Adaptive Sleep System Using Data Analytics and Learning Techniques to Improve Individual Sleep Conditions

Smart overview of the Invention

The patent describes an adaptive sleep system that integrates sensors and inputs to monitor sleep conditions such as pressure and temperature. The system features a controller that commands actuators to adjust these conditions, aiming to enhance sleep quality. The controller uses reference patterns and desired condition profiles, with data analyzed remotely to refine these profiles further.

Background

Sleep quality is influenced by various environmental and physiological factors. Poor sleep can negatively impact health and productivity. Sleep stages, including REM and non-REM phases, are crucial for restorative sleep. Factors like sleep position, pressure points, and temperature can affect these stages. Personalized sleep environments are necessary due to individual differences in body type and health conditions. Current static sleep solutions do not adapt throughout the sleep cycle, limiting their effectiveness.

Technological Advancements

Advances in computation have enabled the use of artificial intelligence and data analytics to improve systems like self-driving cars. This patent applies similar technologies to create a closed-loop system for sleep improvement. The system uses machine learning and data analysis to iteratively enhance control algorithms based on sensor feedback, aiming to personalize and optimize sleep conditions for individuals.

System Components

• Bed System: Incorporates sensors for detecting environmental and physiological conditions, actuators for dynamic adjustment, and a modular design for ease of use.
• Controller: Commands actuators based on sensor data and communicates with a remote computer for data analysis.
• Methods: Analyze user conditions, generate control signals to optimize the environment, and learn from user data to improve sleep quality.
• Network Architecture: Facilitates data analysis across user groups to refine control configurations.

Embodiments

The system may include a sleeping surface with adjustable components based on sensor feedback. It can control localized pressure and temperature settings, adapting them according to user therapy profiles. Data from multiple users is analyzed to update these profiles, ensuring personalized adjustments. The controller may also receive server-based information to enhance actuator operations further.