Wearable Sleep Stage Identification via Motion and Heart Rate Analysis
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Solution Overview
Problem
Current wearable devices provide limited information about an individual's sleep patterns, including REM sleep, deep sleep, and nocturnal movements, which are crucial for overall health and well-being.
Innovation Solution
A system and method using a wearable device with motion and optical sensing systems to monitor heart rate and motion data, identifying REM sleep, deep sleep, and nocturnal motion by analyzing time domain characteristics and significant motion patterns, enabling the characterization of different sleep stages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current wearable devices are used to monitor sleep, then device simplicity is maintained, but sleep information accuracy is insufficient
Solution Approach 1:
The patent combines multiple sensor types (accelerometer for motion, optical sensor for heart rate, temperature sensor) into a single wearable device to achieve comprehensive sleep monitoring. This merging of sensing functions enables accurate detection of sleep stages and nocturnal movements while maintaining a unified device structure.
Solution Approach 2:
The wearable device is designed to perform multiple functions: monitoring motion, heart rate, and temperature simultaneously to characterize different sleep stages (REM, deep, light) and detect nocturnal movements. This multi-functionality allows one device to provide comprehensive sleep information without requiring separate specialized devices.
2Loss of information
If detailed sleep stage identification is implemented, then health monitoring value is improved, but data processing complexity increases
Solution Approach 1:
The patent segments sleep monitoring into distinct functional components: motion detection for nocturnal movements, optical sensing for heart rate variability, and temperature monitoring for sleep stage characterization. Each sensor type processes specific data streams independently before integration, reducing overall processing complexity while maintaining comprehensive sleep information.
Solution Approach 2:
The system performs preliminary data processing on each sensor stream individually (filtering, normalization) before integrating all data types for final sleep stage identification. This preliminary action reduces the complexity of subsequent integration and enables accurate characterization of sleep stages without overwhelming computational requirements.
3Measurement precision
If multiple sensors are integrated for comprehensive sleep monitoring, then measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The patent merges accelerometer, optical sensor, and temperature sensor into a single integrated wearable device with unified data processing. This consolidation achieves comprehensive sleep monitoring (motion, heart rate, temperature) for accurate sleep stage identification while avoiding the complexity of coordinating multiple separate devices.
Data Source
AI summary
Disclosed herein are systems, methods and a computer readable storage medium that determine an individual's movement during sleep. In some embodiments, the identification is based on data from a motion sensor included in wearable device. In some embodiments, the individual wears the wearable device on his wrist during the individual's resting and/or sleep activities. In some embodiments, the system, methods and the computer readable storage medium automatically identify the various (stages) types of sleep during an individual's sleep periods that include periods of REM sleep, deep sleep, and light sleep and that are indicative of the individual's overall well-being and health.