AI-Enhanced Edge Device for Real-Time Snoring Detection

This paper presents the development of a cutting-edge, non-invasive edge device designed to monitor snoring and provide timely, moderate haptic feedback to users. Utilizing the Qualcomm Snapdragon 8cx Gen 3 processor, the device offers robust computing power and AI capabilities for real-time processing, making it a versatile tool for health monitoring applications. The system integrates a high-fidelity MEMS microphone array capable of capturing nuanced audio signals and a TDK piezoelectric haptic actuator, which delivers precise alerts through customized vibrations. The research explores the potential of this advanced hardware in detecting and managing obstructive sleep apnea (OSA), a condition often underdiagnosed due to a lack of patient awareness. By leveraging state-of-the-art digital signal processing and deep learning techniques, the device aims to enhance user awareness and intervention in sleep-related disorders, offering a promising new avenue for improving patient outcomes and quality of life.

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Publication Details

Journal
Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023
Published
2024-10-02
DOI
https://doi.org/10.60087/jaigs.v6i1.224
Primary Topic
Obstructive Sleep Apnea Research
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Enhanced Edge Device for Real-Time Snoring Detection

Jianhua Xie
Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023
Obstructive Sleep Apnea Research
article

AI-Enhanced Edge Device for Real-Time Snoring Detection

Jianhua Xie
article en

Abstract

This paper presents the development of a cutting-edge, non-invasive edge device designed to monitor snoring and provide timely, moderate haptic feedback to users. Utilizing the Qualcomm Snapdragon 8cx Gen 3 processor, the device offers robust computing power and AI capabilities for real-time processing, making it a versatile tool for health monitoring applications. The system integrates a high-fidelity MEMS microphone array capable of capturing nuanced audio signals and a TDK piezoelectric haptic actuator, which delivers precise alerts through customized vibrations. The research explores the potential of this advanced hardware in detecting and managing obstructive sleep apnea (OSA), a condition often underdiagnosed due to a lack of patient awareness. By leveraging state-of-the-art digital signal processing and deep learning techniques, the device aims to enhance user awareness and intervention in sleep-related disorders, offering a promising new avenue for improving patient outcomes and quality of life.

Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023Vol. 6(1)
Sichuan University (CN)
Openalex Percentile: Top 76%
Obstructive Sleep Apnea Research
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AI-Enhanced Edge Device for Real-Time Snoring Detection — Jianhua Xie · Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023 (2024) | TGRS Research Map | TGRS