Adaptive sleep system using data analytics and learning techniques to improve individual sleep conditions
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Solution Overview
Problem
Current sleep solutions are static and fail to adapt to individual sleep dynamics, environmental changes, and personal preferences, 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 analyzing user data and adjusting the bed environment in real-time, enabling personalized and adaptive sleep experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static sleep solutions (beds, cushions, pillows) with fixed characteristics are used, then manufacturing and operation are simple, but they cannot adapt to individual sleep dynamics, environmental changes, and personal preferences, leading to suboptimal sleep quality
Solution Approach 1:
The patent applies dynamics by transforming static sleep surfaces into dynamic, adjustable systems. The bed frame includes adjustable support surfaces that can change position and firmness, while the cushion system incorporates inflatable bladders that can dynamically adjust to user weight and sleep position. This allows the system to adapt to individual sleep dynamics, environmental changes, and personal preferences, directly resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The system incorporates sensors that automatically detect user presence, weight, and sleep position, then autonomously adjust cushion inflation and bed support without user intervention. The microcontroller processes sensor data and controls the inflatable cushion system to self-regulate pressure distribution. This self-service capability enhances adaptability while minimizing the operational complexity for users.
2Reliability
If side sleeping position is maintained to improve breathing, then breathing issues are reduced, but comfort deteriorates as people age and find it harder to sleep comfortably on their sides
Solution Approach 1:
The patent applies local quality by providing differentiated support zones within the sleeping surface. The inflatable cushion system creates localized pressure relief at critical areas (shoulders, hips, neck) while maintaining side-sleeping position. The microcontroller independently controls different cushion zones to optimize support distribution, allowing the user to maintain breathing-beneficial side position while achieving age-appropriate comfort through localized adaptation.
Solution Approach 2:
The system dynamically changes physical parameters (pressure, firmness, position) of the sleep surface to maintain both breathing improvement and comfort. Sensors detect sleep position and breathing patterns, then the microcontroller adjusts cushion inflation parameters in real-time. This allows the system to optimize the balance between maintaining side-sleeping for breathing and adjusting firmness/position for comfort as users age.
3Productivity
If data collection from multiple sensors is implemented to personalize sleep experience, then sleep quality optimization improves, but device complexity and data processing requirements increase
Solution Approach 1:
The patent applies universality by designing a multi-functional integrated system where a single microcontroller handles multiple sensor inputs (pressure sensors, motion sensors, temperature sensors) and coordinates multiple output devices (inflatable cushion bladders, bed frame actuators). This centralized control architecture consolidates data processing complexity into a single processing unit while enabling comprehensive sleep quality optimization through coordinated multi-functional operation.
Solution Approach 2:
The system merges multiple data collection and control functions into an integrated architecture. Pressure sensors, motion sensors, and temperature sensors are combined in a unified sensing network, while the microcontroller integrates data processing, decision-making, and actuator control. The inflatable cushion system and adjustable bed frame are merged into a coordinated support system. This consolidation reduces overall system complexity while enhancing sleep quality optimization capabilities.
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.