HRV Data Preprocessing Using Variance and RR Interval Filtering
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Solution Overview
Problem
Conventional HRV signal data sources contain abnormal data due to issues like insufficient accuracy of collection devices and significant short-term changes in emotions or movements, affecting the accuracy of disease prediction based on HRV data features.
Innovation Solution
An HRV-data preprocessing method that includes determining target peaks, calculating variance, filtering based on variance and heartbeat time intervals, and performing feature extraction on stable HRV data to exclude abnormal data, ensuring high accuracy and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feature extraction is directly performed on raw HRV data, then the processing speed is fast, but the accuracy of disease prediction is low due to abnormal data and interference
Solution Approach 1:
The patent segments the HRV data processing into distinct stages: peak detection, variance calculation, RR interval analysis, and feature extraction. Each stage handles specific aspects of data quality, allowing systematic filtering of abnormal data while maintaining organized and manageable processing steps
Solution Approach 2:
The patent performs preliminary filtering actions before feature extraction by calculating variance of peak data and analyzing RR intervals. This preliminary processing removes abnormal data points and interference early in the pipeline, ensuring that only clean data proceeds to feature extraction and disease prediction
2Measurement precision
If conventional collection devices are used, then the device complexity is low, but the accuracy of HRV data is insufficient due to device limitations and external interference
Solution Approach 1:
The patent introduces intermediate processing steps between data collection and final analysis. The variance calculation and RR interval analysis act as intermediary filters that mediate between raw sensor data and feature extraction, improving data quality without requiring more complex hardware
Solution Approach 2:
The patent transforms the raw HRV data into different parameter representations through variance calculation and RR interval analysis. By changing the parameter form of the data, the system can identify and filter abnormal patterns that are not apparent in the original signal, thereby improving measurement precision
Data Source
AI summary
Provided are an HRV-data preprocessing method and apparatus, and an electronic device. The method includes: obtaining HRV data corresponding to a sliding window; determining a variance of a plurality of target peaks corresponding to the HRV data, and determining HRV data having the variance that falls within a predetermined variance range as first target HRV data; determining an RR interval sequence of the first target HRV data based on the plurality of target peaks, determining whether each RR interval in the RR interval sequence falls within a predetermined heartbeat time interval range, and determining second target HRV data; and extracting a time-domain feature, a frequency-domain feature, and a nonlinear feature of the second target HRV data.