Bio-Information Estimation Using Dynamic Adjustment Coefficients
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Solution Overview
Problem
Current bio-information estimation methods, particularly for blood pressure, face challenges in accuracy and reliability due to variations in individual characteristics and environmental factors, leading to inconsistencies in bio-signal measurements.
Innovation Solution
An apparatus and method that utilize a sensor to measure bio-signals and a processor to obtain features, apply an adjustment coefficient based on bio-information variation, and estimate bio-information by adjusting the scale factor using a defined adjustment coefficient function, ensuring the estimated values are closer to reference values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed scale factor is used to convert bio-signal features to bio-information, then the estimation process is simple and fast, but the accuracy deteriorates due to individual and environmental variations
Solution Approach 1:
The patent applies dynamics by replacing the fixed scale factor with a dynamic adjustment coefficient that varies based on bio-information variation. The adjustment coefficient is obtained through a function that processes the bio-information variation, allowing the scaling factor to adapt to individual characteristics and environmental conditions, thereby improving measurement precision without requiring complex manual calibration for each user.
Solution Approach 2:
The patent implements feedback by using the bio-information variation (the difference between current and reference bio-information) to determine the adjustment coefficient. This feedback loop allows the system to continuously refine its estimation by adjusting the scale factor based on the actual variation observed, improving accuracy while maintaining automated operation.
2Measurement precision
If an adjustment coefficient function is applied to adapt to individual variations, then measurement precision improves, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-defining the adjustment coefficient function that processes bio-information variation. This function is prepared in advance and can be executed efficiently during actual measurements. The function takes the bio-information variation as input and outputs the corresponding adjustment coefficient, enabling rapid adaptation without requiring complex real-time calculations or manual intervention.
3Adaptability or versatility
If the adjustment coefficient is obtained based on bio-information variation, then adaptability to environmental factors improves, but device complexity increases
Solution Approach 1:
The patent applies self-service by enabling the system to automatically determine the adjustment coefficient based on the bio-information variation it measures. The adjustment coefficient function processes the variation data and generates appropriate scaling factors without requiring external intervention or manual calibration. This self-adjusting mechanism improves adaptability to environmental factors while keeping the processing complexity manageable through automated functions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of bio-information estimation by adaptively adjusting for individual and environmental variations, improving the reliability of blood pressure and other bio-parameter measurements.
Implementation Method 1
a sensor configured to measure a bio-signal from an object
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
An apparatus for estimating bio-information includes a sensor configured to measure a bio-signal from an object, and a processor configured to obtain a feature based on the measured bio-signal, obtain a bio-information variation based on the obtained feature, obtain an adjustment coefficient based on the obtained bio-information variation, and estimate the bio-information by applying the obtained adjustment coefficient to the obtained bio-information variation.