Real Time Vigilance Detection using Frontal EEG
نویسندگان
چکیده
Vigilance of an operator is compromised in performing many monotonous activities like workshop and manufacturing floor tasks, driving, night shift workers, flying, general any activity which requires keen attention individual over prolonged periods time. Driver or fatigue these situations leads to drowsiness lowered vigilance one the largest contributors injuries fatalities amongst road accidents accidents. Having a monitoring system detect drop becomes very important. This paper presents uses non-invasively recorded Frontal EEG from easy-to-use commercially available Brain Computer Interface wearable device determine state individual. The change power spectrum Theta Band (4-8Hz) individual’s brain wave predicts changes level - providing early detection warning system. method provides accurate, yet cheap practical for across different environments.
منابع مشابه
Real Time Emotion Detection using EEG
Emotion is an important aspect in the interaction between humans. It is fundamental to human experience and rational decision-making. There is a great interest for detecting emotions automatically. A number of techniques have been employed for this purpose using channels such as voice and facial expressions. However, these channels are not very accurate and can be faked. In this thesis, we are ...
متن کاملENCARA: real-time detection of frontal faces
This paper describes a real-time approach for face detection and selection of frontal views, for further processing. Typically, face detection papers provide results for a set of single images but the problem of face detection in video streams rarely is tackled. Instead of performing an exhaustive search for every video stream frame a set of opportunistic ideas applied in a cascade fashion and ...
متن کاملReal Time Driver’s Drowsiness Detection by Processing the EEG Signals Stimulated with External Flickering Light
The objective of this study is development of driver’s sleepiness using Visually Evoked Potentials (VEP). VEP computed from EEG signals from the visual cortex. We use the Steady State VEPs (SSVEPs) that are one of the most important EEG signals used in human computer interface systems. SSVEP is a response to visual stimuli presented. We present a classification method to discriminate between...
متن کاملReal-Time EEG-Based Happiness Detection System
We propose to use real-time EEG signal to classify happy and unhappy emotions elicited by pictures and classical music. We use PSD as a feature and SVM as a classifier. The average accuracies of subject-dependent model and subject-independent model are approximately 75.62% and 65.12%, respectively. Considering each pair of channels, temporal pair of channels (T7 and T8) gives a better result th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Science and Information Technology
سال: 2021
ISSN: ['0975-4660', '0975-3826']
DOI: https://doi.org/10.5121/ijcsit.2021.13104