maestri, R., Pinna, G. D., Porta, A., Balocchi, R., Sassi, R., Signorini, M. G., … Raczak, G. (2007). Assessing nonlinear properties of heart rate variability from short-term recordings: are these measurements reliable? Physiological Measurement, 28(9), 1067-1077. doi:10.1088/0967-3334/28/9/008Martinez-de-Juan, J. ., Saiz, J., Meseguer, M., & Ponce, J. . (2000). Small bowel motility: relationship between smooth muscle contraction and electroenterogram signal. Medical Engineering & Physics, 22(3), 189-199. doi:10.1016/s1350-4533(00)00032-1Mintchev, M. P., Kingma, Y. J., & Bowes, K. L. (1993). Accuracy of cutaneous recordings of gastric electrical activity. Gastroenterology, 104(5), 1273-1280. doi:10.1016/0016-5085(93)90334-9Prats-Boluda, G., Garcia-Casado, J., Martinez-de-Juan, J. L., & Ponce, J. L. (2007). Identification of the slow wave component of the electroenterogram from Laplacian abdominal surface recordings in humans. Physiological Measurement, 28(9), 1115-1133. doi:10.1088/0967-3334/28/9/012Quigley, E. M. M. (1996). GASTRIC AND SMALL INTESTINAL MOTILITY IN HEALTH AND DISEASE. Gastroenterology Clinics of North America, 25(1), 113-145. doi:10.1016/s0889-8553(05)70368-xSeidel, S. A., Bradshaw, L. A., Ladipo, J. K., Wikswo, J. P., & Richards, W. O. (1999). Noninvasive detection of ischemic bowel. Journal of Vascular Surgery, 30(2), 309-319. doi:10.1016/s0741-5214(99)70142-4Tomomasa, T., Morikawa, A., Sandler, R. H., Mansy, H. A., Koneko, H., Masahiko, T., … Itoh, Z. (1999). Gastrointestinal Sounds and Migrating Motor Complex in Fasted Humans. American Journal of Gastroenterology, 94(2), 374-381. doi:10.1111/j.1572-0241.1999.00862.xWang, Z. S., Cheung, J. Y., & Chen, J. D. Z. (1999). Blind separation of multichannel electrogastrograms using independent component analysis based on a neural network. Medical & Biological Engineering & Computing, 37(1), 80-86. doi:10.1007/bf0251327

Capacitance evaluation on parallel-plate capacitors by means of finite element analysis

[EN] The electric field distribution produced by any disposition of insulating and conducting materials is a key aspect in electrical design, but exact values can only be obtained in simple geometries. In this work, using commercially available F.E.M. software we show the influence of the edge-effect on the electric field distribution of a two parallel-plane conducting plates system surrounded by an insulating medium taking into account the thickness of the conducting plates. We compare our results with previous published works. Finally, we obtain the relationship between capacitance and insulation characteristics, insulation gap, plate dimensions and plate thicknessCatalán Izquierdo, S.; Bueno Barrachina, JM.; Cañas Peñuelas, CS.; Cavallé Sesé, F. (2009). Capacitance evaluation on parallel-plate capacitors by means of finite element analysis. Renewable Energy and Power Quality Journal. 1(7):613-616. http://hdl.handle.net/10251/92552S6136161

Enhancement of Non-Invasive Recording of Electroenterogram by Means of a Flexible Array of Concentric Ring Electrodes

Monitoring intestinal myoelectrical activity by electroenterogram (EEnG) would be of great clinical interest for diagnosing gastrointestinal pathologies and disorders. However, surface EEnG recordings are of very low amplitude and can be severely affected by baseline drifts and respiratory and electrocardiographic (ECG) interference. In this work, a flexible array of concentric ring electrodes was developed and tested to determine whether it can provide surface EEnG signals of better quality than bipolar recordings from conventional disc electrodes. With this aime, sixteen healthy subjects in a fasting state (>8h) underwent recording. The capabiltiy of detecting intestinal pacemaker activity (slow wave) and the influence of physiological interferences were studied. The signals obtained from the concentric ring electrodes proved to be more robust to ECG and respiratory interference than those from conventional disc electrodes. The results also show that intestinal EEnG components such as the slow wave can be more easily identified by the proposed