EEG	BASE BRAIN COMPUTER INTERFACE APPLICATION OF DETECTING HUMAN	GAIT ACTIVITY

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https://hdl.handle.net/2142/124880

Title: EEG BASE BRAIN COMPUTER INTERFACE APPLICATION OF DETECTING HUMAN GAIT ACTIVITY
Author(s): Okubo, Ryu
Issue Date: 2022-05-01
Keyword(s): EEG, gait activity, signal processing, machine learning, brain computer interface
Date of Ingest: 2024-10-15T10:51:27-05:00
Abstract: Traditionally, Brain-Computer Interface (BCI) study aims to establish or improve the communication between patients with permanent paralysis and their family or formal caretakers. Electroencephalogram (EEG) is one of the most common and well-known methods to develop BCI technology. This is because EEGs are usually cheap, easy to wear, and have a high temporal resolution. This study investigated the correlation between human gait activity and EEG data. From past studies, it was known that EEG could be used to detect human locomotor activities, but whether real time BCI applications can detect precise information (such as if a subject is in gait activity or not/ which gait stage they are in) is yet to be known. This study aims to establish a pipeline to detect human gait activity from EEG data with the help of signal processing, statistical analysis, and machine learning algorithms. The findings from this study may help establish or improve the current gait rehabilitation model and provide valuable information for human cortex involvement in gait activity.
Type of Resource: text
Genre of Resource: dissertation/thesis
Language: eng

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