A portable and low-cost electroencephalography device with automated autism diagnosis
| dc.contributor.author | Lormenyo, Hannah Boadiwaa | |
| dc.date.accessioned | 2022-12-22T20:06:50Z | |
| dc.date.available | 2022-12-22T20:06:50Z | |
| dc.date.issued | 2021-05 | |
| dc.description | Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2021 | |
| dc.description.abstract | Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by challenges in speech and communication, impairment in social skills, and repetitive behavior. Autistic children in Africa have very severe symptoms of autism due to the lateness in the diagnosis and treatment of autism on the continent. This work explores the use of a portable, low-cost electroencephalography (EEG) device with automated diagnosis as a means of expediting the process of autism diagnosis in Africa. This work compares two instrumentation amplifier designs for the EEG system. It also compares k-nearest neighbor, support vector machine, decision tree, and random forest as classifiers for providing automated diagnosis for the EEG system. The resulting design was a portable EEG system that can be interfaced with a smartphone for real-time visualization of the EEG signals and automated diagnosis with an accuracy of 85.1%. | |
| dc.description.sponsorship | Ashesi University | |
| dc.identifier.uri | https://hdl.handle.net/20.500.11988/800 | |
| dc.language.iso | en | |
| dc.subject | portable EEG device | en |
| dc.subject | diagnosis | en |
| dc.title | A portable and low-cost electroencephalography device with automated autism diagnosis | |
| dc.type | Capstone project |
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