System, software, and method for detection of sleep-disordered breathing using an electrocardiogram

A method for detecting sleep-disordered breathing, the method comprising:

• (a) detecting a position of a plurality of QRS complex pulses within an electrocardiogram signal;
• (b) determining a plurality of QRS complex pulse area values for a preselected time band coincident with a position of a corresponding plurality of R-wave peaks for the plurality of QRS complex pulses, variations in the area for each of the plurality of QRS complex pulse areas defining QRS complex pulse area morphology for the plurality of QRS complex pulses;
• (c) forming a QRS complex pulse area value sampled time series by interpolating between consecutive QRS complex pulse area values of the electrocardiogram signal to form a QRS complex pulse area value trend and by evenly sampling the formed QRS complex pulse area value trend;
• and
• (d) analyzing the QRS complex pulse area morphology for the plurality of QRS complex pulses by determining a power spectral density of the QRS complex pulse area value sampled time series and determining a power level in a preselected frequency band of the power spectral density.

A system to detect sleep-disordered breathing, the apparatus comprising:

• an apparatus to form and store an electrocardiogram signal from a cardiac electrical signal, the apparatus including:
• at least one electrocardiogram lead having a pair of the electrodes adapted to connect to a selected portion of a patient to detect the cardiac electrical signal, the signal having a plurality of QRS complex pulses,
• a data sampler electrically connected to the at least one electrocardiogram lead to form the electrocardiogram signal by sampling the detected cardiac electrical signal,
• a data storage device for storing the electrocardiogram signal;
• a computer having a processor and a memory associated therewith, the processor positioned to communicate with the data storage device and the memory;
• and
• R-wave peak amplitude morphology analyzing software stored in the memory of the computer for analyzing R-wave peak amplitude morphology of a plurality of R-waves peaks contained within the electrocardiogram signal, the R-wave peak amplitude morphology analyzing software including:
• an R-wave peak amplitude determiner, adapted to receive the electrocardiogram signal, to determine a position and magnitude of the plurality of R-wave peaks within the electrocardiogram signal, variations in the magnitude of the plurality of R-wave peak amplitudes defining R-wave peak amplitude morphology for the plurality of R-wave peaks, and
• an R-wave peak amplitude morphology analyzer, responsive to the R-wave peak amplitude determiner, to detect sleep-disordered breathing from the R-wave peak amplitude morphology.

A computer readable medium that is readable by a computer facilitating detecting sleep disordered breathing in a patient, the computer readable medium comprising a set of instructions that, when executed by the computer, cause the computer to perform the following operations:

• detect a position and magnitude of a plurality of R-wave peak amplitudes within at least a portion of an electrocardiogram signal;
• form a R-wave peak sampled time series by forming an R-wave peak value trend and sampling the formed trend;
• determine a power spectral density of the R-wave peak sampled time series;
• determine a power level in a preselected frequency band of the power spectral density;
• and
• compare the determined power level to a predetermined threshold level.

A computer readable medium that is readable by a computer facilitating detecting sleep disordered breathing in a patient, the computer readable medium comprising a set of instructions that, when executed by the computer, cause the computer to perform the following operations:

• divide an electrocardiogram signal into a first plurality of epochs;
• form an R-wave peak time series for each epoch in a subset of the first plurality of epochs defining a second plurality of epochs by forming an R-wave peak value trend and sampling the formed trend;
• determine a power spectral density of the R-wave peak time series for each of the second plurality of epochs;
• determine a power level in a preselected frequency band of the power spectral density for each of the second plurality of epochs;
• compare the determined power level for each of the second plurality of epochs to a predetermined threshold level to determine if the predetermined threshold is exceeded;
• and
• signal the existence of sleep-disordered breathing when a preselected percentage of second plurality of epochs exceed the predetermined threshold level.