Bio-Signal Failure Prediction Using Pulse Count and Signal Quality
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Solution Overview
Problem
Existing bio-signal measurement methods struggle to accurately determine the success or failure of complex health index estimation due to the influence of brief movements or noise, especially when measurements are taken over extended periods, making it difficult to predict whether bio-information estimation will fail before the time limit is reached.
Innovation Solution
A method and apparatus that utilize failure prediction indicators, such as current and maximum number of pulses, signal quality, and heart rate analysis, to predict the likelihood of bio-information estimation failure before the time limit is reached, using a processor to execute algorithms that compare these indicators with predefined thresholds to output failure flags and guide re-measurement if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If bio-signals are measured for a longer period to reduce the impact of brief movements or noise, then measurement accuracy is improved, but it becomes difficult to determine success or failure of the measurement in a timely manner
Solution Approach 1:
The system performs preliminary analysis of bio-signal characteristics (pulse count, signal quality, heart rate) during the measurement process to predict the final outcome before the measurement period ends. This allows early determination of whether the measurement will succeed or fail, enabling timely re-measurement decisions without waiting for the complete measurement period to elapse.
Solution Approach 2:
The system continuously monitors bio-signal parameters during measurement and provides feedback through failure prediction indicators. By comparing real-time signal characteristics against expected patterns and thresholds, the system can predict measurement outcomes and provide feedback on whether re-measurement is needed, reducing the time loss associated with delayed result determination.
2Reliability
If bio-signals are measured for a longer period to ensure reliable complex health index estimation, then reliability of health index is improved, but the complexity of determining measurement success or failure increases
Solution Approach 1:
The system segments the complex determination of measurement success into multiple simpler failure prediction indicators: pulse count assessment, signal quality evaluation, and heart rate analysis. Each indicator is evaluated independently against specific criteria, and their combined results determine the overall measurement outcome. This segmentation simplifies the complexity of determining measurement success while maintaining reliability through comprehensive multi-factor assessment.
3Measurement precision
If measurement time is extended to obtain sufficient pulses for accurate bio-information estimation, then estimation accuracy is improved, but the time cost increases
Solution Approach 1:
The system performs preliminary assessment of the rate of pulse acquisition and signal quality during the measurement process. By predicting the maximum number of pulses that can be obtained and evaluating current signal quality trends, the system can determine whether the measurement is on track to meet accuracy requirements or if re-measurement should be initiated early, thereby optimizing the measurement duration without sacrificing estimation accuracy.
Data Source
AI summary
A method for predicting failure of bio-information estimation is provided. The method for predicting failure of bio-information estimation includes: receiving a bio-signal; obtaining failure prediction indicators from the bio-signal that is received until a current time, the failure prediction indicators comprising at least one of a current number of pulses of the bio-signal until the current time, a current signal quality of the bio-signal until the current time, a maximum number of pulses of the bio-signal that are predicted to be measured until a time limit, and a maximum signal quality of the bio-signal that is predicted to be measured until the time limit; and predicting whether bio-information estimation will fail based on the failure prediction indicators before the time limit is elapsed.