High resolution ECG waveform processor

Claim 1

An apparatus for averaging a plurality of electrocardiographic waveforms having P, Q, R, S, and T-segments to form a means for sampling said plurality of electrocardiographic waveforms periodically and for generating a sequence of input data samples indicating the amplitude of the electrocardiographic waveforms at each sampled time; means for selectively filtering a first frequency spectrum from said input data samples to produce first filtered data samples, said first frequency spectrum corresponding to the major signal frequency components of the QRS-segments of the waveforms;

Claim 2

An apparatus for averaging a plurality of electrocardiographic waveforms having P, Q, R, S, and T-segments to form a means for sampling said plurality of electrocardiographic waveforms periodically and for generating a sequence of input data samples indicating the amplitude of the electrocardiographic waveforms at each sampled time; means for selectively filtering a first frequency spectrum from said input data samples to produce first filtered data samples, said first frequency spectrum corresponding to the major signal frequency components of the QRS-segments of the waveforms;

Claim 14

An apparatus for sampling a plurality of electrocardiographic waveform indicative of corresponding potentials from surface electrodes placed on a living body comprising: means for sampling the plurality of waveforms periodically and for generating data samples indicating the amplitude of the waveforms at each sampled time; said data samples containing parallel sample values for each electrode for each cycle of the sampling period; means for filtering high frequency noise from said data samples such that high frequency signals in excess of one half the sampling rate are attenuated; means for averaging the parallel sample values of each electrode to generate electrode sample values corresponding to a waveform from a single electrode; and means for differencing corresponding electrode sample values to generate a heartbeat waveform representative of an electrocardiographic potential through one axis of the body.

Claim 15

An apparatus for sampling a plurality of electrocardiographic waveform indicative of corresponding potentials from surface electrodes placed on a living body comprising: means for sampling the plurality of waveforms periodically and for generating data samples indicating the amplitude of the waveforms at each sampled time; said data samples containing parallel sample values for each electrode for each cycle of the sampling period; means for filtering high frequency noise from said data samples such that high frequency signals in excess of one half the sampling rate are attenuated; means for averaging the parallel sample values of each electrode to generate electrode sample values corresponding to a waveform from a single electrode; and means for differencing corresponding electrode sample values to generate a heartbeat waveform representative of an electrocardiographic potential through one axis of the body.

Claim 21

A method for averaging a plurality of electrocardiographic heartbeat waveforms, having a QRS-segment and formatted as sucessive digital samples in a data stream, into an average heartbeat representation, said method comprising the steps of: filtering said samples with a first band pass filter having a frequency pass band related to the major signal frequency components of the QRS-segment of an electrocardiographic heartbeat waveform, said first bandpass filter forming a set of detection samples corresponding to each of said digital samples; filtering each of said samples with a second bandpass filter having a frequency pass band related to the major signal frequency components of the QRS complex of an electrocardiographic beat waveform but wider than the pass band of the first bandpass filter, said second bandpass filter forming a set of classification samples corresponding to each of said digital samples; forming a template of template sample values corresponding to said sample values from said detection samples and said classification samples; calculating a ratio for each sample value as the absolute value of the difference between a sample value and the corresponding template sample value divided by the absolute value of the sum of the sample value and the corresponding template sample value; comparing said calculated ratios to determine the minimum ratio; and identifying the digital sample value at which the minimum ratio for a heartbeat waveform occurs.

Claim 22

A method for averaging a plurality of electrocardiographic heartbeat waveforms, having a QRS-segment and formatted as sucessive digital samples in a data stream, into an average heartbeat representation, said method comprising the steps of: filtering said samples with a first band pass filter having a frequency pass band related to the major signal frequency components of the QRS-segment of an electrocardiographic heartbeat waveform, said first bandpass filter forming a set of detection samples corresponding to each of said digital samples; filtering each of said samples with a second bandpass filter having a frequency pass band related to the major signal frequency components of the QRS complex of an electrocardiographic beat waveform but wider than the pass band of the first bandpass filter, said second bandpass filter forming a set of classification samples corresponding to each of said digital samples; forming a template of template sample values corresponding to said sample values from said detection samples and said classification samples; calculating a ratio for each sample value as the absolute value of the difference between a sample value and the corresponding template sample value divided by the absolute value of the sum of the sample value and the corresponding template sample value; comparing said calculated ratios to determine the minimum ratio; and identifying the digital sample value at which the minimum ratio for a heartbeat waveform occurs.

Claim 23

A method for analyzing electrocardiographic signals to determine the level of high frequency energy in the late QRS-segment, comprising the steps of: sampling a plurality of heartbeat waveforms periodically; generating data samples indicating the amplitude of the waveforms at each sample time; selectively filtering a first frequency spectrum from said data samples to produce first filtered data samples, said first frequency spectrum correspnding to the major signal frequency components of the QRS-segments of the waveforms; selectively filtering a second frequency spectrum from said data samples to produce second filtered data samples, wherein said second frequency spectrum has a greater bandwidth than said first frequency spectrum; detecting heartbeat waveforms as a sequence of said data samples with said first filtered data from said generated data samples; classifying said detected heartbeat waveforms as to type with said second filtered data samples; averaging at least one type of said classified heartbeat waveforms into a sequence of data samples forming a composite heartbeat waveform; applying at least a portion of the late QRS-segments of said composite heartbeat sequence in reverse time order to high pass filter means; and determining the level of high frequency energy output from said high pass filter means.

Claim 24

A method for analyzing electrocardiographic signals to determine the level of high frequency energy in the late QRS-segment, comprising the steps of: sampling a plurality of heartbeat waveforms periodically; generating data samples indicating the amplitude of the waveforms at each sample time; selectively filtering a first frequency spectrum from said data samples to produce first filtered data samples, said first frequency spectrum correspnding to the major signal frequency components of the QRS-segments of the waveforms; selectively filtering a second frequency spectrum from said data samples to produce second filtered data samples, wherein said second frequency spectrum has a greater bandwidth than said first frequency spectrum; detecting heartbeat waveforms as a sequence of said data samples with said first filtered data from said generated data samples; classifying said detected heartbeat waveforms as to type with said second filtered data samples; averaging at least one type of said classified heartbeat waveforms into a sequence of data samples forming a composite heartbeat waveform; applying at least a portion of the late QRS-segments of said composite heartbeat sequence in reverse time order to high pass filter means; and determining the level of high frequency energy output from said high pass filter means.