Continual Monitoring of Respiratory Disorders to Enhance Therapy via Real-Time Lung Sound Imaging in Telemedicine

This work presents a configurable Internet of Things architecture for acoustical sensing and analysis for frequent remote respiratory assessments. The proposed system creates a foundation for enabling real-time therapy and patient feedback adjustment in a telemedicine setting. By allowing continuous...

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Bibliographic Details
Published in:Electronics (Basel) 2024-05, Vol.13 (9), p.1669
Main Authors: Muhammad, Murdifi, Li, Minghui, Lou, Yaolong, Lee, Chang-Sheng
Format: Article
Language:English
Subjects:
Accuracy
Acoustic properties
Acoustics
Airway management
Assessments
Asthma
Biometrics
Chronic obstructive pulmonary disease
Computer architecture
Design optimization
Digital imaging
Image reconstruction
Internet of Things
Lung diseases
Lungs
Medical research
Medicine, Experimental
Microelectromechanical systems
Microphones
Monitoring systems
Noise monitoring
Obstructions
Patient compliance
Patients
Real time
Remote monitoring
Remote sensing
Respiration
Respiratory diseases
Sensors
Sound
Stethoscopes
Telemedicine
Therapy
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Summary:This work presents a configurable Internet of Things architecture for acoustical sensing and analysis for frequent remote respiratory assessments. The proposed system creates a foundation for enabling real-time therapy and patient feedback adjustment in a telemedicine setting. By allowing continuous remote respiratory monitoring, the system has the potential to give clinicians access to assessments from which they could make decisions about modifying therapy in real-time and communicate changes directly to patients. The system comprises a wearable wireless microphone array interfaced with a programmable microcontroller with embedded signal conditioning. Experiments on the phantom model were conducted to demonstrate the feasibility of reconstructing acoustic lung images for detecting obstructions in the airway and provided controlled validation of noise resilience and imaging capabilities. An optimized denoising technique and design innovations provided 7 dB more SNR and 7% more imaging accuracy for the proposed system, benchmarked against digital stethoscopes. While further clinical studies are warranted, initial results suggest potential benefits over single-point digital stethoscopes for internet-enabled remote lung monitoring needing noise immunity and regional specificity. The flexible architecture aims to bridge critical technical gaps in frequent and connected respiratory function at home or in busy clinical settings challenged by ambient noise interference.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics13091669