Physiological Data Discriminator for Subject Identification Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing electrocardiography systems face accuracy issues due to errors in subject information input, leading to incorrect association of physiological data with the wrong subjects, affecting the reliability of examinations.
Innovation Solution
A subject discriminating device and method that acquire and compare physiological data sets from different time points to generate a discriminator, calculating similarity indices to determine if the data sets originate from the same subject, thereby improving data association accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual subject information input is used in electrocardiography systems, then the system operation is simple and ease of use is maintained, but subject identification accuracy deteriorates due to input errors
Solution Approach 1:
The patent replaces manual subject information input (mechanical/system operation) with automatic physiological information-based identification. The discriminator automatically compares physiological data patterns to identify subjects, eliminating manual input errors while maintaining system usability through automated subject discrimination based on electrocardiogram or other physiological signal patterns.
2Reliability
If physiological information is recorded without verification, then the data acquisition process is efficient and productivity is maintained, but data association reliability deteriorates due to incorrect subject matching
Solution Approach 1:
The patent performs preliminary subject identification verification by acquiring physiological information and using the discriminator to verify subject identity before recording the actual examination data. This preliminary check ensures correct subject association while maintaining overall process efficiency, as the verification integrates seamlessly into the existing data acquisition workflow without requiring separate manual verification steps.
3Measurement precision
If a discriminator based on physiological information is introduced, then subject identification accuracy is improved, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The patent creates a discriminative model (discriminator) that learns from training data to replicate accurate subject identification patterns. The discriminator copies successful identification patterns from trained physiological data, enabling accurate subject discrimination without requiring complex real-time analysis of all raw physiological signals, thus balancing accuracy with processing complexity.
Data Source
AI summary
A subject discriminating device method: acquiring a first data set corresponding to change of physiological information and a second data set corresponding to change of the physiological information acquired at a different timing; generating a discriminator having learned one of the first data set and the second data set as training data; calculating a degree of similarity using input information for a data set which is the first data set or the second data set and has not been used to generate the discriminator and first output information which is obtained by inputting the data set which is not used to generate the discriminator to the discriminator; determining whether the first data set and the second data set have been acquired from a same subject based on the degree of similarity; and outputting an output signal corresponding to a result of determination.