Adaptive Heart Sound Tracking Algorithm for Medical Devices

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing heart sound recognition methods in medical devices are prone to errors due to noise interference, low signal-to-noise ratio, and incorrect peak detection, which can lead to inaccurate detection of cardiac events.

Innovation Solution

A medical-device system that includes a data receiver circuit to receive heart sound information and a heart sound recognition circuit to generate a representative heart sound segment. The system uses a time-based tracking algorithm to recognize heart sound components and evaluates a performance index to determine whether to switch to a spectral-based tracking algorithm for improved recognition.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional peak detection methods are used to recognize heart sound components, then the detection process is simple and fast, but the detection accuracy deteriorates due to noise interference and low signal-to-noise ratio

Engineering Contradiction:

Improveheart sound component detection accuracyVSAvoidrecognition algorithm complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system dynamically switches between time-based tracking algorithm and spectral-based tracking algorithm based on signal conditions. The time-based algorithm is used when signal quality is good, while the spectral-based algorithm is activated when noise interference is high, making the system adaptive to varying signal environments and improving detection accuracy without always requiring complex processing

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the processing parameters by switching between different algorithm types (time-domain vs frequency-domain analysis) depending on the signal-to-noise ratio and cardiac cycle characteristics. This parameter change allows the system to optimize detection accuracy for different signal conditions while managing computational complexity

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If spectral-based tracking algorithm is used to improve heart sound recognition accuracy, then the detection precision is improved, but the power consumption and computational complexity increase

Engineering Contradiction:

Improveheart sound component detection accuracyVSAvoiddevice power consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system dynamically selects the appropriate algorithm based on real-time signal quality assessment. The spectral-based algorithm is only activated when needed (low signal-to-noise ratio conditions), while the simpler time-based algorithm handles normal conditions, thus reducing average power consumption while maintaining high detection accuracy when required

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system applies the computationally intensive spectral-based algorithm only partially - specifically when signal quality metrics indicate poor detection conditions. This partial application of the complex algorithm reduces overall computational burden and power consumption while still achieving high detection precision when necessary

Inventive Principle:

Principle #16Partial or excessive action

3Reliability

If heart sound monitoring is performed continuously to detect cardiac events accurately, then the detection reliability is improved, but the false detection rate increases due to noise and incorrect peak identification

Engineering Contradiction:

Improvecardiac event detection reliabilityVSAvoidfalse detection rate

Core Design Contradiction:

ReliabilityVSLoss of information

Solution Approach 1:

The system uses feedback from signal quality assessment and detection performance to adjust the algorithm selection. When false detections occur or signal quality deteriorates, the system switches to the spectral-based algorithm which provides better noise rejection, thereby reducing false detection rate while maintaining high reliability through continuous monitoring and adaptive adjustment

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The dynamic algorithm switching mechanism allows the system to adapt to varying signal conditions in real-time. By transitioning between time-based and spectral-based algorithms based on detected signal characteristics, the system maintains high detection reliability while minimizing false positives caused by noise interference

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS20250160665A1Selectable heart sound tracking in heart failure

Publication Date: 2025.05.22 CARDIAC PACEMAKERS INC

AI summary

Systems and methods for recognizing and tracking heart sound components are disclosed. An exemplary medical-device system includes a data receiver to receive heart sound information, and a heart sound recognition circuit to generate a representative heart sound segment such as an ensemble average of a selected portion of heart sound segments. The heart sound recognition circuit recognizes a heart sound component from the representative heart sound segment using a time-based tracking algorithm, and evaluates a performance index of the time-based heart sound tracking algorithm. Based on the performance index, a decision can be made whether or not to switch to a spectral-based tracking algorithm to recognize the heart sound component from the representative heart sound segment. A physiologic event detector can detect a cardiac event using the recognized heart sound component.