Sleep Apnea Control Device

Abstract

Disclosed herein are various methods, systems, an apparatuses for determining appropriate situations to treat conditions such as sleep apnea. At appropriate times, treatment can be applied such as through electrical stimulation to a person (e.g., an electrical stimulation of a person's genioglossus muscle in response to detecting that the person is undergoing an obstructive sleep apnea precursor event). In exemplary embodiments, a sensor such as a microphone and/or motion sensor can be used to provide a processor with data to facilitate a determination by the processor as to whether an electrical stimulus should be applied.

What is claimed is: 
     
         1 . A stimulation method comprising:
 processing data to determine whether a condition indicative of a sleep apnea event is indicated by the sound data, the processed data comprising at least one member of the group consisting of sound data indicative of whether a condition associated with a sleep apnea-related event exists and motion data indicative of whether a condition associated with a sleep apnea-related event exists;   generating a stimulation signal in response to a determination that the condition exists; and   electrically stimulating a sleep apnea treatment location for a person in response to the generated stimulation signal.   
     
     
         2 . The method of  claim 1  wherein the processed data comprises sound data representative of an ambient acoustic signal, the method further comprising:
 generating the sound data via a microphone. 
 
     
     
         3 . The method of  claim 2  wherein the electrically stimulating step comprises electrically stimulating a genioglossus muscle location in response to the generated stimulation signal. 
     
     
         4 . The method of  claim 3  wherein the electrically stimulating step comprises electrically stimulating the genioglossus muscle location in response to the generated stimulation signal via an electrode positioned to directly stimulate the posterior genioglossus muscle. 
     
     
         5 . The method of  claim 3  wherein the microphone is implanted in the person, the microphone comprising a diaphragm, the diaphragm subcutaneously receiving the ambient acoustic signal. 
     
     
         6 . The method of  claim 3  wherein the processing step comprises (1) detecting whether a predetermined snoring signature is present in the sound data, and (2) determining that the condition is indicated in response to a determination that the predetermined snoring signature is present. 
     
     
         7 . The method of  claim 6  wherein the predetermined snoring signature is a predetermined obstructive sleep apnea precursor snoring signature. 
     
     
         8 . The method of  claim 6  wherein the processed data further comprises the motion data, the method further comprising:
 generating the motion data for the person via a motion sensor while the microphone generates the sound data; and 
 processing the motion data in combination with the sound data to isolate the predetermined snoring signature relative to background noise via a noise cancellation technique. 
 
     
     
         9 . The method of  claim 3  wherein the processing step is performed by a processor that is resident in a housing, the housing having been implanted in the person. 
     
     
         10 . The method of  claim 9  wherein the housing includes an energy storage device for powering the processor, the method further comprising:
 transcutaneously re-charging the energy storage device. 
 
     
     
         11 . The method of  claim 3  further comprising:
 operating in a first mode; and 
 operating in a second mode; 
 wherein the first mode operating step comprises performing the sound data processing step, the step of generating the stimulation signal in response to a determination that the condition is indicated, and the step of electrically stimulating the genioglossus muscle location in response to the generated stimulation signal; and 
 wherein the second mode operating step comprises electrically stimulating the genioglossus muscle location in accordance with a predetermined schedule. 
 
     
     
         12 . The method of  claim 1  wherein the processed data comprises the motion data, the motion data comprising vibratory data indicative of a vibration produced by the person, the method further comprising:
 generating the vibratory data via a vibratory sensor. 
 
     
     
         13 . The method of  claim 1  further comprising:
 electrically stimulating a body location for treating a condition other than sleep apnea. 
 
     
     
         14 . The method of  claim 13  performing the step of electrically stimulating a body location for treating a condition other than sleep apnea on at least one of a command basis or a scheduled basis. 
     
     
         15 . The method of  claim 13  wherein the body location comprises a location proximate to salivary gland so that the electrical stimulation proximate to the salivary gland induces salivation to treat a dry mouth condition. 
     
     
         16 . The method of  claim 13  wherein the body location comprises a location proximate to muscle affecting swallowing so that the electrical stimulation proximate to the muscle treats dysphagia. 
     
     
         17 . A stimulation method comprising:
 processing data indicative of snoring by a person to determine whether a condition indicative of a sleep apnea-related event exists;   generating a stimulation signal in response to a determination that the condition is indicated; and   electrically stimulating a sleep apnea treatment location for the person in response to the generated stimulation signal.   
     
     
         18 . The method of  claim 17 , wherein the processing step comprises a processor distinguishing between obstructive sleep apnea (OSA) snoring and non-OSA snoring based on the processed snoring data; and
 wherein the generating step comprises generating the stimulating signal in response to a determination that OSA snoring is indicated by the processed snoring data.   
     
     
         19 . The method of  claim 18 , wherein the distinguishing step comprises the processor distinguishing between OSA snoring and non-OSA snoring via apnea and hypopnea index precursors and events (AHIPE) discrimination based on a plurality of features of the processed snoring data. 
     
     
         20 . The method of  claim 19 , wherein the distinguishing step further comprises:
 the processor estimating a plurality of parameters from the processed snoring data based on temporal and spectral characteristics of the processed snoring data; and   the processor performing the AHIPE discrimination to distinguish between OSA snoring or non-OSA snoring based on the estimated parameters.