Cover Image

“Analysis of EEG Recordings During Grasp and Lift (GAL) Trials

EEG stands for Electroencephalography is a medical technique that is used to extract the signal in the brain by using a special medical device known as electroencephalogram. EEG signal is highly noisy as the signal is recorded from a scalp electrode that is influenced by different deeper brain st...

Full description

Saved in:
Bibliographic Details
Main Author: Musa, Huwaida
Format: Final Year Project
Language:English
Published: 2018
Online Access:http://utpedia.utp.edu.my/19173/1/Final%20Report%20FYP.pdf
http://utpedia.utp.edu.my/19173/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utp-utpedia.19173
record_format eprints
spelling my-utp-utpedia.191732019-06-20T08:44:24Z http://utpedia.utp.edu.my/19173/ “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials Musa, Huwaida EEG stands for Electroencephalography is a medical technique that is used to extract the signal in the brain by using a special medical device known as electroencephalogram. EEG signal is highly noisy as the signal is recorded from a scalp electrode that is influenced by different deeper brain structure. The changes of the signal with time make the signal to be non-stationary. The idea of using the EEG signal to extract the signals which related to object manipulation is reasonable as most of the human cortex involves in basic motor tasks of a person. However, until now there is uncertainty regarding what extent the extraction of signals from the human brain can be used in the monitoring and control purposes. The purpose of analysing this EEG data is to help develop a prosthetic device that can control an upper limb and generate a power grasp or a pinch grasp involving the thumb and index finger. Specifically for this project, we will focus on the process of analysing the EEG signal that includes the extraction of data, filtering data, applying feature extraction and performing classification of the EEG signal. This paper will review the step by step process involved in this project which is to classify the 6 different events or movement of grasping and lifting using the EEG recording of grasp and lift trial. The classification of the signals is done by using various classifiers that differentiate each of the 6 events and compute the percentage of accuracy for the correctly predicted events. There are two types of investigation which are classification with feature extraction and without feature extraction. Throughout this project, we managed to get the classification accuracy of 6 events for 26.6% and 58.5% while for 2 events of up to 67.4% and 96% using 6 channels for both algorithms respectively. 2018-09 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/19173/1/Final%20Report%20FYP.pdf Musa, Huwaida (2018) “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials. UNSPECIFIED.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
description EEG stands for Electroencephalography is a medical technique that is used to extract the signal in the brain by using a special medical device known as electroencephalogram. EEG signal is highly noisy as the signal is recorded from a scalp electrode that is influenced by different deeper brain structure. The changes of the signal with time make the signal to be non-stationary. The idea of using the EEG signal to extract the signals which related to object manipulation is reasonable as most of the human cortex involves in basic motor tasks of a person. However, until now there is uncertainty regarding what extent the extraction of signals from the human brain can be used in the monitoring and control purposes. The purpose of analysing this EEG data is to help develop a prosthetic device that can control an upper limb and generate a power grasp or a pinch grasp involving the thumb and index finger. Specifically for this project, we will focus on the process of analysing the EEG signal that includes the extraction of data, filtering data, applying feature extraction and performing classification of the EEG signal. This paper will review the step by step process involved in this project which is to classify the 6 different events or movement of grasping and lifting using the EEG recording of grasp and lift trial. The classification of the signals is done by using various classifiers that differentiate each of the 6 events and compute the percentage of accuracy for the correctly predicted events. There are two types of investigation which are classification with feature extraction and without feature extraction. Throughout this project, we managed to get the classification accuracy of 6 events for 26.6% and 58.5% while for 2 events of up to 67.4% and 96% using 6 channels for both algorithms respectively.
format Final Year Project
author Musa, Huwaida
spellingShingle Musa, Huwaida
“Analysis of EEG Recordings During Grasp and Lift (GAL) Trials
author_facet Musa, Huwaida
author_sort Musa, Huwaida
title “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials
title_short “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials
title_full “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials
title_fullStr “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials
title_full_unstemmed “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials
title_sort “analysis of eeg recordings during grasp and lift (gal) trials
publishDate 2018
url http://utpedia.utp.edu.my/19173/1/Final%20Report%20FYP.pdf
http://utpedia.utp.edu.my/19173/
_version_ 1739832597829124096
score 13.211869

Similar Items