A Novel In-Home Sleep Monitoring System Based on Fully Integrated Multichannel Front-End Chip and Its Multilevel...

Area of Science:

• Biomedical Engineering
• Wearable Technology
• Sleep Science

Background:

• Polysomnography (PSG) is the gold standard for sleep monitoring but is expensive and lab-based.
• There is a need for accessible, cost-effective, and portable systems for long-term in-home sleep monitoring.
• Advancements in integrated circuit design enable miniaturized and low-power biopotential acquisition systems.

Purpose of the Study:

• To develop and validate a novel in-home sleep monitoring system utilizing an 8-channel biopotential acquisition front-end chip.
• To compare the performance of the developed system against advanced polysomnography using multilevel data analyses.
• To assess the system's suitability for long-term, out-of-laboratory sleep monitoring and sleep disorder screening.

Main Methods:

• Designed an 8-channel biopotential acquisition front-end chip with a low-noise programmable gain amplifier (PGA) and a 24-bit analog-to-digital converter (ADC).
• Incorporated an innovative chopper-modulated input-scaling-down technique to enhance dynamic range.
• Conducted in-home sleep monitoring of 20 healthy participants using both the proposed system and commercial polysomnography, followed by data consistency and significance analyses.

Main Results:

• The acquisition front-end chip demonstrated excellent performance, including low input-referred noise (0.5 μVpp), high input impedance (1.25 GΩ), and a high common-mode rejection ratio (113.9 dB).
• High agreement was observed between the proposed system and PSG, with kappa coefficients for sleep staging between scorers around 0.80 and consistency metrics for various features exceeding 0.83.
• Macro sleep architecture characteristics derived from both systems showed no significant differences (p > 0.05).

Conclusions:

• The developed in-home sleep monitoring system, built around the novel biopotential acquisition chip, is significantly reduced in size, power, and cost.
• Multilevel data analyses confirm that the system collects stable and accurate in-home sleep data, comparable to PSG.
• The system is well-suited for long-term in-home sleep monitoring and cost-effective sleep disorder screening outside clinical settings.