Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166837
C. Zywietz, B. Widiger, T. Penzel
The aim of our study was to investigate whether morphological ECG parameters are changed during sleep disorders, in particular during apnea. We have set up jointly with the sleep laboratory of Marburg University a new database with polysomnographic and simultaneously recorded 12 lead ECG data. Analyses results on single cases and on a data set of 9 patients are presented. They confirm our hypothesis that morphologic ECG parameters vary systematically with apnea phases. While mean values differences seem to be small between regular and apnea respiration, standard deviations of these parameters are marked. From a separate analysis of data for each type of apnea and a joint processing of heart rate variability we expect additional insight into the reasons for the morphologic ECG changes.
{"title":"Polysomnographic sleep recording with simultaneously acquired 12 lead ECGs: a study for detection and validation of apnea related ECG changes","authors":"C. Zywietz, B. Widiger, T. Penzel","doi":"10.1109/CIC.2002.1166837","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166837","url":null,"abstract":"The aim of our study was to investigate whether morphological ECG parameters are changed during sleep disorders, in particular during apnea. We have set up jointly with the sleep laboratory of Marburg University a new database with polysomnographic and simultaneously recorded 12 lead ECG data. Analyses results on single cases and on a data set of 9 patients are presented. They confirm our hypothesis that morphologic ECG parameters vary systematically with apnea phases. While mean values differences seem to be small between regular and apnea respiration, standard deviations of these parameters are marked. From a separate analysis of data for each type of apnea and a joint processing of heart rate variability we expect additional insight into the reasons for the morphologic ECG changes.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"573-576"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166837","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62181878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166846
E. Angelini, D. Hamming, S. Homma, J. Holmes, A. Laine
This paper presents a new methodology for validation of endocardial surface segmentation with real-time three-dimensional (RT3D) ultrasound via analysis of ventricular anatomical shape and deformations. When comparing manual tracing and deformable model segmentation methods, we observe high correlation for volume quantification while 3D shapes show significant differences when directly compared by point matching. In the absence of real three-dimensional ground truth for screening of ventricular anatomy, this study aims to define new tests to compare segmented shapes and analyze their accuracy in the context of wall motion analysis. Endocardial surfaces are fitted with finite element modeling in spheroidal prolate coordinates and analysis is performed via construction of node parameter maps in time. Comparison of parameter maps for healthy volunteers and patients with abnormal wall motion are reported.
{"title":"Comparison of segmentation methods for analysis of endocardial wall motion with real-time three-dimensional ultrasound","authors":"E. Angelini, D. Hamming, S. Homma, J. Holmes, A. Laine","doi":"10.1109/CIC.2002.1166846","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166846","url":null,"abstract":"This paper presents a new methodology for validation of endocardial surface segmentation with real-time three-dimensional (RT3D) ultrasound via analysis of ventricular anatomical shape and deformations. When comparing manual tracing and deformable model segmentation methods, we observe high correlation for volume quantification while 3D shapes show significant differences when directly compared by point matching. In the absence of real three-dimensional ground truth for screening of ventricular anatomy, this study aims to define new tests to compare segmented shapes and analyze their accuracy in the context of wall motion analysis. Endocardial surfaces are fitted with finite element modeling in spheroidal prolate coordinates and analysis is performed via construction of node parameter maps in time. Comparison of parameter maps for healthy volunteers and patients with abnormal wall motion are reported.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"609-612"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166846","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62182017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166699
P. Langley, M. Stridh, J. J. Rieta, L. Sornmo, J. Millet-Roig, A. Murray
One of the greatest challenges in analysis of the atrial rhythm from the ECG is to distinguish the atrial component from the large ventricular components. Our aim was to compare three techniques of atrial rhythm extraction from three groups working on this problem. 12-lead ECG data from 7 patients in atrial fibrillation were analysed. For extraction of the atrial rhythm, spatiotemporal QRST cancellation was performed by the Lund group, blind source separation by the Valencia group, and principal component analysis by the Newcastle group. Peak atrial frequency was determined by Fourier transform of the signal with the largest atrial activity. All algorithms were successful in distinguishing the atrial rhythm from the low frequency ventricular rhythm. The mean (range) atrial frequency was 6.5 (5.9 7.6) Hz (Lund), 6.7 (5.7 - 7.9) Hz (Valencia) and 6.5 (5.9 - 8.2) Hz (Newcastle). There were no significant differences between the atrial frequencies estimated by each of the techniques.
