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Evaluating a Remote Health Monitoring Application Powered by Bluetooth
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-5590-0784
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-2419-2735
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-1940-1747
2019 (English)In: 11th International Conference on e-Health e-Health'19, 2019, p. 67-74-Conference paper, Published paper (Refereed)
Abstract [en]

It has become widely accepted that the Internet of Things (IoT) devices and technologies are the key enablers for many emerging applications including remote health monitoring. Various physiological sensing devices have been designed and equipped with different radio technologies. The choice of radio hardware plays an important role on the overall performance of the system since it imposes some limitations on the delivered quality of service. Hence, it is critical to properly evaluate the embedded radio technology based on the application requirements. In this paper, we perform extensive experiments on Shimmer physiological sensors that is one of the leading providers of wearable wireless sensor products powered by Bluetooth classic radio. Shimmer sensors are designed and used for monitoring various human health information such as temperature, heart rate, movement, etc. We review and investigate different scenarios in which Shimmer devices are used by medical practitioners to monitor the ECG signal and the movement of a human. This study shows that the Shimmer device can provide reliable data delivery by using a specific configuration. For instance, employing a maximum number of seven Shimmer devices attached on a body at home environment within the range of at most 5 m and with the sampling rate of 512 Hz would result in a reasonable quality of service, while varying these parameters may degrade the overall performance. Mobility of human body, noisy environment, and higher packet transmission rates are some examples that will reduce the system quality. © Copyright 2019 IADIS Press All rights reserved.

Place, publisher, year, edition, pages
2019. p. 67-74-
National Category
Engineering and Technology Medical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-45040Scopus ID: 2-s2.0-85073169425OAI: oai:DiVA.org:mdh-45040DiVA, id: diva2:1345199
Conference
11th International Conference on e-Health e-Health'19, 17 Jul 2019, Porto, Portugal
Projects
ESS-H - Embedded Sensor Systems for Health Research ProfileMobiFog: mobility management in Fog-assisted IoT networksHealth5G: Future eHealth powered by 5GFlexiHealth: flexible softwarized networks for digital healthcareAvailable from: 2019-08-23 Created: 2019-08-23 Last updated: 2019-10-24Bibliographically approved

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Vahabi, MaryamFotouhi, HosseinBjörkman, MatsLindén, Maria

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