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Multimedia Monitori...
Multimedia Monitoring System of Obstructive Sleep Apnea via Deep Active Learning Model
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Teng, Fei (author)
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Wang, Dian (author)
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Yuan, Yue (author)
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Zhang, Haibo (author)
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Singh, Amit Kumar (author)
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- Lv, Zhihan, Dr. 1984- (author)
- Uppsala universitet,Institutionen för speldesign
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(creator_code:org_t)
- IEEE, 2022
- 2022
- English.
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In: IEEE Multimedia. - : IEEE. - 1070-986X .- 1941-0166. ; 29:3, s. 48-56
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https://ieeexplore.i...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- Obstructive Sleep Apnea (OSA) is one of the most common sleep-related breathing disorders. Nearly 1 billion people worldwide suffer from it, causing serious health effects and social burden. However, traditional monitoring systems often fall short in terms of cost and accessibility. In this article, we first propose a deep active learning model to detect OSA events from electrocardiogram (ECG). We then designed and developed a prototype of OSA monitoring system using ECG sensor and smartphone, in which our OSA detection algorithm is implemented and validated. Experiments show that we achieve accuracy of 92.15% while using 40% of labeled data, significantly reducing the cost of labeling and maximizing the performance. According to detection results and health-related multimedia signals, we provide OSA risk level and medical advice to users. We believe that the multimedia monitoring system can efficiently help diagnose OSA, which could lead to effective intervention strategies and better sleep care.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Lungmedicin och allergi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Respiratory Medicine and Allergy (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
Keyword
- Deep learning
- Feature extraction
- Health risks
- Monitoring
- Sleep research
- Active Learning
- Features extraction
- Health effects
- Labelings
- Learning models
- Monitoring system
- Obstructive sleep apnea
- Sleep apnea events
- Sleep-related breathing disorders
- Uncertainty
- Electrocardiography
Publication and Content Type
- ref (subject category)
- art (subject category)
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