Abstract:
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a significant public health concern. Wearable devices, such as smart rings and smart watches, provide a more convenie...Show MoreMetadata
Abstract:
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a significant public health concern. Wearable devices, such as smart rings and smart watches, provide a more convenient and less invasive alternative to traditional polysomnography (PSG) testing for detecting OSAHS. Smart rings, which collect signals from the finger base, offer superior signal quality and robustness compared to wrist signals from smart watches, making them a more convenient option for OSAHS detection. However, there is currently no research validating the performance of smart ring-based OSAHS detection. To our best knowledge, we are the first to investigate the feasibility and effectiveness of detecting OSAHS using smart rings. We analyzed 58 subjects, each wearing both a PSG device and RingConn smart rings for overnight OSAHS monitoring. Additionally, we propose a novel deep learning model to address the challenges posed by the distribution gap between photoplethysmography and blood oxygen saturation in OSAHS detection modeling, while efficiently capturing local and global features. Experimental results have demonstrated that smart rings detected OSAHS in good agreement with PSG, with a correlation coefficient of r =0.93. Our model also outperforms state-of-the-art methods.
Date of Conference: 22-25 April 2024
Date Added to IEEE Xplore: 19 July 2024
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- IEEE Keywords
- Index Terms
- Obstructive Sleep Apnea Hypopnea Syndrome ,
- Smart Ring ,
- Local Features ,
- Global Features ,
- Wearable Devices ,
- Obstructive Sleep Apnea ,
- Photoplethysmography ,
- Distribution Gap ,
- Smart Watches ,
- Receiver Operating Characteristic Curve ,
- Convolutional Neural Network ,
- Low-pass ,
- Positive Predictive Value ,
- Negative Predictive Value ,
- Sleep Apnea ,
- Max-pooling ,
- Apnea-hypopnea Index ,
- Signal Segments ,
- Multimodal Learning ,
- Multimodal Model ,
- Transformer Encoder ,
- PPG Signal
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Obstructive Sleep Apnea Hypopnea Syndrome ,
- Smart Ring ,
- Local Features ,
- Global Features ,
- Wearable Devices ,
- Obstructive Sleep Apnea ,
- Photoplethysmography ,
- Distribution Gap ,
- Smart Watches ,
- Receiver Operating Characteristic Curve ,
- Convolutional Neural Network ,
- Low-pass ,
- Positive Predictive Value ,
- Negative Predictive Value ,
- Sleep Apnea ,
- Max-pooling ,
- Apnea-hypopnea Index ,
- Signal Segments ,
- Multimodal Learning ,
- Multimodal Model ,
- Transformer Encoder ,
- PPG Signal
- Author Keywords