Sleep Score Assessment System Using Reference Metric Comparison
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Solution Overview
Problem
Existing sleep monitoring systems fail to provide meaningful and quantifiable metrics for sleep quality and lack mechanisms to encourage healthy sleep habits.
Innovation Solution
A system and method that receive user data from sensors to determine sleep metrics, compare them to reference metrics from prior sessions, and generate a sleep session score value, which is presented to the user, along with deductions and interventions to improve sleep quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sleep monitoring systems only track basic sleep data, then device complexity is reduced, but the ability to provide meaningful and quantifiable sleep quality metrics is insufficient
Solution Approach 1:
The patent segments sleep quality assessment into multiple independent metrics (sleep efficiency, sleep duration, wakefulness periods, circadian rhythm alignment) rather than using a single complex metric. This allows the system to provide comprehensive sleep quality measurement while keeping each individual metric calculation manageable and interpretable.
Solution Approach 2:
The patent introduces an intermediary processing layer that transforms raw sensor data into meaningful sleep metrics through standardized algorithms. This intermediary layer handles the complexity of data interpretation, allowing the system to deliver precise sleep quality measurements without requiring the end user to understand the underlying complexity.
2Ease of operation
If sleep monitoring systems provide detailed sleep metrics, then sleep quality assessment is improved, but the ability to provide actionable mechanisms for encouraging healthy sleep habits is lacking
Solution Approach 1:
The patent implements a feedback mechanism that compares actual sleep metrics against target sleep metrics and provides actionable recommendations. The system analyzes deviations in sleep patterns and generates specific guidance (such as adjusting bedtime, optimizing sleep environment, or modifying pre-sleep routines) to help users achieve their sleep goals, making sleep improvement accessible and actionable.
Solution Approach 2:
The patent uses circadian rhythm analysis to determine optimal times for sleep and wakefulness in advance. By calculating personalized chronotypes and predicting ideal sleep windows before the user goes to bed, the system provides preliminary guidance that helps users proactively optimize their sleep schedules rather than reacting to poor sleep after the fact.
3Measurement precision
If sleep monitoring systems use multiple sensors and metrics, then sleep quality measurement accuracy is improved, but the system becomes more complex and harder to operate
Solution Approach 1:
The patent extracts and separates the complexity of multi-sensor data processing from the user interface. The system handles all sensor integration, data fusion, and metric calculation internally, presenting users with simplified, actionable insights and recommendations. This extraction of complexity allows accurate multi-metric measurement while maintaining ease of operation.
Data Source
AI summary
The present disclosure pertains to facilitating sleep improvement for a user. In a non-limiting embodiment, user data associated with a sleep session of a user is received from one or more sensors. Based on the user data, one or more sleep metrics associated with the sleep session are generated. One or more reference sleep metrics are determined based on prior user data obtained from one or more prior sleep sessions. One or more immediate values related to the sleep session is/are determined based on a comparison of the sleep metrics with the reference sleep metrics. A sleep session score value is generated based on the immediate values, and the sleep session score value and the sleep metrics are caused to be presented on via an output device.