{"title":"Comparison of atrial rhythm extraction techniques for the estimation of the main atrial frequency from the 12-lead electrocardiogram in atrial fibrillation","authors":"P. Langley, M. Stridh, J. J. Rieta, L. Sornmo, J. Millet-Roig, A. Murray","doi":"10.1109/CIC.2002.1166699","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166699","url":null,"abstract":"One of the greatest challenges in analysis of the atrial rhythm from the ECG is to distinguish the atrial component from the large ventricular components. Our aim was to compare three techniques of atrial rhythm extraction from three groups working on this problem. 12-lead ECG data from 7 patients in atrial fibrillation were analysed. For extraction of the atrial rhythm, spatiotemporal QRST cancellation was performed by the Lund group, blind source separation by the Valencia group, and principal component analysis by the Newcastle group. Peak atrial frequency was determined by Fourier transform of the signal with the largest atrial activity. All algorithms were successful in distinguishing the atrial rhythm from the low frequency ventricular rhythm. The mean (range) atrial frequency was 6.5 (5.9 7.6) Hz (Lund), 6.7 (5.7 - 7.9) Hz (Valencia) and 6.5 (5.9 - 8.2) Hz (Newcastle). There were no significant differences between the atrial frequencies estimated by each of the techniques.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"29-32"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166699","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62179539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166702
L. Widesott, L. Bernardi, R. Furlan, L. Diedrich, R. Antolini, G. Nollo, A. Diedrich
The dynamic response to sinusoidal neck suction, of the RR interval, systolic arterial blood pressure and muscle sympathetic nerve activity series, was studied in 10 controls and 5 patients with orthostatic intolerance. By using different spectral techniques (autoregressive, short time Fourier transformation), the cardiovascular and MSNA variability were analyzed during 0.1 Hz and 0.2 Hz frequency of neck suction. Moreover, by using the autoregressive model, a quantitative analysis of particular power spectral frequency bands was done. Finally, a chirp neck suction input signal was applied to qualitatively compare the frequency response. The patients with orthostatic intolerance showed a partial blood pressure response to NS, particularly over 0.1 Hz compared to controls.
{"title":"Cardiovascular response to sinusoidal neck suction in healthy volunteers and orthostatic intolerance patients","authors":"L. Widesott, L. Bernardi, R. Furlan, L. Diedrich, R. Antolini, G. Nollo, A. Diedrich","doi":"10.1109/CIC.2002.1166702","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166702","url":null,"abstract":"The dynamic response to sinusoidal neck suction, of the RR interval, systolic arterial blood pressure and muscle sympathetic nerve activity series, was studied in 10 controls and 5 patients with orthostatic intolerance. By using different spectral techniques (autoregressive, short time Fourier transformation), the cardiovascular and MSNA variability were analyzed during 0.1 Hz and 0.2 Hz frequency of neck suction. Moreover, by using the autoregressive model, a quantitative analysis of particular power spectral frequency bands was done. Finally, a chirp neck suction input signal was applied to qualitatively compare the frequency response. The patients with orthostatic intolerance showed a partial blood pressure response to NS, particularly over 0.1 Hz compared to controls.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"41-44"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166702","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62179691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166719
P. Brathwaite, A. Nagaraj, B. Kane, D. McPherson, E. Dove
Our goal was to develop an automatic classification algorithm to differentiate between four common lesion types in atherosclerotic (AS) arteries: calcific (CAL), fibro-calcific (FBC), fibrous (FBR), and fibro-fatty (FBF). AS was induced in eight Yucatan miniswine. 22 femoral or carotid arteries were imaged with intravascular ultrasound using a pull-back procedure. Both 2D and 3D texture measures were used, followed by a principal components analysis to reduce dimension. The classifiers were applied to the test dataset, and the results were compared with two independent experts. There was no difference between the 2D and 3D classification of the CA and E1, and of the CA and E2 (ANOVA, F = 2.00). The difference between CA and E1 (or E2) was not larger than the difference between E1 and E2 for any lesion type (ANOVA, F = 0.76). We conclude that using 3D information in the classification scheme improved the algorithm's ability to correctly classify lesion type.
