Posture-Dependent Cardiac Event Detection via Dynamic Threshold Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current medical devices for monitoring cardiovascular conditions, particularly ischemia, face challenges in handling heart rate dependence, leading to inconveniences and inefficiencies in detection accuracy.
Innovation Solution
A system comprising an implanted cardiac diagnostic device with electronic circuitry that detects cardiac events like acute myocardial infarction, using subcutaneous electrodes and processing electrogram signals to compute waveform features, averaging, and filtering to eliminate noise, allowing for wireless communication and alerting patients to potential events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If intracardiac electrodes are used to provide strong signals, then signal amplitude is improved, but device complexity and invasiveness worsen
Solution Approach 1:
The patent uses subcutaneous electrodes that record electrograms from the body surface, creating a copy of the intracardiac electrical activity without requiring direct intracardiac contact. This approach maintains diagnostic capability while avoiding the complexities of intracardiac electrode implantation
Solution Approach 2:
The patent introduces skin electrodes as an intermediary between the external monitoring system and the heart's electrical activity. These electrodes capture the electrical signals through the body tissues, serving as a non-invasive mediator that eliminates the need for direct intracardiac electrode placement
2Ease of operation
If subcutaneous electrodes are used to reduce invasiveness, then ease of operation is improved, but signal amplitude worsens
Solution Approach 1:
The patent implements dynamic threshold adjustment based on heart rate zones. The detection thresholds are not fixed but adapt dynamically to the patient's current heart rate, allowing the system to maintain detection sensitivity across varying signal amplitudes and heart rate conditions
Solution Approach 2:
The patent changes the detection parameters (thresholds) based on heart rate zones. By adjusting the thresholds according to the current heart rate, the system compensates for variations in signal amplitude and maintains effective detection without requiring higher signal strength
3Measurement precision
If heart rate dependent thresholds are used to improve detection accuracy, then measurement precision is improved, but device complexity worsens
Solution Approach 1:
The patent implements dynamic threshold adjustment based on heart rate zones. The detection thresholds are not fixed but adapt dynamically to the patient's current heart rate, allowing the system to maintain detection sensitivity across varying signal amplitudes and heart rate conditions
Solution Approach 2:
The patent pre-defines multiple heart rate zones with associated thresholds before actual monitoring begins. This preliminary configuration allows the device to quickly switch between pre-calculated thresholds based on the current heart rate, reducing the complexity of real-time threshold calculation while maintaining detection accuracy
4Reliability
If persistence criteria are applied to reduce false alarms, then reliability is improved, but loss of time worsens
Solution Approach 1:
The patent implements dynamic adjustment of persistence requirements based on the current heart rate zone. When the heart rate is in a zone where ischemia is more likely, the persistence requirement is reduced, allowing faster detection. When the heart rate is in a zone where false alarms are more common, the persistence requirement is increased to maintain reliability
Solution Approach 2:
The patent changes the persistence parameter (number of consecutive beats required) based on the current heart rate zone. This dynamic parameter adjustment allows the system to balance between early detection and false alarm reduction by adapting the persistence requirement to the current physiological context
Data Source
AI summary
A device for detecting a cardiac event is disclosed. Detection of an event is based on a test applied to a parameter whose value varies according to heart rate. Both the parameter value and heart rate (RR interval) values are filtered with an exponential average filter. The filtered parameter value and heart rate values are stored as separate datasets corresponding to particular body postures. Upper and lower boundary values and detection thresholds of the parameter are computed for each of the datasets. The test to detect the cardiac event depends on the heart rate and the difference between the parameter's value and a corresponding detection threshold.