Literature DB >> 26626086

Development of a wireless blood pressure measuring device with smart mobile device.

İlhan İlhan1, İbrahim Yıldız2, Mehmet Kayrak3.   

Abstract

Today, smart mobile devices (telephones and tablets) are very commonly used due to their powerful hardware and useful features. According to an eMarketer report, in 2014 there were 1.76 billion smartphone users (excluding users of tablets) in the world; it is predicted that this number will rise by 15.9% to 2.04 billion in 2015. It is thought that these devices can be used successfully in biomedical applications. A wireless blood pressure measuring device used together with a smart mobile device was developed in this study. By means of an interface developed for smart mobile devices with Android and iOS operating systems, a smart mobile device was used both as an indicator and as a control device. The cuff communicating with this device through Bluetooth was designed to measure blood pressure via the arm. A digital filter was used on the cuff instead of the traditional analog signal processing and filtering circuit. The newly developed blood pressure measuring device was tested on 18 patients and 20 healthy individuals of different ages under a physician's supervision. When the test results were compared with the measurements made using a sphygmomanometer, it was shown that an average 93.52% accuracy in sick individuals and 94.53% accuracy in healthy individuals could be achieved with the new device.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Blood pressure; Bluetooth; Mobile programming; Signal processing; Smart mobile device

Mesh:

Year:  2015        PMID: 26626086     DOI: 10.1016/j.cmpb.2015.11.003

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  3 in total

1.  Network Coded Cooperative Communication in a Real-Time Wireless Hospital Sensor Network.

Authors:  R Prakash; A Balaji Ganesh; Somu Sivabalan
Journal:  J Med Syst       Date:  2017-03-16       Impact factor: 4.460

2.  Real-Time Cuffless Continuous Blood Pressure Estimation Using 1D Squeeze U-Net Model: A Progress toward mHealth.

Authors:  Tasbiraha Athaya; Sunwoong Choi
Journal:  Biosensors (Basel)       Date:  2022-08-18

3.  The QardioArm App in the Assessment of Blood Pressure and Heart Rate: Reliability and Validity Study.

Authors:  Victoria Mazoteras Pardo; Marta E Losa Iglesias; José López Chicharro; Ricardo Becerro de Bengoa Vallejo
Journal:  JMIR Mhealth Uhealth       Date:  2017-12-15       Impact factor: 4.773

  3 in total

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