system based on a flexible array of concentric ring electrodes. The developed active electrode array could be a very valuable tool for non-invasive diagnosis of disease states such as ischemia and motility disorders of the small bowel which are known to alter the normal enteric slow wave activity.Research supported in part by the Ministerio de Ciencia y Tecnologia de Espana (TEC 2010-16945). The proof-reading of this paper was funded by the Universitat Politecnica de Valencia, Spain.Garcia Casado, FJ.; Zena Giménez, VF.; Prats Boluda, G.; Ye Lin, Y. (2014). Enhancement of Non-Invasive Recording of Electroenterogram by Means of a Flexible Array of Concentric Ring Electrodes. Annals of Biomedical Engineering. 42(3):651-660. https://doi.org/10.1007/s10439-013-0935-yS651660423Abo, M., J. Liang, L. Qian, and J. D. Chen. Distension-induced myoelectrical dysrhythmia and effect of intestinal pacing in dogs. Dig. Dis. Sci. 45(1):129–135, 2000.Besio, W., R. Aakula, K. Koka, and W. Dai. Development of a tri-polar concentric ring electrode for acquiring accurate Laplacian body surface potentials. Ann. Biomed. Eng. 34(3):426–435, 2006.Besio, W., and T. Chen. Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping. Physiol. Meas. 28(5):515–529, 2007.Bradshaw, L. A., S. H. Allos, J. P. Wikswo, Jr, and W. O. Richards. Correlation and comparison of magnetic and electric detection of small intestinal electrical activity. Am. J. Physiol. 272(5 Pt 1):G1159–G1167, 1997.Bradshaw, L. A., J. K. Ladipo, D. J. Staton, J. P. Wikswo, Jr, and W. O. Richards. The human vector magnetogastrogram and magnetoenterogram. IEEE Trans. Biomed. Eng. 46(8):959–970, 1999.Bradshaw, L. A., W. O. Richards, and J. P. Wikswo, Jr. Volume conductor effects on the spatial resolution of magnetic fields and electric potentials from gastrointestinal electrical activity. Med. Biol. Eng Comput. 39(1):35–43, 2001.Caenepeel, P., W. Janssens, A. Accarino, J. Janssens, G. Vantrappen, and H. Eyssen. Variation of slow-wave frequency and locking during the migrating myoelectric complex in dogs. Am. J. Physiol. 261(6):G1079–G1084, 1991.Chang, F. Y., C.-L. Lu, C.-Y. Chen, J.-C. Luo, S.-D. Lee, H.-C. Wu, and J. D. Z. Chen. Fasting and postprandial small intestinal slow waves non-invasively measured in subjects with total gastrectomy. Gastroenterology 22:247–252, 2006.Chen, J. D. Z. Non-invasive measurement of gastric myoelectrical activity and its analysis and applications. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol. 20, 1998, pp. 2802–2807.Chen, J. D. Z., D. Schirmer, and R. W. McCallum. Measurement of electric activity of the human small intestine using surface electrodes. IEEE Trans. Biomed. Eng. 40(6):598–602, 1993.Clifton, J. A., J. Christensen, and H. P. Schedl. The human small intestinal slow wave. Trans. Am. Clin. Climatol. Assoc. 77:217–225, 1966.Feltane, A., G. F. Boudreaux-Bartels, and W. Besio. Automatic seizure detection in rats using Laplacian EEG and verification with human seizure signals. Ann. Biomed. Eng. 41(3):645–654, 2013.Fleckenstein, P., and A. Oigaard. Electrical spike activity in the human small intestine. A multiple electrode study of fasting diurnal variations. Am. J. Dig. Dis. 23(9):776–780, 1978.Garcia-Casado, J., J. L. Martinez-de-Juan, and J. L. Ponce. Noninvasive measurement and analysis of intestinal myoelectrical activity using surface electrodes. IEEE Trans. Biomed. Eng. 52(6):983–991, 2005.Garcia-Casado, J., J. L. Martinez-de-Juan, and J. L. Ponce. Adaptive filtering of ECG interference on surface EEnGs based on signal averaging. Physiol. Meas. 27(6):509–527, 2006.Gruetzmann, A., S. Hansen, and J. Muller. Novel dry electrodes for ECG monitoring. Physiol. Meas. 28(11):1375–1390, 2007.He, B., and R. J. Cohen. Body surface Laplacian mapping of cardiac electrical activity. Am. J. Cardiol. 70(20):1617–1620, 1992.Koka, K., and W. G. Besio. Improvement of spatial selectivity and decrease of mutual information of tri-polar concentric ring electrodes. J. Neurosci. Methods 165(2):216–222, 2007.Lammers, W. J., H. M. Al-Bloushi, S. A. Al-Eisae, F. A. Al-Dhaheri, B. Stephen, R. John, S. Dhanasekaran, and M. Karam. Slow wave propagation and plasticity of interstitial cells of Cajal in the small intestine of diabetic. Exp. Physiol. 