Method for detecting Cheyne-Stokes respiration in patients with congestive heart failure

• US 6,839,581 B1
• Filed: 01/17/2003
• Issued: 01/04/2005
• Est. Priority Date: 04/10/2000
• Status: Expired due to Fees

• Current Assignee: US Department of Veterans Affairs (Government of the United States of America)
• Original Assignee: The Research Foundation for The State University of New York (State University of New York)
• Inventors: Grant, Brydon, El-Solh, Ali
• Primary Examiner(s): Winakur, Eric F.
• Assistant Examiner(s): KREMER, MATTHEW J
• Application Number:
  US10/347,555
• Time in Patent Office: 718 Days
• Field of Search: 600322-324, 600/310, 600/331, 600/529, 128/925
• US Class Current: 600/324
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

The present invention provides a diagnostic tool for detection of Cheyne-Stokes Respiration (CSR). This invention also provides a method for development of the diagnostic tool. The method comprises the steps of performing overnight oximetry recordings in patients suspected of sleep disordered breathing. Spectral analysis is performed on the oximetry recordings to obtain a set of parameters which can be used in the construction of a classification tree and a trained neural network. The diagnostic tools of the present invention can be used for classification of a patient as having CSR or obstructive sleep apnea.

Claims

1. A method for detecting Cheyne-Stokes respiration in an individual comprising:

obtaining pulse oximetry recordings from the individual;

determining oxygen saturation levels at selected intervals;

generating a power spectrum from the oxygen saturation levels;

determining a set of parameters from the power spectrum and the oximetry readings, wherein the set of parameters comprises a delta index; and

inputting the set of parameters into a trained neural network to classify an individual as having Cheyne-Stokes respiration, obstructive sleep apnea or no sleep disordered breathing.

2. The method of claim 1, wherein the pulse oximetry readings are obtained overnight.

3. The method of claim 1, wherein the set of parameters from the power spectrum comprise frequency and magnitude of highest and second highest peaks at local maximas.

4. A storage device having stored thereon computer readable code for causing a computer to execute the method of claim 1.

5. The storage device of claim 4, selected from the group consisting of a floppy disk, a hard drive, a compact disc and a zip drive.

6. A method for developing a trained neural network for classification of an individual as having CSR, OSA or no sleep breathing disorder comprising the steps of:

performing clinical studies to identify patients as having Cheyne-Stokes respiration, obstructive sleep apnea or no sleep breathing disorders;

obtaining overnight pulse oximetry recordings from the patients;

generating power spectra from the oxygen saturation levels;

determining a set of parameters from the power spectra and from the pulse oximetry readings;

analyzing the parameters to obtain relationships between the parameters;

expressing the relationships mathematically; and

exposing the mathematical relationships to a training set and adjusting the mathematical relationships to produce a desired effect.

7. The method of claim 6 further comprising the step of cross-validating the trained neural network.

8. The method of claim 6, wherein the clinical studies are polysomnography studies.