Next Article in Journal
From Data to Rhizomes: Applying a Geographical Concept to Understand the Mobility of Tourists from Geo-Located Tweets
Next Article in Special Issue
Visual Analytics for Electronic Health Records: A Review
Previous Article in Journal
A Review of Hyperscanning and Its Use in Virtual Environments
Previous Article in Special Issue
Toward Evaluation of the Subjective Experience of a General Class of User-Controlled, Robot-Mediated Rehabilitation Technologies for Children with Neuromotor Disability
Open AccessFeature PaperArticle

Using Mobiles to Monitor Respiratory Diseases

1
Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, UAE
2
Department of Electrical Engineering, American University of Sharjah, Sharjah 26666, UAE
3
College of Medicine, University of Sharjah, Sharjah 27272, UAE
*
Author to whom correspondence should be addressed.
Received: 7 November 2020 / Revised: 12 December 2020 / Accepted: 15 December 2020 / Published: 16 December 2020
(This article belongs to the Special Issue Feature Papers: Health Informatics)
In this work, a mobile application is developed to assist patients suffering from chronic obstructive pulmonary disease (COPD) or Asthma that will reduce the dependency on hospital and clinic based tests and enable users to better manage their disease through increased self-involvement. Due to the pervasiveness of smartphones, it is proposed to make use of their built-in sensors and ever increasing computational capabilities to provide patients with a mobile-based spirometer capable of diagnosing COPD or asthma in a reliable and cost effective manner. Data collected using an experimental setup consisting of an airflow source, an anemometer, and a smartphone is used to develop a mathematical model that relates exhalation frequency to air flow rate. This model allows for the computation of two key parameters known as forced vital capacity (FVC) and forced expiratory volume in one second (FEV1) that are used in the diagnosis of respiratory diseases. The developed platform has been validated using data collected from 25 subjects with various conditions. Results show that an excellent match is achieved between the FVC and FEV1 values computed using a clinical spirometer and those returned by the model embedded in the mobile application. View Full-Text
Keywords: asthma; COPD; smartphones; spirometry asthma; COPD; smartphones; spirometry
Show Figures

Figure 1

MDPI and ACS Style

Zubaydi, F.; Sagahyroon, A.; Aloul, F.; Mir, H.; Mahboub, B. Using Mobiles to Monitor Respiratory Diseases. Informatics 2020, 7, 56. https://0-doi-org.brum.beds.ac.uk/10.3390/informatics7040056

AMA Style

Zubaydi F, Sagahyroon A, Aloul F, Mir H, Mahboub B. Using Mobiles to Monitor Respiratory Diseases. Informatics. 2020; 7(4):56. https://0-doi-org.brum.beds.ac.uk/10.3390/informatics7040056

Chicago/Turabian Style

Zubaydi, Fatma; Sagahyroon, Assim; Aloul, Fadi; Mir, Hasan; Mahboub, Bassam. 2020. "Using Mobiles to Monitor Respiratory Diseases" Informatics 7, no. 4: 56. https://0-doi-org.brum.beds.ac.uk/10.3390/informatics7040056

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop