Wearable Acoustic-ECG Sensing for VT Verification
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Solution Overview
Problem
Conventional medical devices that monitor the cardiopulmonary system face challenges in accurately determining cardiac cycle characteristics due to electrical noise and electrode fall-off, leading to variable signal quality and subject-specific variations, which can hinder the detection of cardiopulmonary anomalies.
Innovation Solution
Integration of acoustic sensors with electrocardiogram electrodes and processors to enhance cardiopulmonary data analysis, allowing for improved detection and verification of anomalies such as supraventricular tachycardia, ventricular tachycardia, and respiratory issues by combining acoustic and electrode signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional ECG sensing electrodes are used to monitor cardiopulmonary system, then the device can obtain electrical signals from the body, but electrical noise and electrode fall-off frequently degrade the quality of the ECG signal
Solution Approach 1:
The patent combines acoustic sensor data with ECG electrode signals to detect and verify cardiopulmonary anomalies. The acoustic sensor detects heart sounds and breath sounds, which are then processed alongside ECG signals to improve detection accuracy and reduce false positives caused by electrical noise or electrode fall-off.
2Measurement precision
If ECG signals are used to detect cardiopulmonary anomalies, then the system can identify potential issues, but the characteristics of ECG signals vary from subject to subject due to factors such as the subject's state of health and individual physiology
Solution Approach 1:
The acoustic sensor serves as an intermediary modality that provides additional verification for ECG-detected anomalies. By detecting heart sounds and breath sounds acoustically, the system can verify ECG findings and account for subject-specific variations in ECG signal characteristics, thereby improving overall measurement precision.
3Measurement precision
If acoustic sensors are integrated with ECG electrodes to verify cardiopulmonary anomalies, then the accuracy and precision of detecting anomalies is enhanced, but the device complexity increases
Solution Approach 1:
The acoustic sensor is designed to perform multiple functions: detecting heart sounds, detecting breath sounds, and verifying ECG-detected anomalies. This multi-functionality justifies the added device complexity by providing comprehensive cardiopulmonary monitoring and verification capabilities in a single integrated component.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy and precision of detecting cardiopulmonary anomalies, enabling differentiated treatment based on the severity of the condition and reducing false positives by utilizing acoustic data to verify ECG signals.
Implementation Method 1
obtain an acoustic signal from an acoustic sensor
Data Source
AI summary
An ambulatory medical device configured to be worn on a patient's body includes at least one electrocardiogram (ECG) electrode configured to sense cardiac activity, at least one acoustic sensor configured to detect one or more heart sounds, and at least one processor. The at least one processor is configured to implement a cardiopulmonary function analyzer to detect a suspected tachyarrhythmia based on an analysis of ECG signal(s) and verify the suspected tachyarrhythmia as a ventricular tachycardia (VT) event by analyzing acoustic signal(s) to distinguish the VT event from a supraventricular tachycardia (SVT) event. Said analysis includes determining an intensity and/or a beat-to-beat variability of a first heart sound (S1). The at least one processor verifies the suspected tachyarrhythmia as the VT event when the intensity of the S1 sound is below a predetermined intensity threshold or when the beat-to-beat variability of the S1 sound is above a predetermined variability threshold.