Sleep Platform with Localized Pressure Adjustment for Adaptive Comfort
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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 difficult to sleep comfortably in the side position.
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 in real-time, based on user data and analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static sleep solutions (beds, cushions, pillows) are used, then manufacturing simplicity is maintained, but adaptability to individual sleep needs and environmental changes deteriorates
Solution Approach 1:
The patent implements a dynamic sleep system where the sleep surface continuously adjusts its characteristics (firmness, support, temperature) in real-time based on sensor feedback and machine learning algorithms. This transforms the static bed into a dynamic system that adapts to changing sleep conditions, body positions, and environmental factors throughout the night.
Solution Approach 2:
The system employs machine learning algorithms that enable the bed to automatically learn and adapt to individual user preferences and needs without manual intervention. The system self-adjusts by analyzing sensor data and making autonomous decisions about optimal sleep surface configuration, eliminating the need for users to manually adjust settings.
2Reliability
If static sleep solutions are used, then device complexity is reduced, but sleep quality for individuals with breathing issues deteriorates
Solution Approach 1:
The patent incorporates multiple sensors (pressure, temperature, motion) that continuously monitor sleep conditions and provide feedback to the control system. This feedback loop enables real-time detection of breathing issues, body position problems, and comfort deviations, allowing the system to automatically adjust the sleep surface to maintain optimal conditions for sleep quality.
Solution Approach 2:
The system replaces manual mechanical adjustment with automated electro-mechanical actuation controlled by machine learning algorithms. Motors and actuators dynamically adjust the sleep surface configuration based on digital signals from the control system, enabling precise and responsive adjustments that would be impossible with purely mechanical static solutions.
3Reliability
If personalized adaptive support is provided, then sleep quality improves, but manufacturing complexity increases
Solution Approach 1:
The sleep surface is divided into multiple independently controllable zones or segments, each with its own actuators and sensors. This segmentation allows different regions of the bed to be customized and adjusted independently based on local needs (e.g., head region for breathing support, torso region for alignment, leg region for circulation). The modular segmented design also facilitates easier manufacturing and assembly.
Solution Approach 2:
The patent designs a universal sleep system platform that can serve multiple functions and adapt to various user needs through software configuration rather than hardware customization. The same physical infrastructure (sensors, actuators, frame) supports different sleep profiles, therapeutic modes, and personalization scenarios, reducing manufacturing complexity while maintaining high adaptability.
Data Source
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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.