Adaptive sleep system using data analytics and learning techniques to improve individual sleep conditions based on a therapy profile
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current sleep solutions are static and fail to adapt to individual sleep needs and environmental changes, leading to suboptimal sleep quality, particularly for individuals with breathing issues like snoring and apnea, as they age and find it harder to sleep comfortably on their sides.
Innovation Solution
A dynamic sleep system integrating sensors and actuators to detect and adjust sleep surface conditions, such as pressure and temperature, using machine learning algorithms to optimize sleep quality by dynamically adjusting the bed environment based on real-time data from sensors and user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static sleep solutions (beds, cushions, pillows) with fixed characteristics are used, then device complexity is reduced and ease of manufacture is improved, but adaptability to individual sleep needs and environmental changes deteriorates
Solution Approach 1:
The patent implements a dynamic sleep system where the sleep surface characteristics (firmness, support, temperature) can be adjusted in real-time based on sensor feedback and machine learning algorithms. The system transitions from static fixed characteristics to dynamic adaptive characteristics, allowing the bed to respond to user needs throughout the sleep cycle.
Solution Approach 2:
The system employs machine learning algorithms that automatically analyze sensor data and adjust sleep surface characteristics without user intervention. The closed-loop system self-optimizes by detecting sleep stages, body position, and environmental conditions, then autonomously modifying support and temperature settings.
2Reliability
If static sleep solutions with fixed characteristics are used, then manufacturing and operation are simplified, but sleep quality for individuals with breathing issues deteriorates
Solution Approach 1:
The patent incorporates multiple sensors (pressure, temperature, motion, breathing detection) that continuously monitor sleep conditions and provide feedback to the control system. This feedback loop enables the system to detect breathing issues, apnea events, and snoring, then automatically adjust sleep surface characteristics to improve breathing and sleep quality.
Solution Approach 2:
The system replaces manual adjustment mechanisms with automated electro-mechanical actuators and control systems. Instead of requiring users to manually adjust pillows or positioning, the system uses motors and actuators to dynamically modify sleep surface characteristics based on sensor data and algorithmic decisions.
3Adaptability or versatility
If static sleep solutions are used, then the system remains simple and cost-effective, but the ability to provide personalized support deteriorates
Solution Approach 1:
The patent implements zone-based control where different regions of the sleep surface can have independently adjusted characteristics. Sensors detect local pressure points, body position, and temperature in specific zones, allowing the system to provide customized support to different body parts (head, neck, shoulders, back, legs) simultaneously with different firmness and temperature settings.
Solution Approach 2:
The system dynamically changes physical parameters of the sleep surface including firmness, support distribution, and temperature in different zones. Machine learning algorithms analyze individual user data to optimize these parameters for personalized sleep profiles, adapting to each user's body type, sleep preferences, and health conditions.
4Productivity
If static sleep solutions are used, then device complexity is minimized, but the system's ability to respond to environmental changes and sleep stages deteriorates
Solution Approach 1:
The patent implements periodic monitoring and adjustment cycles where sensors continuously scan for changes in sleep stage, body position, and environmental conditions. The system operates in cycles, detecting changes and making adjustments at appropriate intervals throughout the sleep night, synchronizing with the user's natural sleep rhythm and circadian patterns.
Data Source
AI summary
A bed integrates sensors and other inputs to detect specific sleep environment conditions including point-specific pressure and/or temperature conditions. The bed includes a controller for commanding actuator or other devices to adjust these conditions. The controller may do so based on reference patterns for conditions and profiles of desired conditions. Information regarding the conditions may be provided to a remote computer, which may analyze the conditions and provide revised profiles of desired conditions.