A Novel mHealth Approach for the Monitoring and Assisted Therapeutics of Obstructive Sleep Apnea
Obstructive sleep apnea is a respiratory problem that has serious consequences for physical and mental health, but also in monetary terms, since traffic accidents and poor work performance, among other direct consequences, are attributed to it. It is estimated that between 9% and 38% of the world’s...
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Published in: | Applied sciences Vol. 12; no. 20; p. 10257 |
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Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
Basel
MDPI AG
01-10-2022
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Subjects: | |
Online Access: | Get full text |
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Summary: | Obstructive sleep apnea is a respiratory problem that has serious consequences for physical and mental health, but also in monetary terms, since traffic accidents and poor work performance, among other direct consequences, are attributed to it. It is estimated that between 9% and 38% of the world’s population has this disease. This is a multifactorial disease, therefore, there are several methods of detection and treatment; however, all of them cause discomfort to the patient, or to those around them. In this article we propose a system for the detection and control of obstructive sleep apnea that promises to overcome the drawbacks of the existing therapies, therefore, potentially making it a practical and effective solution for this disease. The proof of concept presented in this paper makes use of an electromyography sensor to collect the myoelectric signal produced by the genioglossus muscle. Surface electrodes provide the electromyography signals to an ESP32 microcontroller, which has the function of analyzing and comparing the data obtained with a predefined value of the apnea threshold. After the detection of an apnea, the circuit is able to create a stimulus signal that is applied directly to the muscle, so that airway occlusion does not occur, and the user does not wake up. The data from each use are automatically sent to a database to be viewed and analyzed at a later point. |
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ISSN: | 2076-3417 2076-3417 |
DOI: | 10.3390/app122010257 |