Biancamed Limited

Pacesetter, Inc.

Philip De Chazal

Conor Joseph Heneghan

Elaine Sheridan

Gene A Bornzin

Rupinder Bharmi

Michael E Benser

An apparatus for diagnosing sleep apnea only uses an electrocardiogram signal and a computer processor and associated computer code that are configured to analyze the electrocardiogram signal and classify each time period of the electrocardiogram signal as either apneic or normal. A diagnostic measure of sleep apnea for the human patient is provided based on classification results obtained by combining a results for various electrocardiogram signal time periods. A computer-readable medium has computer code that causes the computer to analyze an electrocardiogram signal relating to the human patient and classify each time period in a set of time periods as either apneic or normal. A diagnostic measure of sleep apnea is provided based on classification results obtained by combining a plurality of results from the set of time periods using either time or frequency domain processing, or both.

Apparatus for detecting sleep apnea using electrocardiogram signals

Techniques are provided for detecting abnormal respiration within a patient based upon intracardiac electrogram (IEGM) signals or other electrical cardiac signals. Briefly, abnormal respiration is detected using a pattern recognition trained to discriminate normal and abnormal respiration based on morphological parameters and interval-based parameters extracted from the IEGM signals. In addition, techniques are described for distinguishing among different cardiac rhythm types within the patient while using one or more pattern classifiers or other pattern recognition devices.

System and method for detecting abnormal respiration based on intracardiac electrogram signals using a pattern recognition device

There is provided a method of determining a diagnostic measure of sleep apnea including the following steps: acquiring an electrocardiogram signal, calculating a set of RR intervals and electrocardiogram-derived respiratory signal from said electrocardiogram, and hence calculating a set of spectral and time-domain measurements over time periods including power spectral density, mean, and standard deviation. These measurements are processed by a classifier model which has been trained on a pre-existing data base of electrocardiogram signals to provide a probability of a specific time period containing apneic episodes or otherwise. These probabilities can be combined to form an overall diagnostic measure. The system also provides a system and apparatus for providing a diagnostic measure of sleep apnea.

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Sutton, Australia

Philip De Chazal