Literature DB >> 33800728

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

Cristian Vizitiu1, Călin Bîră1,2, Adrian Dinculescu1,3, Alexandru Nistorescu1,4, Mihaela Marin1.   

Abstract

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.

Entities:  

Keywords:  active and assisted living (AAL); arduino; biometric sensors; choice reaction time (CRT); e-Health; elders; independent living; internet of things (IoT); noncommunicable diseases (NCDs); systems engineering

Mesh:

Year:  2021        PMID: 33800728      PMCID: PMC7961703          DOI: 10.3390/s21051837

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  17 in total

1.  The effects of ageing on reaction times to motion onset.

Authors:  V Porciatti; A Fiorentini; M C Morrone; D C Burr
Journal:  Vision Res       Date:  1999-06       Impact factor: 1.886

2.  Simple reaction times and timing of serial reactions of middle-aged and old men.

Authors:  N Inui
Journal:  Percept Mot Skills       Date:  1997-02

3.  Gait in Mild Alzheimer's Disease: Feasibility of Multi-Center Measurement in the Clinic and Home with Body-Worn Sensors: A Pilot Study.

Authors:  Ríona Mc Ardle; Rosie Morris; Aodhán Hickey; Silvia Del Din; Ivan Koychev; Roger N Gunn; Jennifer Lawson; Giovanna Zamboni; Basil Ridha; Barbara J Sahakian; James B Rowe; Alan Thomas; Henrik Zetterberg; Clare MacKay; Simon Lovestone; Lynn Rochesteron
Journal:  J Alzheimers Dis       Date:  2018       Impact factor: 4.472

Review 4.  A review of wearable sensors and systems with application in rehabilitation.

Authors:  Shyamal Patel; Hyung Park; Paolo Bonato; Leighton Chan; Mary Rodgers
Journal:  J Neuroeng Rehabil       Date:  2012-04-20       Impact factor: 4.262

5.  Age-related slowing of response selection and production in a visual choice reaction time task.

Authors:  David L Woods; John M Wyma; E William Yund; Timothy J Herron; Bruce Reed
Journal:  Front Hum Neurosci       Date:  2015-04-23       Impact factor: 3.169

6.  On the capability of smartphones to perform as communication gateways in medical wireless personal area networks.

Authors:  María José Morón; Rafael Luque; Eduardo Casilari
Journal:  Sensors (Basel)       Date:  2014-01-02       Impact factor: 3.576

Review 7.  Smart Homes for Elderly Healthcare-Recent Advances and Research Challenges.

Authors:  Sumit Majumder; Emad Aghayi; Moein Noferesti; Hamidreza Memarzadeh-Tehran; Tapas Mondal; Zhibo Pang; M Jamal Deen
Journal:  Sensors (Basel)       Date:  2017-10-31       Impact factor: 3.576

Review 8.  Age-Related Diseases and Clinical and Public Health Implications for the 85 Years Old and Over Population.

Authors:  Efraim Jaul; Jeremy Barron
Journal:  Front Public Health       Date:  2017-12-11

Review 9.  IoT Wearable Sensors and Devices in Elderly Care: A Literature Review.

Authors:  Thanos G Stavropoulos; Asterios Papastergiou; Lampros Mpaltadoros; Spiros Nikolopoulos; Ioannis Kompatsiaris
Journal:  Sensors (Basel)       Date:  2020-05-16       Impact factor: 3.576

10.  The use of a wearable camera improves autobiographical memory in patients with Alzheimer's disease.

Authors:  Emma Woodberry; Georgina Browne; Steve Hodges; Peter Watson; Narinder Kapur; Ken Woodberry
Journal:  Memory       Date:  2014-02-17
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  1 in total

1.  A Sensor-Based Perspective in Early-Stage Parkinson's Disease: Current State and the Need for Machine Learning Processes.

Authors:  Marios G Krokidis; Georgios N Dimitrakopoulos; Aristidis G Vrahatis; Christos Tzouvelekis; Dimitrios Drakoulis; Foteini Papavassileiou; Themis P Exarchos; Panayiotis Vlamos
Journal:  Sensors (Basel)       Date:  2022-01-06       Impact factor: 3.576

  1 in total

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