Heart Rate Calculator Reduces Overcounting in WCD ECG Signals
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Solution Overview
Problem
Wearable Cardioverter Defibrillator (WCD) systems face challenges in accurately measuring heart rate due to electrical noise and erroneous measurements caused by large T-waves and bigeminy, leading to potential overcounting and incorrect heart rate determinations.
Innovation Solution
A Heart Rate (HR) calculator with reduced overcounting, integrated into WCD systems, uses ECG sensors and a processor to classify ECG signals, detect QRS complexes, and compare mean intervals to adjust HR calculations, avoiding double counting and bigeminy errors by implementing algorithms that differentiate between normal and abnormal rhythms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a WCD system uses ECG sensors to monitor heart rate, then the patient's heart rate can be continuously monitored, but electrical noise and large T-waves cause erroneous measurements and overcounting
Solution Approach 1:
The patent segments the ECG signal analysis by dividing intervals into odd and even groups, analyzing each separately to detect and correct overcounting errors caused by large T-waves misidentified as QRS complexes
Solution Approach 2:
The system implements feedback by comparing mean odd intervals with mean even intervals, using the difference as an indicator of overcounting to adjust the heart rate calculation accordingly
2Productivity
If the HR monitor counts all detected intervals, then the calculation is simple, but it leads to overcounting when large T-waves are misidentified as QRS complexes
Solution Approach 1:
The patent performs preliminary action by comparing odd and even interval means before finalizing the heart rate calculation, identifying and correcting potential overcounting errors in advance
Solution Approach 2:
The system changes the calculation parameter by using different weighting factors for odd and even intervals when overcounting is detected, adjusting the heart rate formula from 60/mean_interval to 60/((odd_mean + even_mean)/2)
3Reliability
If the system detects every ECG peak as a QRS complex, then no beats are missed, but bigeminy causes every other beat to be detected erroneously
Solution Approach 1:
The system uses feedback by comparing the distribution of odd and even intervals to detect bigeminy patterns, where systematic differences indicate every other beat is being erroneously detected
Data Source
AI summary
A heart rate (HR) monitor for use in a medical device configurable to measure a patient's ECG such as, for example, a WCD system. Embodiments can include an ECG sensor and a processor configured with classification criteria to classify a received ECG signal into one of a plurality of ECG rhythm types each with a corresponding algorithm to determine the patient's heart rate. The processor uses the classification criteria to identify the ECG signal's type and determine a heart rate of the patient using the corresponding algorithm. The HR monitor is configurable to avoid overcounting of erroneous measurements of R-R intervals that can result from large T-waves and/or bigeminy by comparing the mean of even R-R intervals with the mean of odd R-R intervals. If the means are significantly different double counting or bigeminy is indicated and the HR calculation is adjusted accordingly.