96:1039–1048, 2011.Li, G., Y. Wang, W. Jiang, L. L. Wang, C.-Y. S. Lu, and W. G. Besio. Active Laplacian electrode for the data-acquisition system of EHG. J. Phys: Conf. Ser. 13:330–335, 2005.Li, G. L., J. Lian, P. Salla, J. Cheng, I. Ramachandra, P. Shah, B. Avitall, and B. He. Body surface Laplacian electrocardiogram of ventricular depolarization in normal human subjects. J. Cardiovasc. Electrophysiol. 14(1):16–27, 2003.Lian, J., G. Li, J. Cheng, B. Avitall, and B. He. Body surface Laplacian mapping of atrial depolarization in healthy human subjects. Med. Biol. Eng Comput. 40(6):650–659, 2002.Lin, Z. Y., and J. D. Z. Chen. Recursive running DCT algorithm and its application in adaptive filtering of surface electrical recording of small-intestine. Med. Biol. Eng. Comput. 32(3):317–322, 1994.Lindh, W. Q., M. Pooler, C. D. Tamparo, B. M. Dahl, and J. Morris. Delmar’s Comprehensive Medical Assisting: Administrative and Clinical Competencies. Clifton Park, NY: Delmar Cengage Learning, p. 573, 2009.Madl, C., and W. Druml. Gastrointestinal disorders of the critically ill. Systemic consequences of ileus. Best. Pract. Res. Clin. Gastroenterol. 17(3):445–456, 2003.Merletti, R. Standards for reporting EMG data. J. Electromyography Kinesiol. 9(1):III–IV, 1999.Morrison, P., B. W. Miedema, L. Kohler, and K. A. Kelly. Electrical rysrhythmias in the Roux jejunal limb—cause and treatment. Am. J. Surg. 160(3):252–256, 1990.Park, H. The pathophysiology of irritable bowel syndrome: inflammation and motor disorder. Korean J. Gastroenterol. 47(2):101–110, 2006.Prats-Boluda, G., J. Garcia-Casado, J. L. Martinez-de-Juan, and J. L. Ponce. Identification of the slow wave component of the electroenterogram from Laplacian abdominal surface recordings in humans. Physiol. Meas. 28(9):1115–1133, 2007.Prats-Boluda, G., J. Garcia-Casado, J. L. Martinez-de-Juan, and Y. Ye-Lin. Active concentric ring electrode for non-invasive detection of intestinal myoelectric signals. Med. Eng. Phys. 33(4):446–455, 2011.Prats-Boluda, G., Y. Ye-Lin, E. Garcia-Breijó, J. Ibañez, and J. Garcia-Casado. Active flexible concentric ring electrode for noninvasive surface bioelectrical recordings. Meas. Sci. Technol. 23(125703):1–10, 2012.Saito, Y. A., P. R. Strege, D. J. Tester, G. R. Locke, N. J. Talley, C. E. Bernard, J. L. Rae, J. C. Makielski, M. J. Ackerman, and G. Farrugia. Sodium channel mutation in irritable bowel syndrome: evidence for an ion channelopathy. Am. J. Physiol. Gastrointest. Liver Physiol. 296(2):G211–G218, 2009.Shafik, A., A. A. Shafik, O. El Sibai, and I. Ahmed. Colonic pacing in patients with constipation due to colonic inertia. Med. Sci. Monit. 9(5):191–196, 2003.Somarajan, S., S. Cassilly, C. Obioha, L. Bradshaw, and W. Richards. Noninvasive biomagnetic detection of isolated ischemic bowel segments. IEEE Trans. Biomed. Eng. 60(6):1677–1684, 2013.Soundararajan, V., and W. Besio. Simulated comparison of disc and concentric electrode maps during atrial arrhythmias. Int. J. Bioelectromagn 7(1):217–220, 2005.Summers, R. W., S. Anuras, and J. Green. Jejunal manometry patterns in health, partial intestinal obstruction, and pseudoobstruction. Gastroenterology 85(6):1290–1300, 1983.Webster, J. G., J. W. Clark, Jr., M. R. Neuman, W. H. Olson, R. A. Peura, F. P. J. Primiano, M. P. Siedband, and L. A. Wheeler. Medical Instrumentation Application and Design. NewYork: Wiley, 1998.Weisbrodt, N. W. Motility of the small intestine. In: Physiology of the Gastrointestinal Tract, edited by L. R. Johnson. New York: Raven Press, 1987, pp. 631–663.Wu, D., H. C. Tsai, and B. He. On the estimation of the Laplacian electrocardiogram during ventricular activation. Ann. Biomed. Eng. 27(6):731–745, 1999.Ye-Lin, Y., J. Garcia-Casado, J. L. Martinez-de-Juan, G. Prats-Boluda, and J. L. Ponce. The detection of intestinal spike activity on surface electroenterograms. Phys. Med. Biol. 55(3):663–680, 2010.Ye-Lin, Y., J. Garcia-Casado, G. Prats-Boluda, J. L. Ponce, and J. L. Martinez-de-Juan. Enhancement of the non-invasive electroenterogram to identify intestinal pacemaker activity. Physiol. Meas. 30(9):885–902, 2009

