IoT based brain-wave assistive system for paralyzed individuals
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2020.
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BRAC University
2021
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10361-145192021-06-10T21:01:19Z IoT based brain-wave assistive system for paralyzed individuals Monowara, Syeda Maliha Shariar, Md Ahnaf Islam, Md. Shafayat Ul Jawad, Muhammed Junaid Noor Sabuj, Saifur Rahman Huda, A.S. Nazmul Department of Electrical and Electronic Engineering, Brac University IoT Internet of Things BCI EEG FFT OpenBCI Bainwave 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). 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. Syeda Maliha Monowara Md Ahnaf Shariar Md. Shafayat Ul Islam Muhammed Junaid Noor Jawad B. Electrical and Electronic Engineering 2021-06-10T05:29:33Z 2021-06-10T05:29:33Z 2020 2020-12 Thesis ID: 16221043 ID: 16121078 ID: 15221001 ID: 14121044 http://hdl.handle.net/10361/14519 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 95 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
en_US |
| topic |
IoT Internet of Things BCI EEG FFT OpenBCI Bainwave |
| spellingShingle |
IoT Internet of Things BCI EEG FFT OpenBCI Bainwave Monowara, Syeda Maliha Shariar, Md Ahnaf Islam, Md. Shafayat Ul Jawad, Muhammed Junaid Noor IoT based brain-wave assistive system for paralyzed individuals |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2020. |
| author2 |
Sabuj, Saifur Rahman |
| author_facet |
Sabuj, Saifur Rahman Monowara, Syeda Maliha Shariar, Md Ahnaf Islam, Md. Shafayat Ul Jawad, Muhammed Junaid Noor |
| format |
Thesis |
| author |
Monowara, Syeda Maliha Shariar, Md Ahnaf Islam, Md. Shafayat Ul Jawad, Muhammed Junaid Noor |
| author_sort |
Monowara, Syeda Maliha |
| title |
IoT based brain-wave assistive system for paralyzed individuals |
| title_short |
IoT based brain-wave assistive system for paralyzed individuals |
| title_full |
IoT based brain-wave assistive system for paralyzed individuals |
| title_fullStr |
IoT based brain-wave assistive system for paralyzed individuals |
| title_full_unstemmed |
IoT based brain-wave assistive system for paralyzed individuals |
| title_sort |
iot based brain-wave assistive system for paralyzed individuals |
| publisher |
BRAC University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14519 |
| work_keys_str_mv |
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