Real Time Breathing Signal Measurement: Current Methods

Grepl, Jan; Penhaker, Marek; Kubíček, Jan; Liberda, A.; Selamat, Ali; Majerník, Jaroslav; Hudák, Radovan

doi:10.1016/j.ifacol.2015.07.024

Cited by 2 publications

(1 citation statement)

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“…The breathing sound recording device is a custom-made digital stethoscope assembly with an inbuilt Bluetooth module developed in an earlier study on pneumonia [44] to communicate with the smartphone for recording the breathing sounds. The stethoscope placement at the most appropriate part of the body is a critical factor [66] . The breathing sounds can be obtained from the following positions on the patient’s body—anterior, posterior, and tracheal.…”

Section: Methodsmentioning

confidence: 99%

A deep-learning based multimodal system for Covid-19 diagnosis using breathing sounds and chest X-ray images

Sait

Lal

Shivakumar

et al. 2021

Applied Soft Computing

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Covid-19 has become a deadly pandemic claiming more than three million lives worldwide. SARS-CoV-2 causes distinct pathomorphological alterations in the respiratory system, thereby acting as a biomarker to aid its diagnosis. A multimodal framework (Ai-CovScan) for Covid-19 detection using breathing sounds, chest X-ray (CXR) images, and rapid antigen test (RAnT) is proposed. Transfer Learning approach using existing deep-learning Convolutional Neural Network (CNN) based on Inception-v3 is combined with Multi-Layered Perceptron (MLP) to develop the CovScanNet model for reducing false-negatives. This model reports a preliminary accuracy of 80% for the breathing sound analysis, and 99.66% Covid-19 detection accuracy for the curated CXR image dataset. Based on Ai-CovScan, a smartphone app is conceptualised as a mass-deployable screening tool, which could alter the course of this pandemic. This app ’s deployment could minimise the number of people accessing the limited and expensive confirmatory tests, thereby reducing the burden on the severely stressed healthcare infrastructure.

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Section: Methodsmentioning

confidence: 99%