Detecting attention level as a warning sign for online classes by using EEG signals

2021 ◽

Vol 2120 (1) ◽

pp. 012028

Author(s):

J W Ong ◽

W J Chew ◽

S K Phang

Keyword(s):

Image Processing ◽

Facial Expression ◽

Facial Features ◽

Online Classes ◽

Main Method ◽

Online Class ◽

The World ◽

Attention Level

Abstract With the COVID-19 pandemic still causing the world to be quarantined in their house to prevent the spread of the virus, this means online classes are still the main method of conducting classes. This project aims to help lecturers monitor the students during class as they are having problems checking whether the students are paying attention or not. This project uses the student’s facial features to determine their attention level using two different coding algorithm Viola-Jones and Sobel edge. These two algorithms help to determine what kind of facial expression that the students are making. The Viola-Jones algorithm detects and captures the student’s facial features such as eyes and mouth while the Sobel edge algorithm detects the edges of the facial features to determine whether the eyes and mouth are open or closed. With the data collected it will run through the database to determine the student’s attention level and inform the lecturer.

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Complexity Measures of Brain Electrophysiological Activity

Journal of Psychophysiology ◽

10.1027/0269-8803/a000024 ◽

2010 ◽

Vol 24 (2) ◽

pp. 131-135 ◽

Cited By ~ 5

Author(s):

Włodzimierz Klonowski ◽

Pawel Stepien ◽

Robert Stepien

Keyword(s):

Brain Activity ◽

Deterministic Chaos ◽

Epileptic Seizures ◽

Eeg Signal ◽

Eeg Signals ◽

Complexity Measures ◽

Electrophysiological Activity ◽

Signal Complexity ◽

Physiological Sleep ◽

The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

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Attention level and visual and auditory monitoring performance

PsycEXTRA Dataset ◽

10.1037/e486812008-001 ◽

1962 ◽

Keyword(s):

Auditory Monitoring ◽

Attention Level ◽

Monitoring Performance

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Does Community of Inquiry Predict Self-Regulation for Undergraduates in Online Classes?

PsycEXTRA Dataset ◽

10.1037/e508232019-001 ◽

2019 ◽

Author(s):

Jati Ariati ◽

Mike Yough ◽

Jane Vogler ◽

William James ◽

Jun Fu ◽

...

Keyword(s):

Community Of Inquiry ◽

Self Regulation ◽

Online Classes

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Are online classes for you? Prepare yourself to e-learn with this advice from online instruction experts

PsycEXTRA Dataset ◽

10.1037/e600932009-013 ◽

2009 ◽

Author(s):

Jamie Chamberlin

Keyword(s):

Online Instruction ◽

Online Classes

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NON-INVASIVE BCI METHOD: EEG - ELECTROENCEPHALOGRAPHY

International Conference on Technics Technologies and Education ◽

10.15547/ictte.2019.02.095 ◽

2019 ◽

pp. 139-145

Author(s):

Selma Büyükgöze

Keyword(s):

Brain Computer Interface ◽

Computer Interface ◽

Electrode Placement ◽

Eeg Signals ◽

Non Invasive ◽

Brain Signals ◽

Brain States ◽

The Brain

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.

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