A New Method for Cardiac Diseases Diagnosis
Affiliation(s)
1 College of Applied Medical Sciences, Department of Medical Equipment Technology, Prince Sattam Bin Abdulaziz University, Al-Kharj, KSA. 2 Higher Institute of Medical Technologies of Tunis, Laboratory of Biophysics, University of Tunis El Manar, Tunis, Tunisia.
1 College of Applied Medical Sciences, Department of Medical Equipment Technology, Prince Sattam Bin Abdulaziz University, Al-Kharj, KSA. 2 Higher Institute of Medical Technologies of Tunis, Laboratory of Biophysics, University of Tunis El Manar, Tunis, Tunisia.
ABSTRACT
The objective of this work is to perform automatic diagnosis using a non invasive method which consists on the bioimpedance signal processing. Bioimpedance signal (BIS) represents the aorta impedance variation during the heart cycle activity. BIS is detected by mean of two electrodes located at the level of the ascendant aorta. Automatic diagnosis method consists on preparing, first, a data base with a set of cepstral parameters of different BIS according to normal case and different cardiac diseases. This data base is composed from n classes Yk corresponding to n diseases. The classification of anonymous individuals is based on the determination of Fisher distance between anonymous disease and class Yk using Fischer formula. Our method permits to calculate seven relevant cepstral parameters. The application of Fisher method has allowed us to perform the diagnosis of five anonymous cases. The major interest of this method is its especially useful for the exploration of cardiovascular system anomalies for emergency cases, children, elderly and pregnant women who can’t support surgical operations especially at the level of the heart.
The objective of this work is to perform automatic diagnosis using a non invasive method which consists on the bioimpedance signal processing. Bioimpedance signal (BIS) represents the aorta impedance variation during the heart cycle activity. BIS is detected by mean of two electrodes located at the level of the ascendant aorta. Automatic diagnosis method consists on preparing, first, a data base with a set of cepstral parameters of different BIS according to normal case and different cardiac diseases. This data base is composed from n classes Yk corresponding to n diseases. The classification of anonymous individuals is based on the determination of Fisher distance between anonymous disease and class Yk using Fischer formula. Our method permits to calculate seven relevant cepstral parameters. The application of Fisher method has allowed us to perform the diagnosis of five anonymous cases. The major interest of this method is its especially useful for the exploration of cardiovascular system anomalies for emergency cases, children, elderly and pregnant women who can’t support surgical operations especially at the level of the heart.
KEYWORDS
Signal Processing, Cepstral Parameters, Bioimpedance, Cardiac Diseases, Automatic Diagnosis
Signal Processing, Cepstral Parameters, Bioimpedance, Cardiac Diseases, Automatic Diagnosis
Cite this paper
Salah, R. , Alhadidi, T. , Mansouri, S. and Naouar, M. (2015) A New Method for Cardiac Diseases Diagnosis. Advances in Bioscience and Biotechnology, 6, 311-319. doi: 10.4236/abb.2015.64030.
Salah, R. , Alhadidi, T. , Mansouri, S. and Naouar, M. (2015) A New Method for Cardiac Diseases Diagnosis. Advances in Bioscience and Biotechnology, 6, 311-319. doi: 10.4236/abb.2015.64030.
References
[1] Yan, J.Y., Lu, Y., Liu, J. and Wu, X.Y. (2010) Intelligent Diagnosis of Cardiovascular Diseases Utilizing ECG Signals. International Journal of Information Acquisition, 07, 81.
http://dx.doi.org/10.1142/S0219878910002087 [2] Kumaravel, N., Sridhar, K.S. and Nithiyanandam, N. (1996) Automatic Diagnosis of Heart Diseases Using Neural Network. Biomedical Engineering Conference, Dayton, 29-31 March 1996, 319-322.
http://dx.doi.org/10.1109/SBEC.1996.493214 [3] Hong, B., Kai, J., Ren, Y., Han, J., Zou, Z., Ahn, C.H. and Kang, K.A. (2008) Highly Sensitive Rapid, Reliable, and Automatic Cardiovascular Disease Diagnosis with Nanoparticle Fluorescence Enhancer and Mems. Advances in Experimental Medicine and Biology, 614, 265-273.
