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    •   BracU IR
    • School of Engineering (SoE)
    • Department of Electrical and Electronic Engineering (EEE)
    • Thesis & Report, BSc (Electrical and Electronic Engineering)
    • View Item
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    IoT based brain-wave assistive system for paralyzed individuals

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    16221043, 16121078, 15221001, 14121044_EEE.pdf (3.425Mb)
    Date
    2020-12
    Publisher
    BRAC University
    Author
    Monowara, Syeda Maliha
    Shariar, Md Ahnaf
    Islam, Md. Shafayat Ul
    Jawad, Muhammed Junaid Noor
    Metadata
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    URI
    http://hdl.handle.net/10361/14519
    Abstract
    Individuals suffering from severe paralysis encounter a multitude of issues that influence their quality of life. Paralysis can occur due to impairments of the central nervous system (CNS) causes by brain-stroke, accidents, neurodegenerative dysfunctions or other factors. A significant portion of our society endures the consequences that limit their physical functionalities such as movement, communication, task performances and so on. In recent decades, technology has made substantial assistive devices that can communicate the brainwave signals and interpret these into commands. The development of the brain-computer interface (BCI) depends on the electric impulses generated in the brain. Hence, this can consequently be implemented for improvement purposes, that can eventually help to overcome the aspects of functional disabilities. To resolve the obstacles associated with paralysis, this project of the brainwave-assistive system is based on the internet-of-things (IoT). The system will be further comprised of multiple sensors that continuously acquire the brainwave frequencies for implementation through the connected microcontroller. For this project, the Cyton biosensing boards along with the WiFi shield have been utilised to read the generated electric signals from the brain which have been differentiated as per the functionality requirements. The WiFi shield enables the accumulated data to be saved in the database henceforth can be accessed at any instance (in real-time basis) through the software application. We have observed feedback generation through a microcontroller, we have further transmitted the data utilizing LSL to Python for the control of computer application. Furthermore, we intend to develop a mobile application that will frequently update the data that would enable the user to visualize the brainwave signals on a dashboard. Further research is required for a better understanding of the system to implement for extensive purposes such as home enhanced mobility, appliance control, emergency alarm-system and so forth.
    Keywords
    IoT; Internet of Things; BCI; EEG; FFT; OpenBCI; Bainwave
     
    Description
    This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2020.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (pages 83-94).
    Department
    Department of Electrical and Electronic Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Electrical and Electronic Engineering)

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