Wheezing Detection Using Machine Learning and Signal Merging
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Solution Overview
Problem
Asthma patients often do not receive timely medical assistance due to the subjective nature of wheezing detection, leading to frequent emergency department visits and hospitalizations, as wheezing can only be detected by its unique auditory characteristics, which may not be recognized by non-medical personnel.
Innovation Solution
A mobile device equipped with a stethoscope input port, circuitry for signal processing, and machine learning algorithms to detect and classify wheezing, providing real-time asthma condition indications, including severity assessment and remedial solutions, allowing for in-home detection and communication with medical professionals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wheezing detection relies on subjective auditory characteristics, then medical professionals can identify wheezing through training and experience, but non-medical personnel cannot detect wheezing timely leading to delayed treatment
Solution Approach 1:
The patent introduces an automated detection system that acts as an intermediary between the patient's lung sounds and the diagnosis. The system uses audio recording, signal processing, and machine learning algorithms to objectively detect wheezing characteristics, translating complex auditory patterns into clear diagnostic results that anyone can use without medical training.
Solution Approach 2:
The patent replaces the mechanical system of human auditory perception and interpretation with an automated electronic system. Instead of relying on human ears and trained judgment, the system uses microphones, digital signal processing, and machine learning models to detect and analyze wheezing sounds objectively and consistently.
2Measurement precision
If in-person medical detection is used, then accurate diagnosis can be made by professionals, but patients must frequently visit medical facilities consuming time and resources
Solution Approach 1:
The patent enables patients to perform self-diagnosis at home using the automated detection system. Patients can record their own lung sounds, receive immediate objective feedback about wheezing presence and severity, and monitor their condition over time without needing to travel to medical facilities for routine check-ups.
Solution Approach 2:
The system provides immediate feedback to patients about their lung sound quality and wheezing detection results. This real-time feedback loop allows patients to understand their condition status, track changes over time, and make informed decisions about when medical intervention is needed, reducing unnecessary medical visits.
3Measurement precision
If multiple locations on the patient's body are recorded, then comprehensive lung assessment is achieved, but the recording process becomes more complex
Solution Approach 1:
The patent divides the lung assessment into multiple discrete recording locations on the patient's body. Each location corresponds to a specific lung zone, and the system guides users to record at each segment separately. This segmentation allows comprehensive coverage while maintaining simplicity through structured, step-by-step guidance.
Solution Approach 2:
The system pre-defines the optimal recording locations and sequence before the actual recording process begins. Users are guided through a predetermined workflow that specifies where and in what order to record, eliminating the need for users to decide on their own how to comprehensively cover all lung areas.
Data Source
AI summary
Described herein are a computer enhanced medical method and device for generating an asthmatic condition indication. The apparatus receives a lung signal from a stethoscope, the lung signal having been converted from an analog signal to a digital signal. Furthermore, circuitry included in the apparatus performs, inter alia, the following: displays a patient recording canvas corresponding to physical locations on a body of the patient, the canvas including an anterior patient orientation and a posterior patient orientation, generates a recording process, the recording process including recording, for a predetermined period of time, the detected lung signal, and associates the recording with a marked location. Furthermore, the circuitry merges the recorded lung signal from each marked location on the patent recording canvas as merged information, and applies processing to the merged information to generate the asthmatic condition indication.