System for the assessment of sleep quality in adults and children

• US 8,355,769 B2
• Filed: 03/17/2010
• Issued: 01/15/2013
• Est. Priority Date: 03/17/2009
• Status: Active Grant

• Current Assignee: Advanced Brain Monitoring
• Original Assignee: Advanced Brain Monitoring
• Inventors: Levendowski, Daniel J., Westbrook, Philip R., Berka, Chris, Popovic, Djordje, Zavora, Timothy, Davis, Gene, Mitrovic, Mirko, Veljkovic, Bratislav
• Primary Examiner(s): Cohen, Lee S
• Application Number:
  US12/726,084
• Publication Number:
  US 20100240982A1
• Time in Patent Office: 1,035 Days
• Field of Search: 600/301, 600/383, 600/393, 600/544, 600/546
• US Class Current: 600/383
• CPC Class Codes: A61B 5/087 Measuring breath flow
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/398 Electrooculography [EOG], e.g. detecting nystagmus; Electroretinography [ERG]
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/4815 Sleep quality
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/6803 Head-worn items, e.g. helmets, masks, headphones or goggles
• CPC Class Codes: A61B 5/6814 Head
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: A61B 5/721 using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor

Abstract

Systems and methods for assessment of sleep quality in adults and children are provided. These techniques include an apparatus worn above the forehead containing the circuitry for collecting and storing physiological signals. The apparatus integrates with a sensor strip and a nasal mask to obtain the physiological signals for the user. The form factor of this apparatus is comfortable, easy to self-apply, and results in less data artifacts than conventional techniques for capturing physiological data for analyzing sleep quality. Neuro-respiratory signals are analyzed using means to extract more accurate definitions of the frequency and severity of sleep discontinuity, sleep disordered breathing and patterns of sleep architecture. Biological biomarkers and questionnaire responses can also be compared to a database of healthy and chronically diseased patients to provide a more accurate differential diagnosis and to help determine the appropriate disease management recommendations.

Claims

1. A system for assessing sleep quality of a user, the system comprising:

a sensor strip comprising at least one sensor, which detects data indicative of normal and abnormal patterns during sleep of a user, and a tab comprising traces electrically coupled to the at least one sensor, wherein the sensor strip is configured to be positioned on the user'"'"'s forehead and removably coupled to at least one strap;

a data acquisition unit comprising an enclosure having a connector therein, wherein the data acquisition unit is configured to be positioned on the user'"'"'s head, wherein the tab of the sensor strip fits within the enclosure and is detachably coupled to the data acquisition unit within the enclosure such that the traces of the tab are electrically coupled to the data acquisition unit via the connector, and wherein the data acquisition unit collects the data indicative of normal and abnormal patterns during sleep from the at least one sensor in the sensor strip.

2. The system of claim 1 further comprising a nasal pneumotachometer in communication with the data acquisition unit to provide the data acquisition unit with a signal indicative of airflow through the user'"'"'s nose, the pneumotachometer being capable of detecting minute changes in airflow through the user'"'"'s nose.

3. The system of claim 1 further comprising a nasal cannula in communication with the data acquisition unit to provide the data acquisition unit with a signal indicative of airflow through the user'"'"'s nose by detecting a difference in pressure between the nasal cavity and the atmosphere.

4. The system of claim 1 further comprising at least one wireless sensor in wireless communication with the data acquisition unit to provide the data acquisition unit with data indicative of a physiological state of the user during sleep, the at least one wireless sensor configured to be separate from the sensor strip.

5. The system of claim 4 wherein the data acquisition unit aligns the data collected from the at least one sensor in the sensor strip with the data provided by the at least one wireless sensor based on timestamp information.

6. The system of claim 4, further comprising at least one executable software module that determines the physiological state of the user during sleep based on changes in oxyhemoglobin saturation.

7. The system of claim 1 wherein the at least one sensor includes at least one electrode for measuring one or more of electroencephalography (EEG), electro-oculargraphy (EOG), and electromyography (EMG) and at least one reflectance sensor.

8. The system of claim 1, wherein the at least one sensor comprises at least two sensors configured to collect data of a different type.

