Soft Wireless Wearable Sensor Patches for At-Home Sleep Monitoring
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Solution Overview
Problem
Current sleep disorder diagnosis methods, such as polysomnography (PSG), are resource-intensive, costly, and not easily accessible, requiring specialized facilities and trained personnel, limiting their availability for at-home use.
Innovation Solution
A portable, wireless wearable sensor system with integrated machine learning, comprising hypoallergenic silicone adhesive substrates and stretchable electrodes, is used for EEG, EOG, and EMG sensing, enabling at-home sleep quality monitoring and obstructive sleep apnea detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional polysomnography is used for sleep disorder diagnosis, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent combines multiple sensor functions (EEG, EOG, EMG, respiratory monitoring) into a single integrated wearable patch device. The patch integrates electrodes for brain activity detection, eye movement sensors, muscle activity sensors, and respiratory monitoring components into one unified wearable unit that can be attached to the patient's chest or body, eliminating the need for separate sensor leads and complex wiring systems.
Solution Approach 2:
The wearable patch is designed to perform multiple monitoring functions simultaneously - detecting sleep stages through EEG, monitoring eye movements through EOG, tracking muscle activity through EMG, and detecting respiratory events. This multi-functional design allows a single device to replace the comprehensive but complex polysomnography system, providing universal sleep disorder diagnosis capability.
2Measurement precision
If polysomnography with specialized equipment is used, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The wearable patch is designed for self-application by the patient without requiring specialized technician assistance. The patch can be easily attached to the patient's chest or body by the patient themselves, eliminating the need for trained personnel to set up complex polysomnography equipment. The device autonomously performs monitoring and can transmit data wirelessly for analysis.
Solution Approach 2:
The patent replaces the complex mechanical polysomnography system with a wireless electronic monitoring system. Instead of requiring physical sensor leads connected to a centralized recording system, the wearable patch uses integrated electronics and wireless communication to transmit sleep data, simplifying the overall system and making it easier to operate in home settings.
3Measurement precision
If traditional wired sensor systems are used, then measurement precision is improved, but portability deteriorates
Solution Approach 1:
The patent extracts the essential sensing and processing functions from the bulky polysomnography equipment and concentrates them into a compact wearable patch. By removing unnecessary components and integrating only the essential sensors and electronics needed for accurate physiological signal detection, the system achieves both precision and portability in a lightweight form factor.
Solution Approach 2:
The wearable patch utilizes flexible substrates and thin-film electronics to achieve both mechanical compliance with the body and electrical functionality. This allows the patch to conform to body surfaces while maintaining lightweight construction and flexible circuitry, enabling portable monitoring without the bulk of traditional wired systems.
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
The system provides accurate sleep stage classification and apnea event detection with 88.5% accuracy, comparable to clinical PSG, facilitating accessible and comfortable home healthcare monitoring.
Implementation Method 1
an integrated sensor system coupled to the inner surface of the silicone adhesive substrate, the integrated sensor system comprising a plurality of electrodes placed in predetermined locations and electrical connections between the plurality of electrodes
Data Source
AI summary
Exemplary systems, methods, and devices are disclosed which provide at-home, portable, wireless sleep sensors and wearable electronics with embedded machine learning. Such devices have applications in assessing sleep quality and detecting sleep apnea with multiple patients. Unlike the conventional system at a sleep center using numerous bulky sensors, the soft all-integrated wearable platform offers natural sleep in a familiar setting. The face-mounted patches that detect brain, eye, and muscle signals show comparable performance in sleep monitoring with polysomnography in a clinical study. Furthermore, deep learning is embedded in an exemplary device, offering automated high-precision sleep scoring, which demonstrates the wearable system's portability and point-of-care usability. The at-home wearable patches help to support portable sleep monitoring and home healthcare.