Sleep and Grind Data Comparison Using Splint Presence Alignment
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Solution Overview
Problem
Existing wearable sleep tracking devices fail to effectively display relationships between bruxism and sleep patterns, making it difficult for individuals with TMD and bruxism to understand the impact of dental splints on their sleep and grinding habits.
Innovation Solution
Time-aligning sleep data from a wearable heart rate sensor with grind data from a wearable motion sensor to display the relationship between sleep stages and grinding events, allowing for graphical representation and comparison with and without a dental splint.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sleep data and grind data are collected separately without integration, then data collection is simple, but the relationship between bruxism and sleep patterns cannot be effectively displayed
Solution Approach 1:
The patent combines sleep data from a wearable heart rate sensor with grind data from a wearable motion sensor into a unified display system. The system merges these separate data streams and presents them together on a single display device, enabling users to view the relationship between sleep stages and grinding events simultaneously without managing multiple separate systems.
Solution Approach 2:
The patent introduces a computer device as an intermediary that receives data from both the heart rate sensor and motion sensor, processes the data alignment, and generates the integrated display. This intermediary handles the complex data fusion and synchronization tasks, shielding users from the underlying system complexity while delivering comprehensive relationship information.
2Measurement precision
If sleep data and grind data are time-aligned and integrated, then the relationship between sleep stages and grinding events can be displayed, but data processing complexity increases
Solution Approach 1:
The system performs preliminary time-alignment processing of sleep data and grind data before display generation. By pre-synchronizing the temporal references of both data streams and establishing a common time baseline in advance, the system achieves precise temporal alignment without adding complexity to the real-time display generation process.
3Loss of information
If detailed sleep stage-specific grind data is displayed, then users gain comprehensive insights into bruxism patterns, but the display becomes more complex and harder to interpret
Solution Approach 1:
The patent segments grind data by sleep stage, presenting grinding event counts and patterns specific to each sleep stage (light sleep, deep sleep, REM sleep). This segmentation organizes detailed information into distinct, manageable categories that correspond to physiologically meaningful sleep stages, making comprehensive data easier to interpret.
Solution Approach 2:
The display provides different levels of detail for different sleep stages based on their relevance to bruxism. The system emphasizes information about grinding events during specific sleep stages where they are most clinically significant, while still maintaining the complete dataset. This localized emphasis on quality information improves interpretability without losing overall detail.
Data Source
AI summary
A method for displaying sleep and grind data involves displaying, on a display of a computer device, a comparison between 1) sleep data and grind data corresponding to a period when a dental splint was not being used by a person, and 2) sleep data and grind data corresponding to a period when a dental splint was being used by the person, wherein the sleep data was generated from heart rate data collected from a wearable heart rate sensor and is associated with a splint presence indicator (SPI) that corresponds to when the heart rate data was collected from the wearable heart rate sensor, the grind data was generated from motion data collected from a wearable motion sensor and is associated with an SPI that corresponds to when the motion data was collected from the wearable motion sensor, and the comparison is generated using the associated SPIs.