{"title":"Automatic classification and differentiation of atherosclerotic lesions in swine using IVUS and texture features","authors":"P. Brathwaite, A. Nagaraj, B. Kane, D. McPherson, E. Dove","doi":"10.1109/CIC.2002.1166719","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166719","url":null,"abstract":"Our goal was to develop an automatic classification algorithm to differentiate between four common lesion types in atherosclerotic (AS) arteries: calcific (CAL), fibro-calcific (FBC), fibrous (FBR), and fibro-fatty (FBF). AS was induced in eight Yucatan miniswine. 22 femoral or carotid arteries were imaged with intravascular ultrasound using a pull-back procedure. Both 2D and 3D texture measures were used, followed by a principal components analysis to reduce dimension. The classifiers were applied to the test dataset, and the results were compared with two independent experts. There was no difference between the 2D and 3D classification of the CA and E1, and of the CA and E2 (ANOVA, F = 2.00). The difference between CA and E1 (or E2) was not larger than the difference between E1 and E2 for any lesion type (ANOVA, F = 0.76). We conclude that using 3D information in the classification scheme improved the algorithm's ability to correctly classify lesion type.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"109-112"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166719","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62179939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166720
J. Klingensmith, A. Nair, B. Kuban, D. Vince
Intravascular ultrasound provides precise tomographic assessment of coronary artery disease, allowing unique potential for analysis of both plaque geometry and composition, two critical factors related to the likelihood of plaque rupture. A novel three-dimensional segmentation technique and spectral analysis are used to create a unique tool for volumetric assessment of plaque composition. The semi-automated 3D segmentation technique was used to identify luminal and medial-adventitial borders in ECG-gated images created from radiofrequency (RF) IVUS data acquired during automated pullbacks in patients. Spectral analysis was applied to the RF data within the segmented plaque. Color-coded pseudo-histology images were created from these plaque component predictions using statistical classification trees. Quantitative analysis and visualization techniques were used to assess volumetric plaque composition and provide a unique tool for evaluation of plaque vulnerability.
{"title":"Volumetric coronary plaque composition using intravascular ultrasound: three-dimensional segmentation and spectral analysis","authors":"J. Klingensmith, A. Nair, B. Kuban, D. Vince","doi":"10.1109/CIC.2002.1166720","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166720","url":null,"abstract":"Intravascular ultrasound provides precise tomographic assessment of coronary artery disease, allowing unique potential for analysis of both plaque geometry and composition, two critical factors related to the likelihood of plaque rupture. A novel three-dimensional segmentation technique and spectral analysis are used to create a unique tool for volumetric assessment of plaque composition. The semi-automated 3D segmentation technique was used to identify luminal and medial-adventitial borders in ECG-gated images created from radiofrequency (RF) IVUS data acquired during automated pullbacks in patients. Spectral analysis was applied to the RF data within the segmented plaque. Color-coded pseudo-histology images were created from these plaque component predictions using statistical classification trees. Quantitative analysis and visualization techniques were used to assess volumetric plaque composition and provide a unique tool for evaluation of plaque vulnerability.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"113-116"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166720","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62179956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166730
S. Mohammad, A. Sureka, D.R. Ely, J. Jenkins
A Visual Software Development Framework (VSDF) has been created to facilitate the software coding process of biological signal analysis. A special purpose graphical user interface (GUI) was developed using VSDF for automating the analysis and classification of waveforms in electrocardiographic (ECG) data. Graphing capabilities were included in the program to allow the user to plot the signal as well as trigger location. Object Oriented Programming (OOP) techniques were used in the Java programming language to calculate correlation coefficients between a template QRS complex and detected QRS complexes throughout an ECG recording. The OOP techniques employed in the development of the software package allow visualization of the entire analysis process. The ECG signal, read from a file, is stored into a simple array data structure and is passed to each of the modules. The signals and systems approach allows incorporation of trigger modules, data conversion modules, and numerical analysis modules directly into the software package, providing ease of software design.
