Multichannel Heart Sound Detection Using Covariance Alignment
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Solution Overview
Problem
Traditional cardiac rhythm management devices rely on electrical signals for heart sound detection, which are prone to noise and errors, limiting their ability to produce accurate combined heart sound signals without signal filtering and processing power constraints.
Innovation Solution
A system that combines heart sound signals from multiple axes without reference to electrical heart signals, using covariance analysis to align and produce a combined heart sound signal, reducing the need for R wave detection and enhancing signal-to-noise ratio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional CRM devices use electrical signals for heart sound detection, then heart sound information can be obtained, but the detection is prone to noise and errors
Solution Approach 1:
The patent replaces electrical signal-based heart sound detection with mechanical vibration detection using accelerometers. The accelerometers detect mechanical vibrations of the heart directly, avoiding the noise and errors inherent in electrical signal processing. This substitution of detection methodology fundamentally resolves the noise problem associated with traditional electrical signal approaches.
Solution Approach 2:
The patent combines signals from multiple accelerometers positioned at different locations to produce a composite heart sound signal. By merging multiple mechanical vibration signals, the system achieves better signal-to-noise ratio and more accurate heart sound detection compared to single-sensor electrical methods.
2Measurement precision
If signal filtering and processing are applied to improve heart sound detection accuracy, then detection precision improves, but processing power requirements increase
Solution Approach 1:
The patent performs preliminary signal alignment using covariance analysis before combining accelerometer signals. By pre-aligning the signals based on their statistical relationships, the system reduces the need for complex post-processing filtering and analysis, thereby lowering overall processing power requirements while maintaining detection accuracy.
3Adaptability or versatility
If R wave detection components are included in the device, then electrical signal processing can be performed, but device size and complexity increase
Solution Approach 1:
The patent extracts and eliminates the R wave detection components from the device by replacing the entire electrical signal processing approach with mechanical vibration detection using accelerometers. This removal of unnecessary components simplifies the device architecture, reduces size, and lowers complexity while maintaining heart sound detection functionality.
4Measurement precision
If multiple accelerometers are used to produce combined heart sound signals, then signal-to-noise ratio improves, but device complexity increases
Solution Approach 1:
The patent designs the accelerometer system where each sensor serves multiple functions: detecting mechanical vibrations, providing spatial information for signal alignment, and contributing to the composite heart sound signal. This multi-functionality allows the use of multiple accelerometers to improve signal-to-noise ratio without proportionally increasing device complexity, as the same components perform multiple detection roles.
Data Source
AI summary
This document discusses, among other things, systems and methods to produce a combined heart sound signal of a patient using a first signal including heart sound information over a first physiologic interval and a second signal including heart sound information over the first physiologic interval.