Apnea Aware: An Intelligent Sleep Monitoring and Intervention System for Obstructive Sleep Apnea

Sleep apnea is a serious condition where breathing is more than once hindered or halted for at slightest 10 seconds amid rest. There are three fundamental sorts of sleep apnea: Obstructive Sleep Apnea (OSA), Central Sleep Apnea (CSA), and Complex Sleep Apnea. OSA, the most common type, is regularly caused by loosening up of throat muscles, driving to trachea blockage. This condition can lead to different wellbeing complications such as heart issues, stroke, anxiety, and depression. Elements like corpulence, liquor ingestion, and smoking contribute to its advancement. Early discovery is significant for convenient treatment. This paper presents a reasonable sleep monitoring framework for recognizing OSA, utilizing SPO2, heart rate, body position changes, and snoring occasions, coordinates with machine learning for progressed precision. The framework incorporates a web interface for patient and doctor to access, calculating the Apnea-Hypopnea Index (AHI) to classify cases as Hypopnea, Apnea, or Normal.

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Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/spices62143.2024.10779694
Primary Topic
Obstructive Sleep Apnea Research
Type
article
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article

Apnea Aware: An Intelligent Sleep Monitoring and Intervention System for Obstructive Sleep Apnea

L Sam, Archana Aniyan, Sereen Sabu, Soorya S Pai
Obstructive Sleep Apnea Research
article

Apnea Aware: An Intelligent Sleep Monitoring and Intervention System for Obstructive Sleep Apnea

L Sam, Archana Aniyan, Sereen Sabu, Soorya S Pai
article en

Abstract

Sleep apnea is a serious condition where breathing is more than once hindered or halted for at slightest 10 seconds amid rest. There are three fundamental sorts of sleep apnea: Obstructive Sleep Apnea (OSA), Central Sleep Apnea (CSA), and Complex Sleep Apnea. OSA, the most common type, is regularly caused by loosening up of throat muscles, driving to trachea blockage. This condition can lead to different wellbeing complications such as heart issues, stroke, anxiety, and depression. Elements like corpulence, liquor ingestion, and smoking contribute to its advancement. Early discovery is significant for convenient treatment. This paper presents a reasonable sleep monitoring framework for recognizing OSA, utilizing SPO2, heart rate, body position changes, and snoring occasions, coordinates with machine learning for progressed precision. The framework incorporates a web interface for patient and doctor to access, calculating the Apnea-Hypopnea Index (AHI) to classify cases as Hypopnea, Apnea, or Normal.

Openalex Percentile: Top 68%
Obstructive Sleep Apnea Research
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Apnea Aware: An Intelligent Sleep Monitoring and Intervention System for Obstructive Sleep Apnea — L Sam, Archana Aniyan, et al. · (2024) | TGRS Research Map | TGRS