Control and Monitor of IoT Devices using EOG and Voice Commands
Abstract
Keywords
Supporting Institution
References
- C.KavithaandG.Nagappan,"Sensing and processing of EOG signals to control human machine interface system, "international journal of since, engineering and technology research(IJSETR), vol. 4, no. 4, pp. 1330-1336, 2015.
- D.A. Thirugnanam,"Development of EOG Based Human Machine Interface Control System for Motorized Wheelchair," Department of Biotechnology and Medical Engineering india 769 008, 2013
- A. Jambhulkar, S. Wandhare, D. Baraskar, and K. Barahate,"Wireless and portable EOG based interface for controlling wheelchair, "IntJSciEng TechnolRes, vol.5,pp . 189-191,2016.
- U. Siddiqui and A. Shaikh, "An overview of electrooculography," International Journal of AdvancedResearchinComputerandCommunicationEngineering,vol.2,no.11,pp.4328-4330, 2013.
- R. Naga, S. Chandralingam, T. Anjaneyulu, and K. Satyanarayana, "Denoising EOG signal using stationary wavelet transform," Measurement Science Review, vol. 12, no. 2, pp. 46-51, 2012.
- Qusay F. Hassan, "Introduction to the Internet of Things," in Internet of Things A to Z: Technologies and Applications , IEEE, 2018.
- A. McEwen and H. Cassimally, Designing the Internet of Things. Wiley, 2013.
- K. K. Patel and S. M. Patel, "Internet of things-IOT: definition, characteristics, architecture, enabling technologies, application & future challenges," International journal of engineering science and computing, vol. 6, no. 5, 2016.
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Authors
Ayman Wazwaz
*
0000-0003-2405-2289
Palestine
Mohammad Ziada
0000-0003-4998-8737
Palestine
Lubna Awawdeh
This is me
0000-0002-2106-9512
Palestine
Mutaz Tahboub
This is me
0000-0003-4600-689X
Palestine
Publication Date
October 1, 2020
Submission Date
September 18, 2020
Acceptance Date
September 30, 2020
Published in Issue
Year 1970 Volume: 8 Number: 3
Cited By
Non-invasive technique to detect diabetic retinopathy based on Electrooculography signal using machine learning classifiers
Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine
https://doi.org/10.1177/09544119221085422