Heart energy signature spectrogram for cardiovascular diagnosis

A new method and application is proposed to characterize intensity and pitch of human heart sounds and murmurs. Using recorded heart sounds from the library of one of the authors, a visual map of heart sound energy was established. Both normal and abnormal heart sound recordings were studied. Representation is based on Wigner-Ville joint time-frequency transformations. The proposed methodology separates acoustic contributions of cardiac events simultaneously in pitch, time and energy. The resolution accuracy is superior to any other existing spectrogram method. The characteristic energy signature of the innocent heart murmur in a child with the S3 sound is presented. It allows clear detection of S1, S2 and S3 sounds, S2 split, systolic murmur, and intensity of these components. The original signal, heart sound power change with time, time-averaged frequency, energy density spectra and instantaneous variations of power and frequency/pitch with time, are presented. These data allow full quantitative characterization of heart sounds and murmurs. High accuracy in both time and pitch resolution is demonstrated. Resulting visual images have self-referencing quality, whereby individual features and their changes become immediately obvious.

[1]  J. Mayer,et al.  On the Quantum Correction for Thermodynamic Equilibrium , 1947 .

[2]  G. N. Webb,et al.  SPECTRAL PHONOCARDIOGRAPHIC STUDIES IN CONGENITAL HEART DISEASE , 1956, British heart journal.

[3]  V. Polyshchuk,et al.  New Gear-Fault-Detection Parameter by Use of Joint Time-Frequency Distribution , 2000 .

[4]  Edgar L. Andreas,et al.  Comment on “Time-frequency analysis with the continuous wavelet transform,” by W. Christopher Lang and Kyle Forinash [Am. J. Phys. 66 (9), 794–797 (1998)] , 1999 .

[5]  L. Cohen,et al.  Time-frequency distributions-a review , 1989, Proc. IEEE.

[6]  M. Tavel,et al.  Usefulness of a new sound spectral averaging technique to distinguish an innocent systolic murmur from that of aortic stenosis. , 2005, The American journal of cardiology.

[7]  Martin Reisslein,et al.  Identifying the classical music composition of an unknown performance with wavelet dispersion vector and neural nets , 2006, Inf. Sci..

[8]  C R Thompson,et al.  Comparison of short-time Fourier, wavelet and time-domain analyses of intracardiac sounds. , 1993, Biomedical sciences instrumentation.

[9]  A. R. Freeman,et al.  The Clinical Significance of the Systolic Murmur: A Study of 1000 Consecutive Non-Cardiac Cases , 1933 .

[10]  Abe Ravin,et al.  Auscultation of the Heart , 1967 .

[11]  Charles E McCulloch,et al.  Association between phonocardiographic third and fourth heart sounds and objective measures of left ventricular function. , 2005, JAMA.

[12]  H. Allen,et al.  Digital acoustic analysis of precordial innocent versus ventricular septal defect murmurs in children. , 1997, The American journal of cardiology.

[13]  H Nygaard,et al.  Assessing the severity of aortic valve stenosis by spectral analysis of cardiac murmurs (spectral vibrocardiography). Part II: Clinical aspects. , 1993, The Journal of heart valve disease.

[14]  Leon Cohen.  The Uncertainty Principle for the Short-Time Fourier Transform and Wavelet Transform , 2001 .

[15]  F. Stewart.  BIGGER'S HANDBOOK OF BACTERIOLOGY , 1959, The Ulster Medical Journal.

[16]  Thomas P. Krauss,et al.  Signal processing toolbox for use with MATLAB : ユーザーズガイド , 1994 .

[17]  M J McLaren,et al.  Innocent murmurs and third heart sounds in Black schoolchildren. , 1980, British heart journal.

[18]  Alfred Mertins,et al.  Signal Analysis: Wavelets, Filter Banks, Time-Frequency Transforms and Applications , 1999 .

[19]  Kyle Forinash,et al.  Time-frequency analysis with the continuous wavelet transform , 1998 .

[20]  L. Debnath.  Wavelet Transforms and Time-Frequency Signal Analysis , 2001 .

[21]  V. McKusick,et al.  Spectral phonocardiography. , 1959, American Journal of Cardiology.

[22]  A Pécoud,et al.  Teaching cardiac auscultation to trainees in internal medicine and family practice: Does it work? , 2004, BMC medical education.

[23]  Hao Ling,et al.  Time-Frequency Transforms for Radar Imaging and Signal Analysis , 2002 .

[24]  Charles Tuchinda,et al.  Wavelet processing of systolic murmurs to assist with clinical diagnosis of heart disease. , 2003, Biomedical instrumentation & technology.

[25]  Loren Paul Rees,et al.  Technical Brief: Development and Evaluation of Methods for Structured Recording of Heart Murmur Findings Using SNOMED-CT® Post-Coordination , 2006, J. Am. Medical Informatics Assoc..

