Environmental Sensor Sleep Analysis System
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Solution Overview
Problem
Current sleep monitoring technologies, such as wearables, face challenges with accuracy and user compliance due to irritation, dislodgment, and reliance on self-reporting, which are often inaccurate, and do not provide personalized recommendations to improve sleep quality.
Innovation Solution
A computer-implemented method using a sensor set including temperature, pressure, humidity, light, sound, thermal-imaging, and motion sensors to analyze sleep patterns and generate personalized recommendations for improving sleep outcomes, leveraging machine-learning models and user interfaces to provide actionable insights and feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wearables are attached to the person to capture sleep data, then sleep quality data can be collected, but the wearables become irritating and easily dislodged
Solution Approach 1:
The patent extracts the sensing function from wearable devices and places sensors in the environment (bed, room). Environmental sensors capture sleep data without requiring physical contact with the user, eliminating irritation and dislodgment issues while maintaining reliable data collection.
Solution Approach 2:
The patent introduces environmental sensors as intermediaries between the user and data collection. These sensors (temperature, humidity, light, sound, motion sensors in the bed and room) mediate the measurement process by capturing physiological and environmental data without direct contact with the user's body.
2Measurement precision
If wearables are used to monitor sleep, then movement and heartbeat data can be captured, but the data becomes inaccurate when users are merely inactive
Solution Approach 1:
The patent combines multiple sensor types (temperature, humidity, light, sound, motion sensors) to cross-validate sleep detection. By merging environmental context data with movement data, the system distinguishes between actual sleep and mere inactivity, improving measurement precision and reliability simultaneously.
Solution Approach 2:
The system uses feedback from multiple sensor sources to continuously refine sleep detection accuracy. Environmental conditions and movement patterns are cross-referenced to validate sleep state, correcting misclassifications and improving overall data accuracy.
3Loss of information
If self-reporting is used to supplement sleep data, then additional information can be gathered, but the data becomes notoriously inaccurate
Solution Approach 1:
The system makes sleep monitoring self-service by using automated environmental sensors to capture data without requiring user input. The sensors independently measure temperature, humidity, light, sound, and movement, eliminating the need for inaccurate self-reporting while maintaining complete sleep information.
4Measurement precision
If multiple sensors are deployed in the environment, then accurate sleep behavior analysis can be achieved, but the device complexity increases
Solution Approach 1:
The patent makes each sensor multi-functional by deploying them in the environmental context. The same temperature sensor monitors both room conditions and body temperature changes; motion sensors detect both user presence and sleep movements. This universality reduces the number of specialized sensors needed, managing complexity while maintaining precision.
Data Source
AI summary
A sleeping application receives initial sensor data from one or more sensors of a sensor set in a physical environment for a time period, wherein the sensor set includes at least one of a temperature sensor, a pressure sensor, a humidity sensor, a light sensor, a sound sensor, a thermal-imaging sensor, and a motion sensor. The sleeping application behavior patterns of a set of sleep events of a target subject based on the initial sensor data. The sleeping application generates a recommendation based on the behavior patterns to achieve a target outcome for a target subject in the physical environment. The sleeping application provides the recommendation.