Abstract: A math model envelope of a single heartbeat between primary and secondary peaks of an autocorrelation of a received cardiovascular sound signal comprises an S1 lobe and a like-polarity S2 lobe. A bootstrap filter envelope is generated by averaging data from a plurality of heart cycles within heart cycle boundaries located responsive to a convolution of the envelope with the cardiovascular sound signal. Start points of a plurality of heart cycle signals are located from a convolution of the bootstrap filter envelope with the cardiovascular sound signal. The S1 and S2 regions are located within a cardiovascular sound signal responsive to peak and valley locations thereof and responsive to a phase window signal generated by filtering an average of a plurality of heart cycle signals, wherein the peak and valley locations are located responsive to a second derivative of the phase window signal and responsive to the start points.

Abstract: A math model envelope of a single heartbeat between primary and secondary peaks of an autocorrelation of a received cardiovascular sound signal comprises an S1 lobe and a like-polarity S2 lobe. A bootstrap filter envelope is generated by averaging data from a plurality of heart cycles within heart cycle boundaries located responsive to a convolution of the envelope with the cardiovascular sound signal. Start points of a plurality of heart cycle signals are located from a convolution of the bootstrap filter envelope with the cardiovascular sound signal. The S1 and S2 regions are located within a cardiovascular sound signal responsive to peak and valley locations thereof and responsive to a phase window signal generated by filtering an average of a plurality of heart cycle signals, wherein the peak and valley locations are located responsive to a second derivative of the phase window signal and responsive to the start points.

Abstract: Each spectral slice array of a plurality is generated for each time segment of a plurality of time segments of a cardiovascular sound signal is convolved with a local spectral averaging window to generate a local spectral average array that is searched for bruit candidates responsive to associated time power or energy values, power levels, and skew values, so as to provide an indication of cardiovascular disease, that may also be responsive to skew-responsive and power-level-responsive probability terms and to a composite thereof. A probability indicator of cardiovascular disease is responsive to a second product of second terms, each second term responsive to a first product of first terms, each first term representative of a probability of no bruits for all time segments for each frequency segment of a two dimensional bruit candidate probability array, each second term representative of a probability of no repetitive bruits within each frequency segment.

Abstract: Each spectral slice array of a plurality is generated for each time segment of a plurality of time segments of a cardiovascular sound signal is convolved with a local spectral averaging window to generate a local spectral average array that is searched for bruit candidates responsive to associated time power or energy values, power levels, and skew values, so as to provide an indication of cardiovascular disease, that may also be responsive to skew-responsive and power-level-responsive probability terms and to a composite thereof. A probability indicator of cardiovascular disease is responsive to a second product of second terms, each second term responsive to a first product of first terms, each first term representative of a probability of no bruits for all time segments for each frequency segment of a two dimensional bruit candidate probability array, each second term representative of a probability of no repetitive bruits within each frequency segment.

Abstract: A system, method and computer executable code for generating a likelihood of cardiovascular disease from acquired cardiovascular sound signals is disclosed, where the generated likelihood of cardiovascular disease is based at least on an overlapping in time of bruit candidates in one heart cycle or in different heart cycles. Also disclosed is a system, method, and computer executable code for collecting, forwarding, and analyzing cardiovascular sound signals, where the collecting and analyzing may occur at locations that are remote from each other. Further disclosed is a system, method, and computer executable code for determining the time and phase information contained in cardiovascular sound signals, for use in analyzing those cardiovascular sound signals.

Abstract: A method and system for modeling cardiovascular disease using a probability regression model is provided. A parameter estimate of a probability regression model for cardiovascular disease can be generated using predictors derived from cardiovascular sound signals and disease status information. A probability of cardiovascular disease can be generated using a probability regression model that includes a predictor derived from cardiovascular sound signals.

Abstract: A system, method, and computer executable code for generating a likelihood of cardiovascular disease from acquired cardiovascular sound signals is diesclosed, where the generated likelihood of cardiovascular disease is based at least on an overlapping in time of bruit candidates in one heart cycle or in different heart cycles. Also disclosed is a system, method, and computer executable code for collecting, forwarding, and analyzing cardiovascular sound signals, where the collecting and analyzing may occur at locations that are remote from each other. Further disclosed is a system, method, and computer executable code for determining the time and phase information contained in cardiovascular sound signals, for use in analyzing those cardiovascular sound signals.