Feasibility and analysis of bipolar concentric recording of Electrohysterogram with flexible active electrode

The conduction velocity and propagation patterns of Electrohysterogram (EHG) provide fundamental information about uterine electrophysiological condition. The accuracy of these measurements can be impaired by both the poor spatial selectivity and sensitivity to the relative direction of the contraction propagation associated with conventional disc electrodes. Concentric ring electrodes could overcome these limitations the aim of this study was to examine the feasibility of picking up surface EHG signals using a new flexible tripolar concentric ring electrode (TCRE), and to compare it with conventional bipolar recordings. Simultaneous recording of conventional bipolar signals and bipolar concentric EHG (BC-EHG) were carried out on 22 pregnant women. Signal bursts were characterized and compared. No significant differences among channels in either duration or dominant frequency in the Fast Wave High frequency range were found. Nonetheless, the high pass filtering effect of the BC-EHG records resulted in lower frequency content within the range 0.1 to 0.2 Hz than the bipolar ones. Although the BC-EHG signal amplitude was about 5-7 times smaller than that of bipolar recordings, similar signal-to-noise ratio was obtained. These results suggest that the flexible TCRE is able to pick up uterine electrical activity and could provide additional information for deducing uterine electrophysiological condition.The authors are grateful to the Obstetrics Unit of the Hospital Universitario La Fe de Valencia (Valencia, Spain), where the recording sessions were carried out. The work was supported in part by the Ministerio de Ciencia y Tecnologia de Espana (TEC2010-16945), by the Universitat Politecnica de Valencia (PAID SP20120490) and Generalitat Valenciana (GV/2014/029) and by General Electric Healthcare.Ye Lin, Y.; Alberola Rubio, J.; Prats Boluda, G.; Perales Marin, AJ.; Desantes, D.; Garcia Casado, FJ. (2015). Feasibility and analysis of bipolar concentric recording of Electrohysterogram with flexible active electrode. Annals of Biomedical Engineering. 43(4):968-976. https://doi.org/10.1007/s10439-014-1130-5S968976434Alberola-Rubio, J., G. Prats-Boluda, Y. Ye-Lin, J. Valero, A. Perales, and J. Garcia-Casado. Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics. Med. Eng. Phys. 35(12):1736–1743, 2013.Besio, W. G., K. Koka, R. Aakula, and W. Dai. Tri-polar concentric ring electrode development for laplacian electroencephalography. IEEE Trans. Biomed. Eng. 53(5):926–933, 2006.Devasahayam, S. R. Signals and Systems in Biomedical Engineering. Berlin: Springer, 2013.Devedeux, D., C. Marque, S. Mansour, G. Germain, and J. Duchene. Uterine electromyography: a critical review. Am. J. Obstet. Gynecol. 169(6):1636–1653, 1993.Estrada, L., A. Torres, J. Garcia-Casado, G. Prats-Boluda, and R. Jane. Characterization of laplacian surface electromyographic signals during isometric contraction in biceps brachii. Conf. Proc. IEEE Eng Med. Biol. Soc. 2013:535–538, 2013.Euliano, T. Y., D. Marossero, M. T. Nguyen, N. R. Euliano, J. Principe, and R. K. Edwards. Spatiotemporal electrohysterography patterns in normal and arrested labor. Am. J. Obstet. Gynecol. 200(1):54–57, 2009.Farina, D., and C. Cescon. Concentric-ring electrode systems for noninvasive detection of single motor unit activity. IEEE Trans. Biomed. Eng. 48(11):1326–1334, 2001.Fele-Zorz, G., G. Kavsek, Z. Novak-Antolic, and F. Jager. A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups. Med. Biol. Eng Comput. 46(9):911–922, 2008.Garfield, R. E., and W. L. Maner. Physiology and electrical activity of uterine contractions. Semin. Cell Dev. Biol. 18(3):289–295, 2007.Garfield, R. E., W. L. Maner, L. B. Mackay, D. Schlembach, and G. R. Saade. Comparing uterine electromyography activity of antepartum patients vs. term labor patients. Am. J. Obstet. Gynecol. 