[26]  Carl J Pepine,et al.  ACC/AHA guideline update for the management of patients with unstable angina and non-ST-segment elevation myocardial infarction--2002: summary article: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on the Management of Patients , 2002, Circulation.

[27]  J. Hertzberg,et al.  Artificial Neural Network-Based Method of Screening Heart Murmurs in Children , 2001, Circulation.

[28]  B. Tovar-Corona,et al.  Time-frequency representation of systolic murmurs using wavelets , 1998, Computers in Cardiology 1998. Vol. 25 (Cat. No.98CH36292).

[29]  de Ng Dick Bruijn.  A theory of generalized functions, with applications to Wigner distribution and Weyl correspondence , 1973 .

[30]  M. Tavel,et al.  Cardiac Auscultation: A Glorious Past—And It Does Have a Future! , 2006, Circulation.

[31]  J.N. Torry,et al.  Effects of respiration on heart sounds using time-frequency analysis , 2001, Computers in Cardiology 2001. Vol.28 (Cat. No.01CH37287).

[32]  Vivek Nigam,et al.  Accessing heart dynamics to estimate durations of heart sounds , 2005, Physiological measurement.

[33]  S. Mangione.  The teaching of cardiac auscultation during internal medicine and family medicine training--a nationwide comparison. , 1998, Academic medicine : journal of the Association of American Medical Colleges.

[34]  Charles Tuchinda,et al.  Cardiac auscultatory recording database: delivering heart sounds through the Internet , 2001, AMIA.

[35]  T. Claasen,et al.  THE WIGNER DISTRIBUTION - A TOOL FOR TIME-FREQUENCY SIGNAL ANALYSIS , 1980 .

[36]  G. N. Webb,et al.  On Cardiovascular Sound: Further Observations by Means of Spectral Phonocardiography , 1955, Circulation.

[37]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[38]  Carl J Pepine,et al.  ACC/AHA 2002 guideline update for the management of patients with unstable angina and non-ST-segment elevation myocardial infarction--summary article: a report of the American College of Cardiology/American Heart Association task force on practice guidelines (Committee on the Management of Patients , 2002, Journal of the American College of Cardiology.

[39]  J.T.E. McDonnell,et al.  Time-frequency and time-scale techniques for the classification of native and bioprosthetic heart valve sounds , 1998, IEEE Transactions on Biomedical Engineering.

[40]  R. Donnerstein,et al.  Hemodynamic and anatomic factors affecting the frequency content of Still's innocent murmur. , 1994, The American journal of cardiology.

[41]  J. Gray,et al.  Helping family physicians improve their cardiac auscultation skills with an interactive CD‐ROM , 2002, The Journal of continuing education in the health professions.

[42]  D H FOGEL,et al.  The innocent systolic murmur in children: a clinical study of its incidence and characteristics. , 1960, American heart journal.

[43]  Nancy E. Reed,et al.  Heart sound analysis for symptom detection and computer-aided diagnosis , 2004, Simul. Model. Pract. Theory.

[44]  J. Finley,et al.  Assessing Children’s Heart Sounds at a Distance With Digital Recordings , 2006, Pediatrics.

[45]  J. Häggström,et al.  Analysis of murmur intensity, duration and frequency components in dogs with aortic stenosis. , 1998, The Journal of small animal practice.

[46]  A. Messiah.  Quantum Mechanics , 1961 .

[47]  William Feldman,et al.  Accuracy of clinical assessment of heart murmurs by office based (general practice) paediatricians , 1999, Archives of disease in childhood.

[48]  Raimo Sepponen,et al.  How to recognize the innocent vibratory murmur , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[49]  Vivek Nigam,et al.  A dynamic method to estimate the time split between the A2 and P2 components of the S2 heart sound , 2006, Physiological measurement.

[50]  R.N. Bracewell,et al.  Signal analysis , 1978, Proceedings of the IEEE.

[51]  M. Tavel,et al.  Assessment of severity of aortic stenosis through time-frequency analysis of murmur. , 2003, Chest.

[52]  R. Juchems,et al.  [On auscultation of the heart. I]. , 1962, Medizinische Klinik.

[53]  W Frank Peacock,et al.  The combined utility of an S3 heart sound and B-type natriuretic peptide levels in emergency department patients with dyspnea. , 2006, Journal of cardiac failure.

[54]  H. Erb,et al.  Sound signature for identification and quantification of upper airway disease in horses. , 2002, American journal of veterinary research.

[55]  L. Nieman,et al.  Cardiac auscultatory skills of internal medicine and family practice trainees. A comparison of diagnostic proficiency. , 1997, JAMA.