Acoustic Asthma Monitoring via Mobile Audio Analysis
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Solution Overview
Problem
Adolescents with asthma face challenges in accurately monitoring their symptoms, leading to inadequate self-management and increased asthma morbidity due to inaccurate symptom perception, particularly underestimation of nighttime symptoms, and the limitations of existing monitoring methods like Peak Expiratory Flow Meters (PEFMs) in providing reliable and sustainable asthma control.
Innovation Solution
A non-invasive automated device (ADAM) that uses sound-detection and analysis technology to monitor asthma symptoms, including wheezing and coughing, and physical activity, providing objective and continuous monitoring of asthma symptoms by converting complex raw data into intuitive numeric data, enabling timely intervention and improving asthma management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If adolescents use traditional monitoring methods like Peak Expiratory Flow Meters (PEFMs), then they can obtain some asthma symptom data, but the monitoring accuracy and reliability are insufficient leading to inadequate self-management
Solution Approach 1:
The patent replaces mechanical monitoring systems (PEFMs) with acoustic sensing technology. The system uses microphones and audio processing to detect wheezing, coughing, and breathing patterns, substituting mechanical flow measurement with acoustic field analysis for more comprehensive and accurate asthma symptom monitoring
Solution Approach 2:
The patent introduces a computational audio analysis system as an intermediary between the patient and healthcare providers. This intermediary processes raw audio signals, extracts relevant features, and generates actionable insights, bridging the gap between simple symptom reporting and clinical decision-making
2Loss of information
If adolescents manually monitor and report asthma symptoms, then they can provide some feedback to providers, but the data is subjective and often inaccurate due to underestimation of nighttime symptoms
Solution Approach 1:
The system enables automatic monitoring without requiring active patient participation. The acoustic sensors continuously capture breathing sounds, and the embedded algorithms automatically analyze and interpret the data, allowing the system to serve itself and eliminating the need for manual symptom reporting by adolescents
Solution Approach 2:
The patent implements continuous monitoring throughout the day and night, capturing asthma symptoms at all times including nighttime when adolescents are sleeping. This continuous acoustic surveillance ensures no symptom information is lost, providing comprehensive data for accurate asthma management
3Reliability
If existing monitoring methods are used, then some asthma data can be collected, but the monitoring is not continuous or objective leading to increased asthma morbidity
Solution Approach 1:
The patent designs a multi-functional acoustic monitoring system that simultaneously detects multiple asthma-related parameters including wheezing, coughing, breathing rate, and sleep quality. This universal approach consolidates multiple monitoring functions into a single acoustic-based platform, improving reliability without proportionally increasing complexity
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
The ADAM device enhances the accuracy and objectivity of asthma symptom monitoring, allowing for better adherence to treatment plans, reducing asthma exacerbations, and improving quality of life by providing real-time feedback and long-term tracking of asthma symptoms, thus empowering adolescents to manage their condition effectively.
Implementation Method 1
a vibration sensing device, configured to detect a vibration over at least a portion of an audible spectrum
Implementation Method 2
an acceleration sensing device, configured to detect acceleration
Data Source
AI summary
An automated system for monitoring respiratory diseases, such as asthma, provides noninvasive, multimodal monitoring of respiratory signs and symptoms that can include wheeze and cough. Some embodiments employ a mobile device, such as a cell phone, in which raw data from a microphone and an accelerometer are processed, analyzed, and stored. Data can be collected continuously. Time domain and frequency domain analyses of signals to determine, e.g., energy, duration, and spectral content of candidate sounds can be employed to discriminate symptoms of interest from background sounds and to establish significance. Accelerometer signals are analyzed to determine activity levels. Analyses of a user's symptoms and activity level prior to, during, and after an event can provide meaningful determinations of disease severity and predict future respiratory events. The system can provide a summary of data, as well as an alarm when symptom severity reaches a threshold.