193(1):23–29, 2005.Garfield, R. E., H. Maul, L. Shi, W. Maner, C. Fittkow, G. Olsen, and G. R. Saade. Methods and devices for the management of term and preterm labor. Ann. N. Y. Acad. Sci. 943(1):203–224, 2001.Hassan, M., J. Terrien, C. Muszynski, A. Alexandersson, C. Marque, and B. Karlsson. Better pregnancy monitoring using nonlinear correlation analysis of external uterine electromyography. IEEE Trans. Biomed. Eng. 60(4):1160–1166, 2013.Kaufer, M., L. Rasquinha, and P. Tarjan. Optimization of multi-ring sensing electrode set, Conference proceedings of IEEE Engineering in Medicine and Biology Society, 1990, pp. 612–613.Koka, K., and W. G. Besio. Improvement of spatial selectivity and decrease of mutual information of tri-polar concentric ring electrodes. J. Neurosci. Methods 165(2):216–222, 2007.Lu, C.-C., and P. P. Tarjan. Pasteless, active, concentric ring sensors for directly obtained laplacian cardiac electrograms. J. Med. Biol. Eng. 22(4):199–203, 2002.Lucovnik, M., W. L. Maner, L. R. Chambliss, R. Blumrick, J. Balducci, Z. Novak-Antolic, and R. E. Garfield. Noninvasive uterine electromyography for prediction of preterm delivery. Am. J. Obstet. Gynecol. 204(3):228.e1–228.e10, 2011.Maner, W. L., and R. E. Garfield. Identification of human term and preterm labor using artificial neural networks on uterine electromyography data. Ann. Biomed. Eng. 35(3):465–473, 2007.Maner, W. L., R. E. Garfield, H. Maul, G. Olson, and G. Saade. Predicting term and preterm delivery with transabdominal uterine electromyography. Obstet. Gynecol. 101(6):1254–1260, 2003.Marque, C., J. M. Duchene, S. Leclercq, G. S. Panczer, and J. Chaumont. Uterine EHG processing for obstetrical monitoring. IEEE Trans. Biomed. Eng. 33(12):1182–1187, 1986.Marque, C. K., J. Terrien, S. Rihana, and G. Germain. Preterm labour detection by use of a biophysical marker: the uterine electrical activity. BMC. Pregnancy Childbirth. 7(Suppl1):S5, 2007.Maul, H., W. L. Maner, G. Olson, G. R. Saade, and R. E. Garfield. Non-invasive transabdominal uterine electromyography correlates with the strength of intrauterine pressure and is predictive of labor and delivery. J. Matern. Fetal Neonatal Med. 15(5):297–301, 2004.Miles, A. M., M. Monga, and K. S. Richeson. Correlation of external and internal monitoring of uterine activity in a cohort of term patients. Am. J. Perinatol. 18(3):137–140, 2001.Prats-Boluda, G., J. Garcia-Casado, J. L. Martinez-de-Juan, and Y. Ye-Lin. Active concentric ring electrode for non-invasive detection of intestinal myoelectric signals. Med. Eng. Phys. 33(4):446–455, 2010.Prats-Boluda, G., Y. Ye-Lin, E. Garcia-Breijo, J. Ibañez, and J. Garcia-Casado. Active flexible concentric ring electrode for non-invasive surface bioelectrical recordings. Meas. Sci. Technol. 23(12):1–10, 2012.Rabotti, C., M. Mischi, S. G. Oei, and J. W. Bergmans. Noninvasive estimation of the electrohysterographic action-potential conduction velocity. IEEE Trans. Biomed. Eng. 57(9):2178–2187, 2010.Rabotti, C., S. G. Oei, H. J. van ‘t, and M. Mischi. Electrohysterographic propagation velocity for preterm delivery prediction. Am. J. Obstet. Gynecol. 205(6):e9–e10, 2011.Rooijakkers, M. J., S. Song, C. Rabotti, S. G. Oei, J. W. Bergmans, E. Cantatore, and M. Mischi. Influence of electrode placement on signal quality for ambulatory pregnancy monitoring. Comput. Math. Methods Med. 2014(1):960980, 2014.Schlembach, D., W. L. Maner, R. E. Garfield, and H. Maul. Monitoring the progress of pregnancy and labor using electromyography. Eur. J. Obstet. Gynecol. Reprod. Biol. 144(Suppl1):S33–S39, 2009.Sikora, J., A. Matonia, R. Czabanski, K. Horoba, J. Jezewski, and T. Kupka. Recognition of premature threatening labour symptoms from bioelectrical uterine activity signals. Arch. Perinatal Med. 17(2):97–103, 2011.Terrien, J., C. Marque, and B. Karlsson. Spectral characterization of human EHG frequency components based on the extraction and reconstruction of the ridges in the scalogram, Conference proceedings of IEEE Engineering in Medicine and Biology Society, 2007, pp. 1872–1875.Terrien, J., C. Marque, T. Steingrimsdottir, and B. Karlsson. Evaluation of adaptive filtering methods on a 16 electrode electrohysterogram recorded externally in labor, 11th Mediterranean Conference on Medical and Biomedical Engineering and Computing, 2007, Vol. 16, pp. 135–138.U.S. Preventive Services Task Force. Guide to clinical preventive services: an assessment of the effectiveness of 169 interventions. Baltimore: Willams & Wilkins, 1989

