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Presented: Deng-Sing YangAdviser: Chih-Kuo Liang
Date:2012.03.14
Potential Overwork Exposure System
Potential Overwork Exposure System
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OUTLINE
Future works4
References5
Introduction1
Materials & Methods2
Results3
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INTRODUCTION
Fatigue is usually a scenario seen during continuous work or driving
Reduces a person’s attention and concentration Loss of ability to sustain a required performance
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INTRODUCTION
Another aspect that needs to be noticed is that children and teenagers alike spend quite a number of hours playing video games
Children may keep on going over their limit that could eventually post significant health issues.
Symptoms include mood shifts, sleep dysregulation, inability to concentrate, appetite lost and among others
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In recent years, computer games has been a part of a college student’s life. In fact many consider it equally important with their textbooks and exams.
Males love to play PC games more than female
INTRODUCTION
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Cases of Sudden Deaths in Gaming
05/22/2008 Male, 43 after 20 hrs
12/10/2008 Male, 39 internet café
07/31/2010 Male, 50 internet café
07/28/2011 Boy after 3 hours
09/28/2011 Female, after 6 hours
02/03/2012 Male, 23 after 23 hours
Suddenly died playing an online game while maintaining playing posture
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New trends in fatigue monitoring
SmartCap monitors workers' fatigue levels by reading their brain waves
It measures employee fatigue in real time by monitoring its wearer's brain waves.
From: 《 gizmag 》 January 30, 2012
3G video driver
fatigue detectionVideo supervision:
Driver reminder via face location, eye location and tracking of fatigue judgment.
From: 《 Electronic Science and Technology 》 November ,2011
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How did we choose this game?
NBA2k12 is a competitive sports game that makes a perfect combination with the NBA culture.
The game requires a lot of attention
and cognitive analysis something in comparison to a person working
New trends in fatigue monitoring
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Why use a single channel wireless EEG?
Three main reasons for using wireless EEG: Most promising technology Convenience Easy integration to software Ease of integration for future commercial purposes
Single channel EEG on the forehead with data transmitted wirelessly via Bluetooth while keeping track of the fatigue condition of the player.
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MATERIALS
AND
METHODOLOGY
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SUBJECTS
2 Male, Average age 27.5 years old
Recording: 5 minutes baseline 1 game of 12 minutes for each period Approximately 1 hour or more of data collection
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Research on fatigue detection
Physiological signals used to detect fatigueEEG, EOG, ECG and sEMGEOG being the most mature while EEG the
most promising method of detecting fatigue.
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Feature extraction methods
Software used: LabVIEW
• VISA for Bluetooth interconnection• Pt. by pt. 5th order Butterworth filter• Harmonic frequencies: Delta, Theta, Alpha1, Alpha2, Beta1 & Beta2• Auto power spectrum of the frequency bands
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Analysis methods
(Alpha + Theta) / Beta ratio as a figure to measure fatigue.
Three kinds of EEG energy ratios (index ratio) : (α+θ)/β: (fatigue and drowsiness level) θ/α: Relaxation level (relaxation level) β/α: Awakening of standards (alertness level)
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How did we determine the fatigue levels?
Fatigue assessment test platform in accordance with the EEG signal captured by the EEG amplifier, frequency-domain operations, according to the analysis rules of
Possible outcomes: Normal Mild Moderate Severe
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System architecture
Therefore, the aim of this system is to study how determine the state of fatigue during gaming through measurement, recording and analyzing the players’ EEG.
The algorithm to measure and determine fatigue has gone through several tests and evaluation thus providing an improved method of measuring fatigue.
Results are then displayed through a user friendly and informative GUI.
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Results and Discussion
GUI
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RESULTS
Player 1(Baseline: 2.77)
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RESULTS
Player 2 (Baseline: 3.45 )
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FUTURE WORKS
The current system relies on a computer and in the future we are looking into using Android- based mobile phone to make it more practical.
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REFERENCES
[1] Y. Shigihara and M. Tanaka, “Relationship between fatigue and photosensitivity,” Behavioral Medicine, vol. 36, pp. 109-112, 2010.
[2] S. Otmani, T. Pebayle, J. Roge, and A. Muzet, “Effect of driving duration and partial sleep deprivation on subsequent alertness and performance of cars drivers,” Physiology and Behavior, vol. 84, pp. 715-724, 2005.
[3] J. Solodar, “Seizures triggered by video games: underestimated and undiagnosed,” taken from http://www.epilepsy.com/pdfs/journal/EIS-Issue3-2.pdf, accessed on December 18, 2011.
[4] Y. Dong, Z. Hu, K. Uchimura, and N. Murayama, “Driver inattention monitoring system for intelligent vehicles: a review,” IEEE Trans on Intelligent Transportations Systems, vol. 12, no. 2, pp. 596-614, 2011.
[5] B. T. Jap, S. Lal, P. Fischer, and E. Bekiaris, “Using EEG spectral components to assess algorithms for detecting fatigue,” Expert Systems with Applications, vol. 36, pp. 2352-2359, 2009.
[6] H. J. Eoh, M. K. Chung, and S.-H. Kim, “Electroencephalographic study of drowsiness in simulated driving with sleep deprivation,” Industrial Ergonomics, vol. 35, pp. 307-320, 2005.
[7] S. K. L. Lal, and A. Craig, “A critical review of the psychophysiology of driver fatigue,” Biological Psychology, vol. 55, pp. 173-194, 2001.
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