Peak Recognition in Waveforms

A new system of peak component recognition and measurement in digitized waveforms is detailed. Two input parameters identify waveform context (scale and noise content), and a third specifies baseline tolerance (if applicable). The input waveform is preprocessed by a discrete linear piecewise approximation algorithm yielding a segmentation in endpoint/slope/constant format. Slope values are encoded as symbols of a string which is parsed by a syntax-directed finite-state automaton. One of three different machines and sets of semantic routines is chosen depending upon whether the waveform is baseline-free, unipolar, or bipolar. In the last case, the endpoint values relative to the baseline are encoded as symbols of a second string which modifies the action of the machine. An electrocardiogram is employed as an example waveform to demonstrate the bipolar algorithm, which runs with sufficient speed to allow real-time processing. A proposed on-line implementation of the system is outlined.

[1]  King-Sun Fu,et al.  Syntactic Methods in Pattern Recognition , 1974, IEEE Transactions on Systems, Man, and Cybernetics.

[2]  S J Hengeveld,et al.  Computer detection of P-waves. , 1976, Computers and biomedical research, an international journal.

[3]  R. Stacy,et al.  Computers in biomedical research , 1967 .

[4]  K Obayashi,et al.  Automatic ECG and arrhythmia interpreter--an almost analog device. , 1973, Journal of electrocardiology.

[5]  Steven L. Horowitz,et al.  A syntactic algorithm for peak detection in waveforms with applications to cardiography , 1975, Commun. ACM.

[6]  H B Boom,et al.  On-line processing of orthogonal exercise electrocardiograms. , 1975, Computers and biomedical research, an international journal.

[7]  W Gersch.  A note on trapezoidal digital filter design. , 1973, Computers and biomedical research, an international journal.

[8]  irwin Guttman,et al.  Introductory Engineering Statistics , 1965 .

[9]  M Serafini,et al.  A pattern recognition method applied to EEG analysis. , 1973, Computers and biomedical research, an international journal.

[10]  R E Bonner,et al.  Computer diagnosis of electrocardiograms. II. A computer program for EKG measurements. , 1968, Computers and biomedical research, an international journal.

[11]  A. Grandage.  Introductory Engineering Statistics, 2nd edition , 1972 .

[12]  R H Swatzell,et al.  The on-line computer system for determining the systolic time intervals. , 1973, Computers and biomedical research, an international journal.

[13]  Alfred V. Aho,et al.  The Theory of Parsing, Translation, and Compiling , 1972 .

[14]  I Tomek.  Two quantitative measures of similarity of one class of waveforms. , 1973, Computers and biomedical research, an international journal.

[15]  J. Rice.  The approximation of functions , 1964 .

[16]  Earl E. Swartzlander,et al.  Introduction to Mathematical Techniques in Pattern Recognition , 1973 .

[17]  J. R. Cox,et al.  Digital analysis of the electroencephalogram, the blood pressure wave, and the electrocardiogram , 1972 .

[18]  J. E. Albus.  Electrocardiogram Interpretation Using a Stochastic Finite State Model , 1977 .

[19]  J L Willems,et al.  Arrhythmia detection by digital computer. , 1972, Computers and biomedical research, an international journal.

[20]  Tzay Y. Young,et al.  Classification, Estimation and Pattern Recognition , 1974 .

[21]  Kenneth Steiglitz,et al.  An introduction to discrete systems , 1974 .

[22]  T A Pryor.  A note on filtering electrocardiograms. , 1971, Computers and biomedical research, an international journal.

[23]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.