Gastric Myoelectrical Activity in Patients with Diabetes

This descriptive, correlational study investigated the associations among gastric myoelectrical activity (GMA), upper gastrointestinal (GI) symptoms, and glucose control. The study also attempted to determine whether any relationship existed between upper GI symptoms, glucose control, age, or length of diagnosis and pattern of GMA identified using electrogastrography (EGG). A total of 25 persons participated in the study. The sample was comprised of 7 healthy controls, 5 patients diagnosed with type 1 diabetes, and 13 patients diagnosed with type 2 diabetes. Electrogastrography was performed for 30 minutes in the fasting state and continued at 30-minute intervals for a total of 1-1/2 hours post-prandially. Data from the fasting, 30-minute post-prandial period, and 120-minute post-prandial periods were analyzed for the study. Findings of this study support the potential use of EGG as a screening tool in the detection of patterns of GMA in healthy and diabetic individuals. Using EGG, gastric myoelectrical activity can be identified in both healthy controls and patients diagnosed with diabetes. Further studies are needed to generate data that can be used to explain the pathology behind, and relationship between GMA abnormalities, upper GI signs and symptoms, and the lack of glucose control in patients with diabetes

Design of a non-invasive sensing system for diagnosing gastric disorders

Gastric disorders are widely spread among the population of any age. At the moment, the diagnosis is made by using invasive systems that cause several side effects. The present manuscript proposes an innovative non-invasive sensing system for diagnosing gastric dysfunctions. The Electro-GastroGraphy (EGG) technique is used to record myoelectrical signals of stomach activities. Although EGG technique is well known for a long time, several issues concerning the signal processing and the definition of suitable diagnostic criteria are still unresolved. So, EGG is to this day a trial practice. The authors want to overcome the current limitations of the technique and improve its relevance. To this purpose, a smart EGG sensing system has been designed to non-invasively diagnose gastric disorders. In detail, the system records the gastric slow waves by means of skin surface electrodes placed in the epigastric area. Cutaneous myoelectrical signals are so acquired from the body surface in proximity of stomach. Electro-gastrographic record is then processed. According to the diagnostic model designed from the authors, the system estimates specific diagnostic parameters in time and frequency domains. It uses Discrete Wavelet Transform to obtain power spectral density diagrams. The frequency and power of the EGG waveform and the dominant frequency components are so analyzed. The defined diagnostic parameters are put in comparison with the reference values of a normal EGG in order to estimate the presence of gastric pathologies by the analysis of arrhythmias (tachygastria, bradygastria and irregular rhythm). The paper aims to describe the design of the system and of the arrhythmias detection algorithm. Prototype development and experimental data will be presented in future works. Preliminary results show an interesting relevance of the suggested technique so that it can be considered as a promising non-invasive tool for diagnosing gastrointestinal motility disorders

Active flexible concentric ring electrode for non-invasive surface bioelectrical recordings

