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This study will evaluate and compare the diagnostic accuracy and effectiveness of the Five Seasons Sleep Tracking Mat with the gold standard, polysomnography.
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Given that obstructive sleep apnea (OSA) imposes a heavy disease burden, conducting effective public screening is regarded as a crucial step in health management and chronic disease prevention. Currently, the diagnosis of OSA relies on polysomnography (PSG) and manual scoring, which are constrained by equipment availability and personnel shortages, resulting in low efficiency, high costs, and scheduling difficulties. Additionally, PSG monitoring requires numerous contact-based sensors, leading to poor patient compliance. The lack of large-scale screening and long-term follow-up further restricts the implementation of standardized and evidence-based treatments. Developing new, effective, low- or zero-burden sleep monitoring devices to minimize sleep disruption while ensuring monitoring accuracy is, therefore, a key direction for future research.
The Five Seasons Sleep Tracking Mat (5S Sleep Tracking Mat) detects heartbeats, respiration, body movements, and snoring using ballistocardiogram (BCG) signals. The device is composed primarily of a control unit, monitoring mat, temperature/humidity sensor, power adapter, and light sensor. During operation, the device accurately captures the impact force of bodily movements at a high sampling rate of 2 kHz. It then uses proprietary signal processing and pre-trained AI models to extract heartbeat and respiratory waveforms, as well as body movements. Additionally, it automatically detects respiratory events, calculates the apnea-hypopnea index (AHI), and determines sleep stages. Since the monitoring mat only needs to be placed under the pillow without requiring direct contact with the body or wearable accessories, it is particularly suitable for home-based, long-term daily sleep monitoring.
In this study, researchers will use the current gold standard, PSG, as a reference to validate the Five Seasons Sleep Tracking Mat for sleep monitoring and OSA-assisted diagnosis.
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Weijun Huang, Dr.
Data sourced from clinicaltrials.gov
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