Group Sleep Adjustment via Personalized Stimuli
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Solution Overview
Problem
Existing technologies lack the ability to effectively adjust the sleep habits of multiple users to achieve a common future goal by providing personalized and incremental sleep adjustments based on individual sleep profiles and patterns.
Innovation Solution
An apparatus comprising a processor and memory configured to determine sleep adjustments for a group of users by analyzing their sleep biosignals and awake profiles, and providing stimuli through remote output devices such as earphones or speakers to induce posture changes, audio, temperature, or vibratory stimuli to align with a target sleep outcome.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sleep monitoring and adjustment systems are implemented for multiple users, then sleep quality and alertness can be improved, but the device complexity and computational requirements increase significantly
Solution Approach 1:
The system segments the sleep adjustment process into distinct phases: monitoring phase (collecting biosignals during sleep), analysis phase (processing data to identify sleep patterns and issues), and adjustment phase (delivering targeted stimuli such as audio, temperature, or light interventions). This segmentation allows the complex system to manage multiple users efficiently by handling each user's sleep cycle in discrete, manageable stages rather than attempting simultaneous comprehensive control.
Solution Approach 2:
The system performs preliminary analysis of sleep profiles during the monitoring phase, identifying sleep patterns, disturbances, and individual characteristics before the adjustment phase begins. By pre-processing and pre-analyzing sleep data, the system prepares personalized adjustment strategies in advance, reducing real-time computational complexity while maintaining high sleep quality outcomes for multiple users.
2Adaptability or versatility
If personalized sleep adjustments are provided for each user, then individual sleep needs are met, but the system complexity and data processing requirements increase
Solution Approach 1:
The system applies local quality by tailoring sleep adjustments to each user's specific sleep profile, biosignals, and individual needs while using a unified platform architecture. Each user receives customized stimuli (audio frequencies, temperature adjustments, light timing) based on their unique sleep characteristics, but the underlying system uses common processing algorithms and data structures, allowing personalization without proportionally increasing overall system complexity.
Solution Approach 2:
The system employs universal processing algorithms and data structures that can handle multiple users simultaneously. The core architecture is designed to process sleep data from any number of users using the same fundamental methods, enabling the system to scale from one to many users without requiring fundamentally different approaches for each user, thus achieving versatility without linear complexity growth.
3Productivity
If sleep data from multiple users is analyzed to determine common goals, then group sleep outcomes can be improved, but the measurement and data processing difficulty increases
Solution Approach 1:
The system merges individual sleep data from multiple users to identify common sleep patterns, disturbances, and opportunities for improvement. By aggregating and analyzing collective sleep profiles, the system determines group-level goals and interventions that benefit multiple users simultaneously. This merging approach leverages the statistical power of large datasets to identify trends that would be difficult to detect in individual cases, improving group productivity while using efficient data aggregation techniques.
Data Source
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AI summary
An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: receive respective sleep profiles of a plurality of users, each sleep profile comprising recorded sleep phases of a sleep session of a respective user of the plurality of users, receive a target sleep outcome of the plurality of users; and based on the respective sleep profiles and the target sleep outcome, determine one or more respective sleep adjustments for provision to at least one of the respective plurality of users, the respective sleep adjustments comprising stimuli configured to attempt to adjust a respective user's sleep during one or more of the respective user's sleep session and a subsequent sleep session, in an attempt to achieve, at least in part, the target sleep outcome of the plurality of users.