Monday , 14 October 2019
roen

Art. 02 – Vol. 27 – No. 3 – 2017

Use of IoT technology in the Medical Field

Ramona PLOTOGEA
ramonaplotogea@gmail.com
Bucharest Academy of Economic Studies
Alin ZAMFIROIU
zamfiroiu@ici.ro
National Institute for Research & Development in Informatics – ICI Bucharest

Abstract: This article presents an overview of the main strategies, variables and, of course, of the approach that enables IoT technologies and brain-computer interfaces to provide a significant contribution to a better, healthier lifestyle. This paper describes two current technology breakthroughs that are extremely popular at the moment, provides a brief description of the issues concerning brain disorders and of the impact of these brain-computer interfaces and it also debates the way these two main breakthroughs may pull together in order to achieve an impressive progress in medicine and in other fields, as well. The observations and main results that sum up this paper are meant to show that persistent research and development of this technology aim to use brain activity strictly in order to help people with severe motor disabilities. Furthermore, this technological breakthrough may serve as an instrument for the early detection of neurological diseases and its use must definitely not be targeted for the hacking process of the human brain.

Keywords:  IoT, Brainwaves, Brain-computer interface, Electroencephalography, Brain-hacking.

REFERENCES

  1. MANN,, JASON: Opportunities and Applications across Industries. The Internet of Things. l.: iianalytics.com, 2015.
  2. MANYIKA, JAMES; CHUI, MICHAEL; BISSON, PETER; WOETZEL, JONATHAN; DOBBS, RICHARD; BUGHIN, JACQUES; AHARON, DAN: Unlocking the potential of the Internet of Things. http://www.mckinsey.com. [Interactiv] Iunie 2015. http://www.mckinsey.com/ business-functions/digital-mckinsey/our-insights/the-internet-of-things-the-value-of-digitizing-the-physical-world.
  3. Brain–computer interface. https://en.wikipedia.org/wiki/ Brain%E2%80%93computer_interface#Early_work.
  4. POSTELNICU, CEZAR CRISTIAN: Utilizarea biopotențialelor în interfețele om-mașină pentru aplicații de robotică. Centrul de cercetare : Informatică Industrială Virtuală și Robotică, Școala Doctorală Interdisciplinară. Brașov : Univ. Transilvania Brașov, 2012. p. 62.

View full text

CITE THIS PAPER AS:
Ramona PLOTOGEA, Alin ZAMFIROIU, IoT Platforms – Use of IoT technology in the Medical Field, Romanian Journal of Information Technology and Automatic Control, ISSN 1220-1758, vol. 27(3), pp. 19-28, 2017.

  1. PLUMMER, QUINTEN: The Internet of Medical Things, A New Concept in Healthcare.http://www.technewsworld.com/ story/83654.html. 2016
  2. JAVAID, MUHAMMAD ADEEL.: Brain-Computer Interface. Institute of Electrical and Electronics Engineers Journal. 5 June 2013, p. 19.
  3. GRABIANOWSKI, ED. How Brain-computer Interfaces Work. How Tech Stuff Works.http://computer.howstuffworks.com/ brain-computer-interface5.htm. 2016.
  4. ELECTROENCEFALOGRAFIE: [Interactiv] https://ro.wikipedia.org/wiki/ Electroencefalografie.
  5. RAMADAN, RABIE; ELSHAHED, MARWA; ALI, RASHA: Basics of Brain Computer Interface. [autorul cărţii] Aboul Ella Hassanien și Ahmad Taher Azar. Brain-Computer Interfaces. New Yok: Springer Int. Publ., 2015, p. 416.
  6. DIMITROV, DIMITER V.: Medical Internet of Things and Big Data in Healthcare. Healthcare Informatics Research. 156, 2016.
  7. HOCHBERG, LEIGH; DONOGHUE, JOHN.: Sensors for brain-computer interfaces. IEEE Engineering in Medicine and Biology Magazine,
  8. *** INC., NEUROSKY: Ultimate Guide to NueroSky: EEG & ECG Biosensor Solutions. [Interactiv] NeuroSky Incorporate. [Citat: 1 May 2017.]  http://neurosky.com/biosensors/eeg-sensor/ultimate-guide-to-eeg/.
  9. MORETTI, DAVIDE; PATERNICO, DONATA; BINETTI, GIULIANO; ZANETTI, ORAZIO; FRISONI, GIOVANNI: EEG upper/low alpha frequency power ratio. Frontiers in Aging Neuroscience. [Interactiv] 25 Oct 2013. [Citat: 3 February 2017.] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3807715/.
  10. IOANID, ANA: Fundamente multidisciplinare ale neurofeedback – ului. Aspecte biofizice şi matematice. Bucureşti. s.n., 2009.
  11. *** Dealing with noise in EEG recording and data analysis. Repovs, Grega. Ljubljana. Journal of the Slovenian Medical Informatics Association, 2010.
  12. WOLPAW, JONATHAN: Brain-Computer Interfaces: Principles and Practice. New York: Oxford University Press, 2012.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.