{"title":"A signals and systems and object oriented programming approach to development of ECG analysis software","authors":"S. Mohammad, A. Sureka, D.R. Ely, J. Jenkins","doi":"10.1109/CIC.2002.1166730","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166730","url":null,"abstract":"A Visual Software Development Framework (VSDF) has been created to facilitate the software coding process of biological signal analysis. A special purpose graphical user interface (GUI) was developed using VSDF for automating the analysis and classification of waveforms in electrocardiographic (ECG) data. Graphing capabilities were included in the program to allow the user to plot the signal as well as trigger location. Object Oriented Programming (OOP) techniques were used in the Java programming language to calculate correlation coefficients between a template QRS complex and detected QRS complexes throughout an ECG recording. The OOP techniques employed in the development of the software package allow visualization of the entire analysis process. The ECG signal, read from a file, is stored into a simple array data structure and is passed to each of the modules. The signals and systems approach allows incorporation of trigger modules, data conversion modules, and numerical analysis modules directly into the software package, providing ease of software design.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"153-156"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166730","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62180272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166747
R. Povinelli, F. M. Roberts, Michael T. Johnson, K. Ropella
A novel, nonlinear, phase space based method to quickly and accurately identify life-threatening arrhythmias is proposed. The accuracy of the proposed method in identifying sinus rhythm (SR), monomorphic ventricular tachycardia (MVT), polymorphic VT (PVT), and ventricular fibrillation (VF) for signals of at least 0.5 s duration was determined for six different ECG signal lengths. The ECG recordings were transformed into a phase space, and statistical features of the resulting attractors were learned using artificial neural networks. Classification accuracies for SR, MVT, PVT and VF were 93-96, 95-100, 79-91, and 81-88%, respectively. As expected, classification accuracy for the proposed method was essentially equivalent for ECG signals longer than 1 s. Surprisingly, classification accuracy for this new method did not degrade for 0.5 s ECG signals, indicating that even such short duration signals contain structures predictive of rhythm type. The phase space method's classification accuracy was higher for all segment durations compared to two other methods.
{"title":"Are nonlinear ventricular arrhythmia characteristics lost, as signal duration decreases?","authors":"R. Povinelli, F. M. Roberts, Michael T. Johnson, K. Ropella","doi":"10.1109/CIC.2002.1166747","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166747","url":null,"abstract":"A novel, nonlinear, phase space based method to quickly and accurately identify life-threatening arrhythmias is proposed. The accuracy of the proposed method in identifying sinus rhythm (SR), monomorphic ventricular tachycardia (MVT), polymorphic VT (PVT), and ventricular fibrillation (VF) for signals of at least 0.5 s duration was determined for six different ECG signal lengths. The ECG recordings were transformed into a phase space, and statistical features of the resulting attractors were learned using artificial neural networks. Classification accuracies for SR, MVT, PVT and VF were 93-96, 95-100, 79-91, and 81-88%, respectively. As expected, classification accuracy for the proposed method was essentially equivalent for ECG signals longer than 1 s. Surprisingly, classification accuracy for this new method did not degrade for 0.5 s ECG signals, indicating that even such short duration signals contain structures predictive of rhythm type. The phase space method's classification accuracy was higher for all segment durations compared to two other methods.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"87 1","pages":"221-224"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166747","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62180354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166734
A. Ripoli, M. Emdin, C. Passino, L. Zyw
The analysis of time series measured from nonlinear signals, may be performed either in the phase space or in the tie-domain. The Largest Lyapunov Exponent (LLE) characterises exponential divergence of trajectories in the phase space; fractal analysis is able to describe the complex pattern of a given time series. To evaluate the relation between the dynamic behavior and pattern complexity of the inherent biological system, RR-interval sequences were derived from 24-hour Holter recordings performed in 55 healthy subjects (37/spl plusmn/4 years, 34 males). Pattern fractal analysis (PFD) was computed on the basis of the measured length and diameter of the signal pattern. and LLE was evaluated by the Wolf algorithm. For each subject, the linear regression between computed PFD and LLE measures over the 24-hour period has been computed, extracting the correlation coefficient and the slope of the PFD vs. LLE relation. The strongest linear correlation between LLE and PFD indicates a light link between the system dynamics and the pattern of the extracted signals. This link suggests the possibility of a direct evaluation of nonlinear dynamics, even over short time intervals, exploiting the computationally less expensive PFD.
