Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.799755
Title: Visible light optical camera communication for electroencephalography applications
Author: Aggarwal, Geetika
ISNI:       0000 0004 8506 2517
Awarding Body: Northumbria University
Current Institution: Northumbria University
Date of Award: 2020
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Abstract:
Due to the cable-free deployment and flexibility of wireless communications, the data transmission in the applications of home and healthcare has shown a trend of moving wired communications to wireless communications. One typical example is electroencephalography (EEG). Evolution in the radio frequency (RF) technology has made it is possible to transmit the EEG data without data cable bundles. However, presently, the RF-based wireless technology used in EEG suffers from electromagnetic interference and might also have adverse effects on the health of patient and other medical equipment used in hospitals or homes. This puts some limits in RF-based EEG solutions, which is particularly true in RF restricted zones like Intensive Care Units (ICUs). As a recently developed optical wireless communication (OWC) technology, visible light communication (VLC) using light-emitting diodes (LEDs) for both simultaneous illumination and data communication has shown its advantages of free from electromagnetic interference, potential huge unlicensed bandwidth and enhanced data privacy due to the line transmission of light. The most recent development of VLC is the optical camera communication (OCC), which is an extension of VLC IEEE standard 802.15.7, also referred to as visible light optical camera communication (VL-OCC). Different from the conventional VLC where traditional photodiodes are used to detect and receive the data, VL-OCC uses the imaging camera as the photodetector to receive the data in the form of visible light signals. The data rate requirement of EEG is dependent on the application; hence this thesis investigates a low cost, organic LED (OLED)-driven VL-OCC wireless data transmission system for EEG applications.
Supervisor: Dai, Xuewu ; Binns, Richard ; Saatchi, Reza Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.799755  DOI: Not available
Keywords: F300 Physics ; G100 Mathematics ; G400 Computer Science ; H600 Electronic and Electrical Engineering
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