Sleep state classification

• US 8,600,502 B2
• Filed: 06/05/2012
• Issued: 12/03/2013
• Est. Priority Date: 08/18/2003
• Status: Expired due to Fees

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Lovett, Eric G., Sweeney, Robert J., KenKnight, Bruce H.
• Primary Examiner(s): Szmal, Brian
• Assistant Examiner(s): NGUYEN, HUONG Q
• Application Number:
  US13/488,962
• Publication Number:
  US 20120245437A1
• Time in Patent Office: 546 Days
• Field of Search: 600/546, 600/586, 600/595, 600/587
• US Class Current: 607/18
• CPC Class Codes: A61B 2560/0468 Built-in electrodes
• CPC Class Codes: A61B 5/00 Measuring for diagnostic purposes radiation diagnosis A61B6/00; diagnosis by ultrasonic, sonic or infrasonic waves A61B8/00; Identification of persons
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1135 by monitoring thoracic expansion
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/398 Electrooculography [EOG], e.g. detecting nystagmus; Electroretinography [ERG]
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Systems and methods for sleep state classification involve detecting conditions related to sleep, including at least one condition associated with rapid eye movement (REM) sleep. Additionally, a condition modulated by the sleep-wake status of the patient may be detected. A medical system that is partially or fully implantable incorporates sensors and circuitry for detecting and processing the sleep-related signals. A sleep state processor classifies the patient'"'"'s sleep state based on the sleep-related signals. Sleep state classification may be used in connection with the delivery of sleep state appropriate therapy, diagnostic testing, or patient monitoring.

Claims

1. A method of providing therapy to a patient, comprising:

identifying a sleep-wake status of the patient;

sensing pectoral muscle tone using a sensor of an implantable stimulation device implanted in a pectoral region;

detecting REM sleep status based on the pectoral muscle tone;

classifying one or more sleep states based on the sleep-wake status and the REM sleep status, wherein the classifying, the detecting the sleep-wake status, and the detecting REM sleep status are performed at least in part implantably; and

providing at least one of sleep state informed monitoring, diagnostics and therapy to the patient using the sleep state classification.

2. The method of claim 1, wherein sensing the muscle tone comprises sensing the muscle tone using a strain gauge sensor or a mechanical force sensor.

3. The method of claim 1, wherein sensing the muscle tone includes sensing the muscle tone using a sensor on a housing of the implantable stimulation device.

4. The method of claim 1, wherein sensing the muscle tone includes sensing the muscle tone using a sensor on a lead system of the implantable stimulation device.

5. The method of claim 1, wherein detecting the condition associated with the sleep-wake status of the patient comprises detecting patient activity.

6. The method of claim 5, wherein detecting patient activity comprises detecting patient activity using a respiration sensor.

7. The method of claim 1, wherein classifying the one or more sleep states comprises adaptively classifying the one or more sleep states.

8. The method of claim 7, wherein adaptively classifying the one or more sleep states comprises:

learning sleep-related responses of a patient; and

classifying the one or more sleep states using the learned sleep-related responses.

9. The method of claim 8, wherein learning the sleep-related responses comprises:

detecting changes in the sleep-related signals over a period of time; and

learning the sleep-related responses based on the detected changes.

10. The method of claim 1 further comprising, sensing cardiac signals and providing at least one of sleep state informed monitoring, diagnostics and therapy to the patient using the sleep state classification and the cardiac signals.

11. A medical system, comprising:

a detector system comprising a first and second sensor, the first sensor coupled to an implantable medical device, the first sensor configured to sense muscle tone in the pectoral region of the patient and to detect REM sleep status based on the pectoral muscle tone, and the second sensor configured to detect sleep-wake status of the patient;

a classification system coupled to the detector system and configured to classify sleep state based on the REM sleep status and the sleep-wake status; and

the implantable medical device coupled to the classification system and configured to provide at least one of sleep state informed monitoring, diagnostics and therapy to the patient using the sleep state classification.

12. The system of claim 11, wherein the first sensor is a strain gauge sensor or a mechanical force sensor.

13. The system of claim 11, wherein the first sensor is mechanically coupled to a lead system of the implantable medical device.

14. The system of claim 11, wherein the second sensor comprises a patient activity sensor.

15. The system of claim 11, wherein the second sensor comprises a respiration sensor.

16. The system of claim 11, wherein the classification system is configured to adaptively classify the one or more sleep states.

17. The system of claim 11, wherein the classification system is configured to learn sleep-related responses of a patient and classify the one or more sleep states using the learned sleep-related responses.

18. The system of claim 11, wherein the implantable medical device is configured to provide respiratory therapy.

19. A medical system, comprising:

a detector system comprising a first, a second, and a third sensor, the first sensor coupled to an implantable stimulation device, the first sensor configured to sense muscle tone in the pectoral region of the patient and to detect REM sleep status based on the pectoral muscle tone, the second sensor configured to detect a sleep-wake status of the patient, and the third sensor configured to detect cardiac signals;

a classification system coupled to the detector system and configured to classify sleep state based on the REM sleep status and the sleep-wake status; and

the implantable stimulation device coupled to the classification system and configured to provide at least one of sleep state informed monitoring, diagnostics and therapy to the patient using the sleep state classification and the cardiac signals.

20. The system of claim 19, wherein the third sensor is configured to detect cardiac signals on a beat-to-beat basis.