{"title":"Pattern complexity and nonlinear dynamics in RR-sequences","authors":"A. Ripoli, M. Emdin, C. Passino, L. Zyw","doi":"10.1109/CIC.2002.1166734","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166734","url":null,"abstract":"The analysis of time series measured from nonlinear signals, may be performed either in the phase space or in the tie-domain. The Largest Lyapunov Exponent (LLE) characterises exponential divergence of trajectories in the phase space; fractal analysis is able to describe the complex pattern of a given time series. To evaluate the relation between the dynamic behavior and pattern complexity of the inherent biological system, RR-interval sequences were derived from 24-hour Holter recordings performed in 55 healthy subjects (37/spl plusmn/4 years, 34 males). Pattern fractal analysis (PFD) was computed on the basis of the measured length and diameter of the signal pattern. and LLE was evaluated by the Wolf algorithm. For each subject, the linear regression between computed PFD and LLE measures over the 24-hour period has been computed, extracting the correlation coefficient and the slope of the PFD vs. LLE relation. The strongest linear correlation between LLE and PFD indicates a light link between the system dynamics and the pattern of the extracted signals. This link suggests the possibility of a direct evaluation of nonlinear dynamics, even over short time intervals, exploiting the computationally less expensive PFD.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"169-172"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166734","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62180401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-09-22DOI: 10.1109/CIC.2002.1166735
H. Carvalho, L. F. Junqueira, J. Souza-Neto
The interest in the study of the Autonomic Nervous System has grown in the last years, mainly because of its important participation in the cardiovascular regulation and in many pathophysiological processes like heart failure, arrhythmias and sudden death. A great variety of tests have been employed for the functional evaluation of the Cardiovascular Autonomic Nervous System. However, the existence of variables with non-linear characteristics has made difficult the analysis of the responses. Based on this fact and considering that the Fuzzy Logic has been actually used with success in the development of classifier and analysis of control systems, its use in the investigation of the Cardiovascular Autonomic Function seems to be justified and a promise. The present paper describes the development of a system based on fuzzy logic to evaluate simultaneous cardiovascular autonomic tests results.
{"title":"A computerized fuzzy logic system for evaluation of the cardiovascular autonomic function based on multiple functional tests","authors":"H. Carvalho, L. F. Junqueira, J. Souza-Neto","doi":"10.1109/CIC.2002.1166735","DOIUrl":"https://doi.org/10.1109/CIC.2002.1166735","url":null,"abstract":"The interest in the study of the Autonomic Nervous System has grown in the last years, mainly because of its important participation in the cardiovascular regulation and in many pathophysiological processes like heart failure, arrhythmias and sudden death. A great variety of tests have been employed for the functional evaluation of the Cardiovascular Autonomic Nervous System. However, the existence of variables with non-linear characteristics has made difficult the analysis of the responses. Based on this fact and considering that the Fuzzy Logic has been actually used with success in the development of classifier and analysis of control systems, its use in the investigation of the Cardiovascular Autonomic Function seems to be justified and a promise. The present paper describes the development of a system based on fuzzy logic to evaluate simultaneous cardiovascular autonomic tests results.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"173-176"},"PeriodicalIF":0.0,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166735","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62180469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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