System for the assessment of sleep quality in adults and children

• US 8,639,313 B2
• Filed: 01/14/2013
• Issued: 01/28/2014
• Est. Priority Date: 03/17/2009
• Status: Active Grant

• Current Assignee: Advanced Brain Monitoring
• Original Assignee: Advanced Brain Monitoring
• Inventors: Westbrook, Philip R., Levendowski, Daniel J., Zavora, Timothy, Davis, Gene, Popovic, Djordje, Berka, Chris, Mitrovic, Mirko, Veljkovic, Bratislav
• Primary Examiner(s): Cohen, Lee S
• Application Number:
  US13/741,063
• Publication Number:
  US 20130131464A1
• Time in Patent Office: 379 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 and a tab, wherein the tab comprises traces that are electrically coupled to the at least one sensor;

a data acquisition unit comprising at least one controller and a connector,

wherein the connector is configured to be detachably coupled to the tab of the sensor strip such that the traces of the tab are electrically coupled to the data acquisition unit via the connector, and

wherein the controller collects signal data from the at least one sensor; and

one or more software modules that are configured to, when executed by one or more hardware processors, characterize an etiology of a sleep quality for a user by, for each of a plurality of disorders, determining a probability that the user has the disorder based, at least in part, on the signal data.

2. The system of claim 1, wherein the plurality of disorders comprises depression.

3. The system of claim 1, wherein the one or more software modules are further configured to provide a differential diagnosis based on the determined probabilities of the user having the disorders.

4. The system of claim 3, wherein the one or more software modules are further configured to provide recommendations for therapy based on the differential diagnosis.

5. The system of claim 1, wherein the one or more software modules are further configured to identify sleep states and arousals based on the signal data, and, for one or more of the plurality of disorders, determine the probability that the user has the disorder based on the identified sleep states and arousals.

6. Previously Presented) The system of claim 5, wherein the one or more software modules are further configured to determine one or more ratios of power in a plurality of frequency bands of the signal data, and identify sleep states based on the determined one or more ratios of power.

7. The system of claim 5, wherein the one or more software modules are further configured to calculate one or more weighted sums of power in a plurality of frequency bands of the signal data, and identify sleep states based on the calculated one or more weighted sums of power.

8. The system of claim 1, wherein the signal data comprise at least one actigraphic signal.

9. The system of claim 8, wherein the actigraphic signal comprises data indicative of one or more body movements.

10. The system of claim 1, wherein the at least one sensor comprises a plurality of sensors, and wherein the one or more software modules are further configured to align the signal data from the plurality of sensors based on time stamps associated with the signal data.

11. The system of claim 1, wherein the one or more software modules comprise a web portal that is configured to:

receive the collected signal data;

provide one or more web pages to a user, wherein the one or more web pages are configured to present a questionnaire to the user; and

receive responses to the questionnaire from the user;

wherein the one or more software modules are configured to, for one or more of the plurality of disorders, determine a probability that the user has the disorder based, at least in part, on the signal data and the responses to the questionnaire.

12. The system of claim 1, wherein the one or more software modules are further configured to:

receive responses to a questionnaire from the user;

access comparative data comprising values for a plurality of patients; and

,

for one or more of the plurality of disorders, determine a probability that the user has the disorder based, at least in part, on the signal data, the responses to the questionnaire, and the comparative data.

13. A method for assessing sleep quality of a user, the method comprising:

by a controller of a data acquisition unit, which is electrically coupled to at least one sensor of a sensor strip via a connector detachably coupled to a tab of the sensor strip such that traces of the tab, which are electrically coupled to the at least one sensor, are electrically coupled to the data acquisition unit, collecting signal data from the at least one sensor; and

,

by one or more software modules, executed by one or more hardware processors, characterizing an etiology of a sleep quality for a user by, for each of a plurality of disorders, determining a probability that the user has the disorder based, at least in part, on the signal data.

14. The method of claim 13, further comprising, by the one or more software modules, attributing insomnia to either a physical or psychological cause.

15. The method of claim 13, wherein the plurality of disorders comprises depression.

16. The method of claim 13, further comprising, by the one or more software modules, providing a differential diagnosis based on the determined probabilities of the user having the disorders, and providing recommendations for therapy based on the differential diagnosis.

17. The method of claim 13, further comprising, by the one or more software modules, identifying sleep states and arousals based on the signal data, and, for one or more of the plurality of disorders, determining the probability that the user has the disorder based on the identified sleep states and arousals.

18. The method of claim 13, wherein the signal data comprises at least one actigraphic signal comprising data indicative of one or more body movements.

19. The method of claim 13, further comprising, by the one or more software modules, acquiring responses to a questionnaire from the user, and, for one or more of the plurality of disorders, determining the probability that the user has the disorder based, at least in part, on the signal data and the acquired responses to the questionnaire.

20. The method of claim 19, wherein the one or more software modules comprise a web portal, and wherein the method further comprises, by the web portal:

receiving the collected signal data; and

providing one or more web pages to a user, wherein the one or more web pages are configured to present the questionnaire to the user and receive the responses to the questionnaire from the user.

21. The method of claim 19, further comprising:

accessing comparative data comprising values for a plurality of patients; and

,

for one or more of the plurality of disorders, determining a probability that the user has the disorder based, at least in part, on the signal data, the acquired responses to the questionnaire, and the comparative data.