http://dx.doi.org/10.1007/978-0-387-74911-2_30 [4] Scherhag, A.W., et al. (2013) Continuous Measurement of Hemodynamic Alterations during Pharmacologic Cardiovascular Stress Using Automated Impedance Cardiography. The Journal of Clinical Pharmacology, 37, 21S-28S. [5] Fortin, J., et al. (2006) Non-Invasive Beat-To-Beat Cardiac Output Monitoring by an Improved Method of Transthoracic Bioimpedance Measurement. Computers in Biology and Medicine, 36, 1185-1203.
http://dx.doi.org/10.1016/j.compbiomed.2005.06.001 [6] Kubicek, W.G., Karnegis, J.N., Patterson, R.P., Witsoe, D.A. and Mattson, R.H. (1966) Development and Evaluation of an Impedance Cardiac Output System. Aerospace Medicine, 37, 1208-1212. [7] Bizouarn, P., Blanloeil, Y. and De La Coussaye, J.E. (1996) Conférences d’actualisation “Méthodes de mesure du débit cardiaque en réanimation”. Elsevier, Paris, et Société Française d’Anesthésie et de Réanimation (SFAR), 377-398. [8] Ben Salah, R. (1988) Pléthysmographie électrique thoracique localisée. Application à la détermination des paramètres cardiovasculaires et au diagnostic des cardiopathies. Ph.D. Faculté des sciences de Tunis. [9] Chemam, M.N. (1983) Analyse automatique des signaux pléthysmographiques. Application à la mesure du débit sanguin et à la reconnaissance des cardiopathies. Ph.D. Dissetation, ENIT, Tunis. [10] Collete, M., Leftheriotis, G. and Humeau, A. (2009) Modeling and Interpretation of the Bioelectrical Impedance Signal for the Determination of the Local Arterial Stiffness. Medical Physics, 36, 4340-4348.
http://dx.doi.org/10.1118/1.3213084 [11] Ivorra, A. (2002) Bioimpédance Monitoring for Physicians: An Overview. Centre Nacional de Microelectrònica, Barcelona, Spain. [12] Kubicek, W.G., Patterson, R.P. and Witsoe, D.A. (1970) Impedance Cardiography as a Non Invasive Method of Monitoring Cardiac Function and Other Parameters of the Cardiovascular System. Annals of the N. Y. Academy of Sciences, 170, 724-732.
http://dx.doi.org/10.1111/j.1749-6632.1970.tb17735.x [13] Mansouri, S., Mahjoubi, H. and Ben Salah, R. (2010) Determination of Instantaneous Arterial Blood Pressure from Bio-Impedance Signal. Journal of Biophysics and Structural Biology, 2, 009-015. [14] Mansouri, S., Mahjoubi, H. and Ben Salah, R. (2009) FPGA-Based Derivative Module for Bioimpedance Signal. International Journal of Computer Science and Network Security, 9, 16-20. [15] Mansouri, S. (2011) Conception d’un système de détermination non invasive des paramètres biorhéologiques cardiovasculaire par la méthode de bioimpédance périphérique. Ph.D. Faculté des sciences de Tunis. [16] Romeder, J.M. (1973) Méthode et programme d’analyse discriminante, Dunod. [17] Ben Salah, R., et al. (1988) Temporal, Spectral and Cepstral Analysis of Plethysmographic Signal. Application to Automatic Diagnosis of Cardiac Diseases. Signal Processing IV. Thories and Applications. Elsevier Science Publishers B. V., North Holland. [18] Ben Salah, R. and Mansouri, S. (2008) Automatical Diagnosis of Cardiac Diseases by Cepstral Processing of the Bioimpédance Signal. 3rd IEEE International Conference on information and Communication Technologies: From Theory to Applications. Damascuc, 7-11 April 2008, 7-11.
