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General Information
    • ISSN: 1793-8236 (Online)
    • Abbreviated Title Int. J. Eng. Technol.
    • Frequency:  Quarterly 
    • DOI: 10.7763/IJET
    • Managing Editor: Ms. Jennifer Zeng
    • Abstracting/ Indexing: Inspec (IET), CNKI Google Scholar, EBSCO, ProQuest, Crossref, Ulrich Periodicals Directory, Chemical Abstracts Services (CAS), etc.
    • E-mail: ijet_Editor@126.com
IJET 2016 Vol.8(4): 293-296 ISSN: 1793-8236
DOI: 10.7763/IJET.2016.V8.900

Using Mobile Phone Sensors to Detect Rapid Respiratory Rate in the Diagnosis of Pneumonia

Xingjuan Li

Abstract—In resource-poor areas, the rapid respiratory rate is an important factor to determine pneumonia. Identifying the rapid respiratory rate from robust sensors can solve the problem of labor-intensive practice of counting respiratory rate for doctors. In this paper, the smart phone sensors are proposed to detect physical signs of breathing in a non-invasive way. The proposed method was targeting at detecting the rapid respiratory rate. It was designed by android apps with the ability to acquire breathing signals from phone sensors, and follow-up biomedical signal processing. Data recovery is used to reconstruct the whole information of collected data from android. Moreover, based on the features of breathing signal, additional signal processing is used to reduce interference. Finally, the rapid respiratory rate is measured by comparing with the definition of rapid respiratory rate given by the World Health Organization. Smart phone provides a diagnostic platform for suspected pneumonia patients. The whole algorithm may give an error of ±2 breaths per minute. Therefore, this research provides a new way of capturing breathing signal using phone sensors with high performance. Using this proposed technology, the danger signs of pneumonia can be recognized earlier, thus more lives will be saved by prompt treatments.

Index Terms—Rapid respiratory rate, pneumonia, mobile phone sensors, bio-medical signal processing.

Xingjuan Li is with the School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, QLD 4072 Australia (e-mail: mirandalxj@gmail.com)


Cite: Xingjuan Li, "Using Mobile Phone Sensors to Detect Rapid Respiratory Rate in the Diagnosis of Pneumonia," International Journal of Engineering and Technology vol. 8, no. 4, pp. 293-296, 2016.

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