Lung Sound Analysis with Pause-Phase Noise Exclusion
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Solution Overview
Problem
Existing lung sound analysis systems struggle to accurately diagnose heart failure in non-specialist settings due to the challenge of distinguishing between normal and abnormal lung sounds, particularly when noise is present during the pause phase of breathing, leading to potential misdiagnosis.
Innovation Solution
A lung sound analysis system that includes an acquisition means for acquiring time-series acoustic signals, a determination means to identify the pause phase of breathing, and a detection means to analyze lung sounds during phases other than the pause phase, thereby reducing noise interference and improving diagnostic accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If lung sounds are analyzed during the pause phase of breathing, then more complete breathing cycle coverage is achieved, but noise from outside sources is erroneously detected as abnormality
Solution Approach 1:
The breathing cycle is segmented into distinct phases (inspiration, expiration, and pause phase). The analysis system processes lung sounds differently for each phase, specifically excluding the pause phase from abnormality detection to avoid noise contamination while maintaining analysis of the inspiratory and expiratory phases where actual lung sounds occur.
Solution Approach 2:
The pause phase is extracted and separated from the lung sound analysis process. By identifying and removing the pause phase segments from the acoustic signals subjected to abnormality detection, the system eliminates the source of noise-related false positives while preserving analysis of the clinically relevant inspiratory and expiratory phases.
2Device complexity
If lung sounds are divided into only two phases (first-half inspiration and latter-half expiration), then processing is simplified, but the pause phase is incorrectly included causing erroneous noise detection
Solution Approach 1:
The breathing cycle is segmented into three distinct phases rather than two: inspiration phase, expiration phase, and pause phase. This tripartite segmentation allows the system to identify and exclude the pause phase from abnormality detection, improving measurement precision without significantly increasing processing complexity.
Solution Approach 2:
A phase determination mechanism acts as an intermediary between the raw acoustic signal and the abnormality detection process. This intermediary component identifies and marks the pause phase segments, allowing the detection algorithm to selectively process only the relevant inspiratory and expiratory phases, thereby maintaining simplicity while improving accuracy.
Data Source
AI summary
A lung sound analysis system includes an acquisition means for acquiring time-series acoustic signals including lung sounds of a subject who is a heart failure patient, a determination means for determining a pause phase of breathing of the subject, a dividing means for dividing the time-series acoustic signals into those in a period of the pause phase of breathing of the subject and those in a period other than the pause phase, according to a result of the determination, and a detection means for detecting abnormality in the lung sounds from the time-series acoustic signals in the period other than the pause phase after the division. The system supports medical decision making for healthcare professionals monitoring heart failure patients.