Methods and apparatus for ventilatory treatment of respiratory disorders
US-2024399083-A1 · Dec 5, 2024 · US
US9687177B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9687177-B2 |
| Application number | US-201013383341-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 14, 2010 |
| Priority date | Jul 16, 2009 |
| Publication date | Jun 27, 2017 |
| Grant date | Jun 27, 2017 |
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Automated devices provide methodologies for determining sleep conditions, which may be in conjunction with treatment of sleep disordered breathing by a pressure treatment apparatus such as a continuous positive airway pressure device. Based on a measure of respiratory airflow, respiratory characteristics are extracted to detect arousal conditions, sleep stability, sleep states and/or perform sleep quality assessments. The methodologies may be implemented for data analysis by a specific purpose computer, a monitoring device that measures a respiratory airflow and/or a respiratory treatment apparatus that provides a respiratory treatment regime based on the detected conditions.
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The invention claimed is: 1. A method for controlling a processor to detect a sleep state from a measured flow of breathable gas, the method of the processor comprising: determining a plurality of respiratory characteristics from a measure of respiratory flow; detecting a sleep state from potential sleep states comprising a Non-REM sleep state and a REM sleep state, the detecting of the sleep state based on the determined respiratory characteristics, the detection of the sleep state based on data from the measure of flow from a flow sensor, the detecting of the sleep state not being based on data from electroencephalogram (E.E.G.), electromyography (E.M.G.) and electrooculography (E.O.G.) sensors; and indicating the detected sleep state, wherein the determined plurality of respiratory characteristics from which the sleep state is detected includes a set of two or more measures of (a) a measure of expiratory peak flow variation derived from a plurality of breaths, (b) a measure of a ratio of an expiratory peak flow location and expiratory time, (c) a measure of an expiratory peak flow location variation derived from a plurality of breaths, (d) a measure of an area of an expiratory peak flow, (e) a measure of an area of an expiratory peak flow variation, (f) a measure of a time from expiratory peak flow to inspiration start, (g) a measure of a time since last confirmed breath variability, (h) a measure of a high breath frequency period, and (i) a measure of inspiratory time variability. 2. The method of claim 1 wherein the potential sleep states further comprises an awake state. 3. The method of claim 2 wherein the REM sleep state is a light REM state and the potential sleep states further comprises a deep REM state. 4. The method of claim 1 wherein the processor determines a next sleep state as the detected sleep state by calculating probabilities representative of transitions from a current sleep state to each potential next sleep state with data from the plurality of respiratory characteristics, in which the next sleep state is of the potential sleep states which include the current sleep state, and determines the detected sleep state as a function of a most probable one of the calculated probabilities. 5. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of inspiratory peak flow variation. 6. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of expiratory peak flow variation derived from a plurality of breaths. 7. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of a ratio of an expiratory peak flow location and expiratory time. 8. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of an expiratory peak flow location variation derived from a plurality of breaths. 9. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of an area of an expiratory peak flow. 10. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of an area of an expiratory peak flow variation. 11. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of a time from expiratory peak flow to inspiration start. 12. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of a time since last confirmed breath variability. 13. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of a high breath frequency period. 14. The method of claim 1 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of inspiratory time variability. 15. The method of claim 1 wherein processer further controls a respiratory pressure treatment regime based on the detected sleep state. 16. A sleep state detection apparatus comprising: a controller having at least one processor to access data representing a measured flow of breathable gas, the controller being further configured to: determine a plurality of respiratory characteristics from a measure of respiratory flow based on the accessed data; detect a sleep state from potential sleep states comprising a Non-REM sleep state and a REM sleep state, the detecting of the sleep state based on the determined respiratory characteristics, the detecting of the sleep state based on data from the measure of flow from a flow sensor, the detecting of the sleep state not being based on data from electroencephalogram (E.E.G.), electromyography (E.M.G.) and electrooculography (E.O.G.) sensors; and indicate the detected sleep state, wherein the determined plurality of respiratory characteristics from which the sleep state is detected includes a set of two or more measures of (a) a measure of expiratory peak flow variation derived from a plurality of breaths, (b) a measure of a ratio of an expiratory peak flow location and expiratory time, (c) a measure of an expiratory peak flow location variation derived from a plurality of breaths, (d) a measure of an area of an expiratory peak flow, (e) a measure of an area of an expiratory peak flow variation, (f) a measure of a time from expiratory peak flow to inspiration start, (g) a measure of a time since last confirmed breath variability, (h) a measure of a high breath frequency period, and (i) a measure of inspiratory time variability. 17. The sleep state detection apparatus of claim 16 wherein the potential sleep states further comprises an awake state. 18. The sleep state detection apparatus of claim 17 wherein the REM sleep state is a light REM state and the potential sleep states further comprises a deep REM state. 19. The sleep state detection apparatus of claim 16 wherein the processor determines a next sleep state as the detected sleep state by calculating probabilities representative of transitions from a current sleep state to each potential next sleep state with data from the plurality of respiratory characteristics, in which the next sleep state is of the potential sleep states which include the current sleep state, and determines the detected sleep state as a function of a most probable one of the calculated probabilities. 20. The sleep state detection apparatus of claim 16 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of inspiratory peak flow variation. 21. The sleep state detection apparatus of claim 16 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of expiratory peak flow variation derived from a plurality of breaths. 22. The sleep state detection apparatus of claim 16 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of a ratio of an expiratory peak flow location and expiratory time. 23. The sleep state detection apparatus of claim 16 wherein the plurality of respiratory characteristics from which the sleep state is detected includes a measure of an expirat
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