Condition-Based ECG Filtering for CPR Artifact Suppression
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Solution Overview
Problem
Conventional AEDs struggle with CPR-induced artifacts in ECG readings, leading to inaccurate shock versus non-shock classifications due to the destruction of waveforms, necessitating CPR interruptions that worsen ischemic injury and reduce survival rates in out-of-hospital cardiac arrest patients.
Innovation Solution
A condition-based filtering method using stop-band filters is applied to ECG signals to suppress CPR artifacts, allowing accurate shock/no-shock decisions without requiring additional reference signals, by activating filters based on frequency-wise locations in the power spectrum.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional AEDs use rhythm classification algorithms to make shock decisions, then automated shock/no-shock decisions can be made, but CPR artifacts destroy waveform morphology leading to inaccurate classifications
Solution Approach 1:
The patent introduces an intermediary signal processing system that includes a stop-band filter and adaptive filter as mediators between the raw ECG signal and the rhythm classification algorithm. These filters act as intermediaries to remove CPR artifacts from the ECG signal, allowing the classification algorithm to work accurately despite the presence of chest compression artifacts. The filter system processes the signal through multiple stages: initial filtering, power spectrum analysis, adaptive filter adjustment, and final filtered signal generation for classification.
2Measurement precision
If CPR interruptions are performed to acquire artifact-free ECGs, then accurate rhythm analysis can be performed, but ischemic injury increases and survival rate decreases
Solution Approach 1:
The patent replaces the mechanical approach of physically interrupting CPR to obtain clean ECG signals with an electronic signal processing solution. Instead of stopping chest compressions to get artifact-free signals, the system uses digital signal processing techniques (stop-band filters and adaptive filters) to remove artifacts from the continuous ECG signal. This substitution allows CPR to continue without interruption while still achieving accurate rhythm analysis, thereby improving patient survival rates.
3Object-generated harmful factors
If existing filtering methods using Kalman filters and adaptive filtering are used, then CPR artifacts can be suppressed, but additional reference signals are required which most AEDs lack
Solution Approach 1:
The patent implements a self-service filtering system that uses only the ECG signal itself as input, without requiring external reference signals from accelerometers or other sensors. The system performs self-processing by analyzing the power spectrum of the ECG signal to identify CPR artifact frequencies and automatically adjusting filter parameters accordingly. This self-service approach allows standard AEDs with basic ECG capability to perform artifact suppression without adding complex hardware, making the solution widely applicable to existing devices.
Data Source
AI summary
Methods, systems, and apparatuses are described for automated external defibrillation for determining shock/no-shock decisions based on ECG readings taken when a patient is undergoing cardiopulmonary resuscitation (CPR). A device may filter an ECG signal of a patient to reduce artifacts from the signal caused by CPR being performed on the patient. The device may use the filtered ECG signal to determine whether to deliver a therapeutic shock to a patient even if the patient is undergoing CPR.