9. The system of claim 1 wherein the sensor strip is disposable and the tab of the sensor strip can be decoupled from the data acquisition unit.

10. The system of claim 9 wherein the sensor strip includes an adhesive backing for removeably affixing the sensor strip to the user'"'"'s body.

11. The system of claim 1 further comprising a microphone which detects snoring, wherein the data acquisition is in communication with the microphone to collect data indicative of snoring.

12. The system of claim 1 further comprising at least one executable software module, wherein the data acquisition unit collects data from at least two sensors, and wherein the at least one executable software module distinguishes abnormal from normal sleep states and continuity of the user based at least in part on a measure of agreement between the data collected from the at least two sensors.

13. The system of claim 12, wherein the at least one executable software module additionally identifies one or more diseases which may be negatively impacted by the user'"'"'s sleep quality using a comparative data store of subjects.

14. The system of claim 13, wherein the at least one executable software module additionally identifies one or more recommendations for treatment of the identified one or more diseases using a disease recommendations data store.

15. The system of claim 12 further comprising an external computer system which receives data collected by the data acquisition unit from the data acquisition unit, wherein the at least one executable software module is executed on the external computer system.

16. The system of claim 12, wherein the at least one executable software module comprises a web portal comprising one or more user interfaces.

17. The system of claim 16, wherein the web portal provides viewing and editing of the data.

18. The system of claim 12, wherein the at least one executable software module distinguishes abnormal sleep states and continuity using patterns of sympathetic, cortical, or behavioral arousals of the user.

19. The system of claim 1, further comprising at least one executable module that:

recognizes rapid eye movement (REM) states based on ratios between electroencephalographic (EEG) beta and delta power;

recognizes slow wave sleep states based on ratios of EEG delta, beta, and theta power; and

recognizes light non-REM sleep states based on short duration fast-frequency EEG bursts indicative of sleep spindles.

20. The system of claim 1, wherein the connector comprises a socket connection.

21. The system of claim 1, wherein the at least one sensor comprises at least two sensors, and the system further comprises at least one executable software module that receives the data collected by the data acquisition unit, and determines a quality of the user'"'"'s sleep based, at least in part, on the concordance of normal and abnormal patterns across the collected data.

22. The system of claim 21, wherein the at least one executable software module determines two or more potential underlying medical conditions of the user based, at least in part, on the determined quality of the user'"'"'s sleep.

23. The system of claim 22, wherein the at least one executable software module further, for each of the two or more potential underlying medical conditions, determines a probability estimate that the user has or will develop the potential underlying medical condition.

24. The system of claim 22, wherein the at least one executable software module determines the two or more potential underlying medical conditions of the user further based, in part, on daytime psychophysiological states of the user.

25. The system of claim 22, wherein the at least one executable software module determines the two or more potential underlying medical conditions of the user further based, in part, on biological markers.

26. The system of claim 22, wherein the at least one executable software module further compares the determined quality of the user'"'"'s sleep to a database of corresponding values.

27. The system of claim 1, wherein the data acquisition unit is configured to receive cardio-physiologic data from one or more cardio-physiologic sensors.

28. The system of claim 27, further comprising the one or more cardio-physiologic sensors, wherein the one or more cardio-physiologic sensors are separate from the sensor strip.

29. The system of claim 27, further comprising at least one executable software module that:

receives the data indicative of normal and abnormal patterns during sleep;

receives the cardio-physiologic data;

measures non-abating sympathetic hyperactivity based, at least in part, on the cardio-physiologic data; and

determines one or more potential underlying medical conditions of the user based, at least in part, on the data indicative of normal and abnormal patterns during sleep and the measure of non-abating sympathetic hyperactivity.

30. The system of claim 1, further comprising at least one executable software module that determines one or more potential underlying medical conditions of the user based on frequency characteristics of one or more sleep states of the user.

31. The system of claim 30, wherein the at least one executable software module resides in the data acquisition unit.

32. The system of claim 30, wherein the at least one executable software module resides on a computer system which is external to the data acquisition unit.