Bioelectrical surface recordings are usually performed by unipolar or bipolar disc electrodes even though they entail the serious disadvantage of having poor spatial resolution. Concentric ring electrodes give improved spatial resolution, although this type of electrode has so far only been implemented in rigid substrates and as they are not adapted to the curvature of the recording surface may provide discomfort to the patient. Moreover, the signals recorded by these electrodes are usually lower in amplitude than conventional disc electrodes. The aim of this work was thus to develop and test a new modular active sensor made up of concentric ring electrodes printed on a flexible substrate by thick-film technology together with a reusable battery-powered signal-conditioning circuit. Simultaneous ECG recording with both flexible and rigid concentric ring electrodes was carried out on ten healthy volunteers at rest and in motion. The results show that flexible concentric ring electrodes not only present lower skin electrode contact impedance and lower baseline wander than rigid electrodes but are also less sensitive to interference and motion artefacts. We believe these electrodes, which allow bioelectric signals to be acquired non-invasively with better spatial resolution than conventional disc electrodes, to be a step forward in the development of new monitoring systems based on Laplacian potential recordings.This research was supported in part by the Ministerio de Ciencia y Tecnologia de Espana (TEC2010-16945) and by the Universitat Politecnica de Valencia (PAID 2009/10-2298). The proof-reading of this paper was funded by the Universitat Politecnica de Valencia, Spain.Prats Boluda, G.; Ye Lin, Y.; García Breijo, E.; Ibáñez Civera, FJ.; Garcia Casado, FJ. (2012). Active flexible concentric ring electrode for non-invasive surface bioelectrical recordings. Measurement Science and Technology. 23(12):1-10. https://doi.org/10.1088/0957-0233/23/12/125703S1102312Malmivuo, J., & Plonsey, R. (1995). BioelectromagnetismPrinciples and Applications of Bioelectric and Biomagnetic Fields. doi:10.1093/acprof:oso/9780195058239.001.0001Gevins, A. (1989). Dynamic functional topography of cognitive tasks. Brain Topography, 2(1-2), 37-56. doi:10.1007/bf01128842Bradshaw, L. A., Wijesinghe, R. S., & Wikswo, Jr., J. P. (2001). Spatial Filter Approach for Comparison of the Forward and Inverse Problems of Electroencephalography and Magnetoencephalography. Annals of Biomedical Engineering, 29(3), 214-226. doi:10.1114/1.1352641Bradshaw, L. A., Richards, W. O., & Wikswo, J. P. (2001). Volume conductor effects on the spatial resolution of magnetic fields and electric potentials from gastrointestinal electrical activity. Medical & Biological Engineering & Computing, 39(1), 35-43. doi:10.1007/bf02345264Garcia-Casado, J., Martinez-de-Juan, J. L., & Ponce, J. L. (2005). Noninvasive Measurement and Analysis of Intestinal Myoelectrical Activity Using Surface Electrodes. IEEE Transactions on Biomedical Engineering, 52(6), 983-991. doi:10.1109/tbme.2005.846730SippensGroenewegen, A., Peeters, H. A. P., Jessurun, E. R., Linnenbank, A. C., Robles de Medina, E. O., Lesh, M. D., & van Hemel, N. M. (1998). Body Surface Mapping During Pacing at Multiple Sites in the Human Atrium. Circulation, 97(4), 369-380. doi:10.1161/01.cir.97.4.369Lian, J., Li, G., Cheng, J., Avitall, B., & He, B. (2002). Body surface Laplacian mapping of atrial depolarization in healthy human subjects. Medical & Biological Engineering & Computing, 40(6), 650-659. doi:10.1007/bf02345304Wu, D., Tsai, H. C., & He, B. (1999). On the Estimation of the Laplacian Electrocardiogram during Ventricular Activation. Annals of Biomedical Engineering, 27(6), 731-745. doi:10.1114/1.224Koka, K., & Besio, W. G. (2007). Improvement of spatial selectivity and decrease of mutual information of tri-polar concentric ring electrodes. Journal of Neuroscience Methods, 165(2), 216-222. doi:10.1016/j.jneumeth.2007.06.007Prats-Boluda, G., Garcia-Casado, J., Martinez-de-Juan, J. L., & Ye-Lin, Y. (2011). Active concentric ring electrode for non-invasive detection of intestinal myoelectric signals. Medical Engineering & Physics, 33(4), 446-455. doi:10.1016/j.medengphy.2010.11.009He, B., & Cohen, R. J. (1992). Body surface Laplacian mapping of cardiac electrical activity. The American Journal of