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Lightweight Headgear Brain Waves for Fatigue Detection in Smartphone


Affiliations
1 Department of Computer Science & Information Engineering, Chang Jung Christian University, Taiwan, Province of China
 

Fatigue is an annoying phenomenon that can affect people’s concentration on learning or working. It will reduce the learning efficiency of people and even cause danger in working. For example, fatigue driving results in car accident have been reporting from the daily news. In order to avoid the accidents mentioned above, this research design the mobile system to detect fatigue to alert people by way of the lightweight brainwave detector, and the smartphone that everyone owns nowadays. In this system, light weight head mounted brainwave device is adopted and the signal are transmitted to the smartphone for further processing. Our algorithm calculates the fatigue index by focus, eyes blink frequency, δ-wave, α-wave, β-wave, and θ-wave captured from the brainwave to determine human’s spiritual condition. When the experimental results were carried out to the car drivers, the system can remind drivers when they were tired and drowsy while driving. This system can notify people to aware his own spiritual state so as to raise working efficacy and avoid the occurrences of accident caused by fatigue. In addition, the whole system without complex instrument and expensive cost.

Keywords

Brainwave Device, Fatigue Detecting, Smartphone, Headgear.
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  • Lightweight Headgear Brain Waves for Fatigue Detection in Smartphone

Abstract Views: 411  |  PDF Views: 169

Authors

Yung Gi Wu
Department of Computer Science & Information Engineering, Chang Jung Christian University, Taiwan, Province of China
Jwu Jenq Chen
Department of Computer Science & Information Engineering, Chang Jung Christian University, Taiwan, Province of China
Rui Hsin Wang
Department of Computer Science & Information Engineering, Chang Jung Christian University, Taiwan, Province of China

Abstract


Fatigue is an annoying phenomenon that can affect people’s concentration on learning or working. It will reduce the learning efficiency of people and even cause danger in working. For example, fatigue driving results in car accident have been reporting from the daily news. In order to avoid the accidents mentioned above, this research design the mobile system to detect fatigue to alert people by way of the lightweight brainwave detector, and the smartphone that everyone owns nowadays. In this system, light weight head mounted brainwave device is adopted and the signal are transmitted to the smartphone for further processing. Our algorithm calculates the fatigue index by focus, eyes blink frequency, δ-wave, α-wave, β-wave, and θ-wave captured from the brainwave to determine human’s spiritual condition. When the experimental results were carried out to the car drivers, the system can remind drivers when they were tired and drowsy while driving. This system can notify people to aware his own spiritual state so as to raise working efficacy and avoid the occurrences of accident caused by fatigue. In addition, the whole system without complex instrument and expensive cost.

Keywords


Brainwave Device, Fatigue Detecting, Smartphone, Headgear.

References