System for classroom performance evaluation through EEG and motion sensing
The main aim of this project System for Classroom Performance Evaluation Through EEG and Motion Sensing, code named ELETA (Effective Learning Evaluation through Attentiveness) is to make a system that can provide us the attentiveness of the individual students present during the class lecture using...
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sg-ntu-dr.10356-599322023-03-03T20:45:15Z System for classroom performance evaluation through EEG and motion sensing Gehan Kaushal Priyadharsana Chan Syin School of Computer Engineering A*STAR DRNTU::Engineering::Computer science and engineering The main aim of this project System for Classroom Performance Evaluation Through EEG and Motion Sensing, code named ELETA (Effective Learning Evaluation through Attentiveness) is to make a system that can provide us the attentiveness of the individual students present during the class lecture using subject’s brain waves and head motion. It facilitates the individual students to have their record of attentiveness during every lecture they have taken and their overall performance as well based on a performance evaluation. The lecturer/teacher has access to see each and every individual’s attentiveness performance real-time. This enables the lecturer/teacher to be more engaging with the students and specially take care of the students who are lacking the attentiveness at particular time to enhance the learning experience effectively. The project comprises of development of hardware and the software parts. The hardware part includes the making of the multi-modal headband that includes all the sensors. We have found an EEG device available in the market namely “NeruoSky Mindwave”. The existing Mindwave headband of NeuroSky was customized to meet our requirement. We have hacked the ThinkGear AM chip in Mindwave for the acquisition of EEG sensor data and Inertial Measurement Unit was used to obtain movement parameters specially for the head movement tracking of the subject. Arduino Pro Mini microcontroller was used to handle all EEG data, IMU data and send it on high-speed to the Bluetooth device (Android Smartphone) via a Bluetooth modem. The software part includes the application software development namely Android app development, Client desktop application development and server side development. Android app’s main functionality to provide the DAQ (data acquisition) from multi- modal headband in user side and Client desktop application’s to show (visualize platform) relevant real-time attentiveness of subjects’ (for teachers/lectures) via the server. This report describes the overall steps to develop hardware and software development for the completion of ELETA (Effective Learning Evaluation through Attentiveness) system. Bachelor of Engineering (Computer Engineering) 2014-05-19T08:08:53Z 2014-05-19T08:08:53Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/59932 en Nanyang Technological University 78 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering Gehan Kaushal Priyadharsana System for classroom performance evaluation through EEG and motion sensing |
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The main aim of this project System for Classroom Performance Evaluation Through EEG and Motion Sensing, code named ELETA (Effective Learning Evaluation through Attentiveness) is to make a system that can provide us the attentiveness of the individual students present during the class lecture using subject’s brain waves and head motion. It facilitates the individual students to have their record of attentiveness during every lecture they have taken and their overall performance as well based on a performance evaluation. The lecturer/teacher has access to see each and every individual’s attentiveness performance real-time. This enables the lecturer/teacher to be more engaging with the students and specially take care of the students who are lacking the attentiveness at particular time to enhance the learning experience effectively.
The project comprises of development of hardware and the software parts. The hardware part includes the making of the multi-modal headband that includes all the sensors. We have found an EEG device available in the market namely “NeruoSky Mindwave”. The existing Mindwave headband of NeuroSky was customized to meet our requirement. We have hacked the ThinkGear AM chip in Mindwave for the acquisition of EEG sensor data and Inertial Measurement Unit was used to obtain movement parameters specially for the head movement tracking of the subject. Arduino Pro Mini microcontroller was used to handle all EEG data, IMU data and send it on high-speed to the Bluetooth device (Android Smartphone) via a Bluetooth modem.
The software part includes the application software development namely Android app development, Client desktop application development and server side development. Android app’s main functionality to provide the DAQ (data acquisition) from multi- modal headband in user side and Client desktop application’s to show (visualize platform) relevant real-time attentiveness of subjects’ (for teachers/lectures) via the server.
This report describes the overall steps to develop hardware and software development for the completion of ELETA (Effective Learning Evaluation through Attentiveness) system. |
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Chan Syin |
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Chan Syin Gehan Kaushal Priyadharsana |
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Final Year Project |
author |
Gehan Kaushal Priyadharsana |
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Gehan Kaushal Priyadharsana |
title |
System for classroom performance evaluation through EEG and motion sensing |
title_short |
System for classroom performance evaluation through EEG and motion sensing |
title_full |
System for classroom performance evaluation through EEG and motion sensing |
title_fullStr |
System for classroom performance evaluation through EEG and motion sensing |
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System for classroom performance evaluation through EEG and motion sensing |
title_sort |
system for classroom performance evaluation through eeg and motion sensing |
publishDate |
2014 |
url |
http://hdl.handle.net/10356/59932 |
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1759856831915622400 |