Cardiology, 70(20), 1617-1620. doi:10.1016/0002-9149(92)90471-aBesio, W., Aakula, R., Koka, K., & Dai, W. (2006). Development of a Tri-polar Concentric Ring Electrode for Acquiring Accurate Laplacian Body Surface Potentials. Annals of Biomedical Engineering, 34(3), 426-435. doi:10.1007/s10439-005-9054-8Ye-Lin, Y., Garcia-Casado, J., Prats-Boluda, G., Ponce, J. L., & Martinez-de-Juan, J. L. (2009). Enhancement of the non-invasive electroenterogram to identify intestinal pacemaker activity. Physiological Measurement, 30(9), 885-902. doi:10.1088/0967-3334/30/9/002Hjorth, B. (1975). An on-line transformation of EEG scalp potentials into orthogonal source derivations. Electroencephalography and Clinical Neurophysiology, 39(5), 526-530. doi:10.1016/0013-4694(75)90056-5Perrin, F., Pernier, J., Bertnard, O., Giard, M. ., & Echallier, J. . (1987). Mapping of scalp potentials by surface spline interpolation. Electroencephalography and Clinical Neurophysiology, 66(1), 75-81. doi:10.1016/0013-4694(87)90141-6Nunez, P. L., & Westdorp, A. F. (1994). The surface laplacian, high resolution EEG and controversies. Brain Topography, 6(3), 221-226. doi:10.1007/bf01187712Srinivasan, R., Nunez, P. L., Tucker, D. M., Silberstein, R. B., & Cadusch, P. J. (1996). Spatial sampling and filtering of EEG with spline Laplacians to estimate cortical potentials. Brain Topography, 8(4), 355-366. doi:10.1007/bf01186911Farina, D., & Cescon, C. (2001). Concentric-ring electrode systems for noninvasive detection of single motor unit activity. IEEE Transactions on Biomedical Engineering, 48(11), 1326-1334. doi:10.1109/10.959328G. Besio, C. C. Lu, P. P. Tarjan, W. (2001). A Feasibility Study for Body Surface Cardiac Propagation Maps of Humans from Laplacian Moments of Activation. Electromagnetics, 21(7-8), 621-632. doi:10.1080/027263401752246243Li, G., Wang, Y., Lin, L., Jiang, W., Wang, L. L., Lu, S. C.-Y., & Besio, W. G. (2005). Active Laplacian electrode for the data-acquisition system of EHG. Journal of Physics: Conference Series, 13, 330-335. doi:10.1088/1742-6596/13/1/077Engel, J., Chen, J., & Liu, C. (2003). Development of polyimide flexible tactile sensor skin. Journal of Micromechanics and Microengineering, 13(3), 359-366. doi:10.1088/0960-1317/13/3/302Papakostas, T. V., Lima, J., & Lowe, M. (s. f.). A large area force sensor for smart skin applications. Proceedings of IEEE Sensors. doi:10.1109/icsens.2002.1037366Stieglitz, T. (2001). Flexible biomedical microdevices with double-sided electrode arrangements for neural applications. Sensors and Actuators A: Physical, 90(3), 203-211. doi:10.1016/s0924-4247(01)00520-9Hamilton, P. S., & Tompkins, W. J. (1986). Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database. IEEE Transactions on Biomedical Engineering, BME-33(12), 1157-1165. doi:10.1109/tbme.1986.325695Besio, W., & Chen, T. (2007). Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping. Physiological Measurement, 28(5), 515-529. doi:10.1088/0967-3334/28/5/006Besio, G., Koka, K., Aakula, R., & Weizhong Dai. (2006). Tri-polar concentric ring electrode development for Laplacian electroencephalography. IEEE Transactions on Biomedical Engineering, 53(5), 926-933. doi:10.1109/tbme.2005.863887Setti, L., Fraleoni-Morgera, A., Ballarin, B., Filippini, A., Frascaro, D., & Piana, C. (2005). An amperometric glucose biosensor prototype fabricated by thermal inkjet printing. Biosensors and Bioelectronics, 20(10), 2019-2026. doi:10.1016/j.bios.2004.09.022Reddy, A. S. G., Narakathu, B. B., Atashbar, M. Z., Rebros, M., Rebrosova, E., & Joyce, M. K. (2011). Gravure Printed Electrochemical Biosensor. Procedia Engineering, 25, 956-959. doi:10.1016/j.proeng.2011.12.235Gruetzmann, A., Hansen, S., & Müller, J. (2007). Novel dry electrodes for ECG monitoring. Physiological Measurement, 28(11), 1375-1390. doi:10.1088/0967-3334/28/11/005LI, G., LIAN, J., SALLA, P., CHENG, J., RAMACHANDRA, I., SHAH, P., … HE, B. (2003). Body Surface Laplacian Electrocardiogram of Ventricular Depolarization in Normal Human Subjects. Journal of Cardiovascular Electrophysiology, 14(1), 16-27. doi:10.1046/j.1540-8167.2003.02199.