Physiological Data Integration via Environmental Validity Checks
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Solution Overview
Problem
Existing electronic devices face challenges in integrating and presenting physiological data from multiple devices effectively, leading to reduced readability and accuracy due to differences in measurement accuracy and frequency, as well as errors in selecting reference values and simultaneous measurement issues.
Innovation Solution
An electronic device and method that receive physiological data from multiple sources, determine the validity of the data based on measurement environment data, and generate integrated data by comparing valid data from different devices, prioritizing accurate measurements and displaying the integrated data for improved user understanding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all physiological data from multiple devices is presented at once, then data completeness is improved, but readability is reduced
Solution Approach 1:
The patent segments physiological data from multiple devices into separate categories or groups, allowing the system to maintain data completeness while improving readability by organizing information in a structured, non-overwhelming manner. Each device's data can be segmented into distinct sections with clear labeling.
Solution Approach 2:
The patent introduces additional organizational dimensions such as time stamps, device identifiers, and data validity markers to structure the presentation of physiological data. This multi-dimensional organization allows comprehensive data display while maintaining readability through hierarchical structuring.
2Quantity of substance
If physiological data from multiple devices with different measurement accuracies is integrated, then data availability is improved, but measurement precision is reduced
Solution Approach 1:
The patent applies local quality by assigning different weights or priorities to data from different devices based on their known measurement accuracies. High-accuracy devices contribute more significantly to the integrated result, while lower-accuracy devices provide supplementary information, maintaining overall data availability without compromising precision.
Solution Approach 2:
The patent changes parameters such as data weighting factors, confidence levels, and integration coefficients based on device characteristics and measurement conditions. This dynamic parameter adjustment allows the system to optimize the contribution of each device's data to the final integrated physiological assessment.
3Measurement precision
If data validity is strictly verified before integration, then measurement precision is improved, but device availability is reduced
Solution Approach 1:
The patent implements partial validation by applying different levels of strictness to validity checks based on device reliability, measurement type, and clinical context. Critical parameters undergo rigorous validation, while less critical measurements are accepted with minimal verification, balancing precision requirements with device availability.
Solution Approach 2:
The patent incorporates beforehand cushioning by establishing pre-defined validity thresholds, confidence intervals, and fallback mechanisms that allow the system to handle potentially invalid data gracefully. This preparation enables the system to maintain operation even when some data points fail strict validation, preserving device availability.
4Ease of operation
If reference value selection is simplified by choosing from available device data, then ease of operation is improved, but measurement precision is reduced
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors the quality and consistency of selected reference values, adjusting future selections based on performance outcomes. This automated feedback loop maintains ease of operation by eliminating manual intervention while improving precision through data-driven selection criteria.
Solution Approach 2:
The patent enables self-service by allowing the system to automatically select and validate reference values based on pre-established criteria without requiring user intervention. The system evaluates device performance, data quality, and measurement conditions to autonomously determine the most appropriate reference value, balancing operational simplicity with accuracy.
Data Source
AI summary
An electronic device is disclosed that includes: communication circuitry, a memory operatively coupled to a processor and storing instructions which, when executed, cause the processor to: receive first physiological data and second physiological data obtained by measuring a physiological state of a user's body, obtain measurement environment data for an environment where each of the first physiological data and the second physiological data is measured, determine validity of each of the first physiological data and the second physiological data based on at least a portion of the measurement environment data, generate integrated data of the first physiological data and the second physiological data based on at least one of comparing the first physiological data with the second physiological data and the measurement environment data, based on the first physiological data and the second physiological data being valid, and control a display to display the integrated data on the display.