Exhaustive Description of the System Architecture and Prototype Implementation of an IoT-Based eHealth Biometric Monitoring System for Elders in Independent Living

In this paper, we present an exhaustive description of an extensible e-Health Internet-connected embedded system, which allows the measurement of three biometric parameters: pulse rate, oxygen saturation and temperature, via several wired and wireless sensors residing to the realm of Noncommunicable...

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Main Authors: Cristian Vizitiu, Călin Bîră, Adrian Dinculescu, Alexandru Nistorescu, Mihaela Marin
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/5/1837
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spelling doaj-468467484e3848719755bd97fe5b64a92021-03-07T00:00:25ZengMDPI AGSensors1424-82202021-03-01211837183710.3390/s21051837Exhaustive Description of the System Architecture and Prototype Implementation of an IoT-Based eHealth Biometric Monitoring System for Elders in Independent LivingCristian Vizitiu0Călin Bîră1Adrian Dinculescu2Alexandru Nistorescu3Mihaela Marin4Space Applications for Human Health and Safety Department, Institute of Space Science, 077125 Măgurele, RomaniaSpace Applications for Human Health and Safety Department, Institute of Space Science, 077125 Măgurele, RomaniaSpace Applications for Human Health and Safety Department, Institute of Space Science, 077125 Măgurele, RomaniaSpace Applications for Human Health and Safety Department, Institute of Space Science, 077125 Măgurele, RomaniaSpace Applications for Human Health and Safety Department, Institute of Space Science, 077125 Măgurele, RomaniaIn this paper, we present an exhaustive description of an extensible e-Health Internet-connected embedded system, which allows the measurement of three biometric parameters: pulse rate, oxygen saturation and temperature, via several wired and wireless sensors residing to the realm of Noncommunicable Diseases (NCDs) and cognitive assessment through Choice Reaction Time (CRT) analysis. The hardware used is based on ATMEGA AVR + MySignals Hardware printed circuit board (Hardware PCB), but with multiple upgrades (including porting from ATMEGA328P to ATMEGA2560). Multiple software improvements were made (by writing high-level device drivers, text-mode and graphic-mode display driver) for increasing functionality, portability, speed, and latency. A top-level embedded application was developed and benchmarked. A custom wireless AT command firmware was developed, based on ESP8266 firmware to allow AP-mode configuration and single-command JavaScript Object Notation (JSON) data-packet pushing towards the cloud platform. All software is available in a git repository, including the measurement results. The proposed eHealth system provides with specific NCDs and cognitive views fostering the potential to exploit correlations between physiological and cognitive data and to generate predictive analysis in the field of eldercare.https://www.mdpi.com/1424-8220/21/5/1837e-HealthInternet of Things (IoT)eldersindependent livingActive and Assisted Living (AAL)Systems Engineering
collection DOAJ
language English
format Article
sources DOAJ
author Cristian Vizitiu
Călin Bîră
Adrian Dinculescu
Alexandru Nistorescu
Mihaela Marin
spellingShingle Cristian Vizitiu
Călin Bîră
Adrian Dinculescu
Alexandru Nistorescu
Mihaela Marin
Exhaustive Description of the System Architecture and Prototype Implementation of an IoT-Based eHealth Biometric Monitoring System for Elders in Independent Living
Sensors
e-Health
Internet of Things (IoT)
elders
independent living
Active and Assisted Living (AAL)
Systems Engineering
author_facet Cristian Vizitiu
Călin Bîră
Adrian Dinculescu
Alexandru Nistorescu
Mihaela Marin
author_sort Cristian Vizitiu
title Exhaustive Description of the System Architecture and Prototype Implementation of an IoT-Based eHealth Biometric Monitoring System for Elders in Independent Living
title_short Exhaustive Description of the System Architecture and Prototype Implementation of an IoT-Based eHealth Biometric Monitoring System for Elders in Independent Living
title_full Exhaustive Description of the System Architecture and Prototype Implementation of an IoT-Based eHealth Biometric Monitoring System for Elders in Independent Living
title_fullStr Exhaustive Description of the System Architecture and Prototype Implementation of an IoT-Based eHealth Biometric Monitoring System for Elders in Independent Living
title_full_unstemmed Exhaustive Description of the System Architecture and Prototype Implementation of an IoT-Based eHealth Biometric Monitoring System for Elders in Independent Living
title_sort exhaustive description of the system architecture and prototype implementation of an iot-based ehealth biometric monitoring system for elders in independent living
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2021-03-01
description In this paper, we present an exhaustive description of an extensible e-Health Internet-connected embedded system, which allows the measurement of three biometric parameters: pulse rate, oxygen saturation and temperature, via several wired and wireless sensors residing to the realm of Noncommunicable Diseases (NCDs) and cognitive assessment through Choice Reaction Time (CRT) analysis. The hardware used is based on ATMEGA AVR + MySignals Hardware printed circuit board (Hardware PCB), but with multiple upgrades (including porting from ATMEGA328P to ATMEGA2560). Multiple software improvements were made (by writing high-level device drivers, text-mode and graphic-mode display driver) for increasing functionality, portability, speed, and latency. A top-level embedded application was developed and benchmarked. A custom wireless AT command firmware was developed, based on ESP8266 firmware to allow AP-mode configuration and single-command JavaScript Object Notation (JSON) data-packet pushing towards the cloud platform. All software is available in a git repository, including the measurement results. The proposed eHealth system provides with specific NCDs and cognitive views fostering the potential to exploit correlations between physiological and cognitive data and to generate predictive analysis in the field of eldercare.
topic e-Health
Internet of Things (IoT)
elders
independent living
Active and Assisted Living (AAL)
Systems Engineering
url https://www.mdpi.com/1424-8220/21/5/1837
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