[1] Yan, J.Y., Lu, Y., Liu, J. and Wu, X.Y. (2010) Intelligent Diagnosis of Cardiovascular Diseases Utilizing ECG Signals. International Journal of Information Acquisition, 07, 81.
http://dx.doi.org/10.1142/S0219878910002087 [2] Kumaravel, N., Sridhar, K.S. and Nithiyanandam, N. (1996) Automatic Diagnosis of Heart Diseases Using Neural Network. Biomedical Engineering Conference, Dayton, 29-31 March 1996, 319-322.
http://dx.doi.org/10.1109/SBEC.1996.493214 [3] Hong, B., Kai, J., Ren, Y., Han, J., Zou, Z., Ahn, C.H. and Kang, K.A. (2008) Highly Sensitive Rapid, Reliable, and Automatic Cardiovascular Disease Diagnosis with Nanoparticle Fluorescence Enhancer and Mems. Advances in Experimental Medicine and Biology, 614, 265-273.
http://dx.doi.org/10.1007/978-0-387-74911-2_30 [4] Scherhag, A.W., et al. (2013) Continuous Measurement of Hemodynamic Alterations during Pharmacologic Cardiovascular Stress Using Automated Impedance Cardiography. The Journal of Clinical Pharmacology, 37, 21S-28S. [5] Fortin, J., et al. (2006) Non-Invasive Beat-To-Beat Cardiac Output Monitoring by an Improved Method of Transthoracic Bioimpedance Measurement. Computers in Biology and Medicine, 36, 1185-1203.
http://dx.doi.org/10.1016/j.compbiomed.2005.06.001 [6] Kubicek, W.G., Karnegis, J.N., Patterson, R.P., Witsoe, D.A. and Mattson, R.H. (1966) Development and Evaluation of an Impedance Cardiac Output System. Aerospace Medicine, 37, 1208-1212. [7] Bizouarn, P., Blanloeil, Y. and De La Coussaye, J.E. (1996) Conférences d’actualisation “Méthodes de mesure du débit cardiaque en réanimation”. Elsevier, Paris, et Société Française d’Anesthésie et de Réanimation (SFAR), 377-398. [8] Ben Salah, R. (1988) Pléthysmographie électrique thoracique localisée. Application à la détermination des paramètres cardiovasculaires et au diagnostic des cardiopathies. Ph.D. Faculté des sciences de Tunis. [9] Chemam, M.N. (1983) Analyse automatique des signaux pléthysmographiques. Application à la mesure du débit sanguin et à la reconnaissance des cardiopathies. Ph.D. Dissetation, ENIT, Tunis. [10] Collete, M., Leftheriotis, G. and Humeau, A. (2009) Modeling and Interpretation of the Bioelectrical Impedance Signal for the Determination of the Local Arterial Stiffness. Medical Physics, 36, 4340-4348.
http://dx.doi.org/10.1118/1.3213084 [11] Ivorra, A. (2002) Bioimpédance Monitoring for Physicians: An Overview. Centre Nacional de Microelectrònica, Barcelona, Spain. [12] Kubicek, W.G., Patterson, R.P. and Witsoe, D.A. (1970) Impedance Cardiography as a Non Invasive Method of Monitoring Cardiac Function and Other Parameters of the Cardiovascular System. Annals of the N. Y. Academy of Sciences, 170, 724-732.
http://dx.doi.org/10.1111/j.1749-6632.1970.tb17735.x [13] Mansouri, S., Mahjoubi, H. and Ben Salah, R. (2010) Determination of Instantaneous Arterial Blood Pressure from Bio-Impedance Signal. Journal of Biophysics and Structural Biology, 2, 009-015. [14] Mansouri, S., Mahjoubi, H. and Ben Salah, R. (2009) FPGA-Based Derivative Module for Bioimpedance Signal. International Journal of Computer Science and Network Security, 9, 16-20. [15] Mansouri, S. (2011) Conception d’un système de détermination non invasive des paramètres biorhéologiques cardiovasculaire par la méthode de bioimpédance périphérique. Ph.D. Faculté des sciences de Tunis. [16] Romeder, J.M. (1973) Méthode et programme d’analyse discriminante, Dunod. [17] Ben Salah, R., et al. (1988) Temporal, Spectral and Cepstral Analysis of Plethysmographic Signal. Application to Automatic Diagnosis of Cardiac Diseases. Signal Processing IV. Thories and Applications. Elsevier Science Publishers B. V., North Holland. [18] Ben Salah, R. and Mansouri, S. (2008) Automatical Diagnosis of Cardiac Diseases by Cepstral Processing of the Bioimpédance Signal. 3rd IEEE International Conference on information and Communication Technologies: From Theory to Applications. Damascuc, 7-11 April 2008, 7-11.