PPG Detection of Sleep-State Transitions Without Polysomnography
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Solution Overview
Problem
Current methods for detecting transitions between awake, drowsiness, and sleep phases are invasive, costly, and unreliable, particularly in transportation and working environments, as they rely on complex and expensive equipment like polysomnography (PSG) or insufficient vehicle-based and physiological measures.
Innovation Solution
A modular, adaptive, and cost-effective electronic processing system using PhotoPlethysmography (PPG) technology for both contact and contactless detection, combining time and frequency domain analysis to predict transitions between awake, drowsiness, and sleep phases, with self-calibration and consideration of extra context features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If polysomnography (PSG) is used for detecting transitions between awake, drowsiness, and sleep phases, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent extracts and focuses on a specific physiological parameter (PPG signal from peripheral blood flow) that can indicate sleep-wake transitions, rather than using the complete PSG suite of 10-30 sensors. This extraction approach maintains detection capability while dramatically reducing system complexity and cost.
Solution Approach 2:
The patent uses photoplethysmography (PPG) as a simplified copy or surrogate for the more complex EEG and other PSG measurements. The PPG signal serves as an optical copy that reflects cardiovascular changes associated with sleep-wake transitions, providing a less invasive and simpler alternative to direct brain activity monitoring.
2Measurement precision
If polysomnography (PSG) is used for detecting transitions between awake, drowsiness, and sleep phases, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements automated detection algorithms that process PPG signals and automatically identify sleep-wake transitions without requiring specialized technical staff for assembly or doctors for analysis. The system performs self-calibration and automated phase detection, making it operable by non-experts in transportation and working environments.
3Reliability
If traditional physiological measures are used for drowsiness detection, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent makes the PPG sensor multi-functional by extracting multiple physiological parameters (heart rate, respiratory rate, blood oxygen saturation, and sleep-wake state indicators) from a single optical measurement. This universal approach maintains detection reliability across different physiological metrics while using a single simple sensor instead of multiple specialized devices.
4Ease of operation
If contactless detection is implemented, then ease of operation is improved, but measurement precision may deteriorate
Solution Approach 1:
The patent uses the skin and tissue as an intermediary medium for contactless PPG detection. The optical sensor measures blood flow changes through the tissue without direct skin contact, and the system includes signal processing algorithms that compensate for the attenuation and distortion introduced by this intermediary, maintaining measurement precision while achieving non-invasive detection.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides accurate, real-time, and non-invasive detection and prediction of transitions between awake, drowsiness, and sleep phases, suitable for various applications where drowsiness is a concern, reducing the risk of accidents and improving safety.
Implementation Method 1
The PPG monitor module 2 may be any device capable of detecting physiological parameters of a subject, such as heart rate, respiratory rate, blood oxygen saturation and the like, through PhotoPlethysmography (PPG) technology, in a contact or contactless manner.
Data Source
AI summary
A smart system comprising a contact or contactless PPG sensor to output a PPG signal; and an electronic processing system in communication with the PPG sensor to acquire the PPG signal therefrom and analyse the PPG signal in one or both of time and frequency domains to real-time predict transitions between awake and sleep phases of a subject based on an output of the analysis, either wearing the smart wearable system equipped with the contact PPG sensor or remotely monitored by the contactless PPG sensor.