Authors
Ali S. AlMejrad*
Biomedical Technology Department, Applied Medical Sciences College, King Saud University, P.O. Box 10219, Riyadh 11433, Kingdom of Saudi Arabia
*Corresponding author. Email: [email protected]
Corresponding Author
Ali S. AlMejrad
Received 20 November 2019, Accepted 15 December 2019, Available Online 28 February 2020.
DOI
https://doi.org/10.2991/jrnal.k.200221.006How to use a DOI?
Keywords
Respiratory disease; virtual instrument; signal processing; power spectrum
Abstract
Respiratory problem is one of the most common health problems occurring in Saudi Arabia due to the continuous changes of the weather in addition to surface winds that cause dust during all seasons yearly. The most affected people especially children and elderly in addition to the adults with respiratory problems such as asthma. Such problem needs emergency care as soon as it occurred. The goal of our research is to develop a compact respiratory diagnostic system using advanced signal processing that can be used remotely via the virtual instrumentation technology to help accurately diagnosis at early stages of respiratory diseases. It can also overcome the lack of expert physicians in rural regions and some urban clinics or health centers. The proposed system will be implemented using Virtual Instrumentation (VI) that consists of computer, microphone with simple analog circuit, digitizer and LabVIEW software. VI has been designed for easy measurement and analysis. In addition to that, it has features and ability to control the whole system of acquisition, play, display, processing and advanced analysis of the different acquired respiratory signals. Respiratory signals obtained from our system are analyzed for diagnosis purposes using advanced signal processing techniques to the analysis of respiratory parameters using time and frequency domains. The obtained results can be displayed and printed in a report format including acquired respiratory signal, filtered signal, extracted segment for selection of phase, power spectral density, and analyzed respiratory parameters for diagnosis purpose. The developed system is successful and achieved its purpose based on the tests performed with real respiratory signals of normal and abnormal cases that proved to be efficient system while dealing with many respiratory problems conditions.
Copyright
© 2020 The Authors. Published by ALife Robotics Corp. Ltd..
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).