Secure access control by means of human stress detection

This paper proposes a stress detection system based on fuzzy logic and the physiological signals heart rate and galvanic skin response. The main contribution of this method relies on the creation of a stress template, collecting the behaviour of previous signals under situations with a different level of stress in each individual. The creation of this template provides an accuracy of 99.5% in stress detection, improving the results obtained by current pattern recognition techniques like GMM, k-NN, SVM or Fisher Linear Discriminant. In addition, this system can be embedded in security systems to detect critical situations in accesses as cross-border control. Furthermore, its applications can be extended to other fields as vehicle driver state-of-mind management, medicine or sport training.

[1]  Johannes Wagner,et al.  From Physiological Signals to Emotions: Implementing and Comparing Selected Methods for Feature Extraction and Classification , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[2]  H. Cai,et al.  An Experiment to Non-Intrusively Collect Physiological Parameters towards Driver State Detection , 2007 .

[3]  M.S. Sharawi,et al.  Design and implementation of a human stress detection system: A biomechanics approach , 2008, 2008 5th International Symposium on Mechatronics and Its Applications.

[4]  Elisabeth André,et al.  Emotion recognition based on physiological changes in music listening , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  A. C. Vindel,et al.  Hiperventilación y experiencia de ansiedad , 2007 .

[6]  A. Barreto,et al.  Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[7]  David J. Spiegelhalter,et al.  Machine Learning, Neural and Statistical Classification , 2009 .

[8]  Lipo Wang,et al.  Data Mining With Computational Intelligence , 2006, IEEE Transactions on Neural Networks.

[9]  Mitsuru Ishizuka,et al.  Symmetric Multimodality Revisited: Unveiling Users' Physiological Activity , 2007, IEEE Transactions on Industrial Electronics.

[10]  Chao Li,et al.  Realization of stress detection using psychophysiological signals for improvement of human-computer interactions , 2005, Proceedings. IEEE SoutheastCon, 2005..

[11]  D. N. Geary Mixture Models: Inference and Applications to Clustering , 1989 .

[12]  Tao Lin,et al.  Do physiological data relate to traditional usability indexes? , 2005, OZCHI.

[13]  K. Guney,et al.  COMPARISON OF MAMDANI AND SUGENO FUZZY INFERENCE SYSTEM MODELS FOR RESONANT FREQUENCY CALCULATION OF RECTANGULAR MICROSTRIP ANTENNAS , 2009 .

[14]  Emil Jovanov,et al.  Stress monitoring using a distributed wireless intelligent sensor system. , 2003, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[15]  신재우,et al.  Chronic Stress Evaluation using Neuro-Fuzzy , 2003 .

[16]  M. Zvolensky,et al.  A review of psychological factors/processes affecting anxious responding during voluntary hyperventilation and inhalations of carbon dioxide-enriched air. , 2001, Clinical psychology review.

[17]  Dana Kulic,et al.  Anxiety detection during human-robot interaction , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Zhelong Wang,et al.  A Method for Stress Detection Based on FCM Algorithm , 2009, 2009 2nd International Congress on Image and Signal Processing.

[19]  Dimitris N. Metaxas,et al.  Monitoring of facial stress during space flight: Optical computer recognition combining discriminative and generative methods , 2007 .

[20]  Jennifer A. Healey,et al.  Wearable and automotive systems for affect recognition from physiology , 2000 .

[21]  Christine L. Lisetti,et al.  Using Noninvasive Wearable Computers to Recognize Human Emotions from Physiological Signals , 2004, EURASIP J. Adv. Signal Process..

[22]  Peter Funk,et al.  A Case-Based Approach Using Behavioural Biometrics to Determine a User's Stress Level , 2005, ICCBR Workshops.

[23]  Gonzalo Bailador,et al.  Pattern recognition using temporal fuzzy automata , 2010, Fuzzy Sets Syst..

[24]  Gonzalo Bailador,et al.  Two Stress Detection Schemes Based on Physiological Signals for Real-Time Applications , 2010, 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[25]  Mobyen Uddin Ahmed,et al.  Using Calibration and Fuzzification of Cases for Improved Diagnosis and Treatment of Stress , 2006 .

[26]  Lan Li,et al.  Emotion Recognition Using Physiological Signals from Multiple Subjects , 2006, 2006 International Conference on Intelligent Information Hiding and Multimedia.

[27]  Nilanjan Sarkar,et al.  Psychophysiological control architecture for human-robot coordination-concepts and initial experiments , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[28]  Armando Barreto,et al.  Electromyograms as Physiological Inputs that Provide Efficient Computer Cursor Control , 2005 .

[29]  Jennifer Healey,et al.  Detecting stress during real-world driving tasks using physiological sensors , 2005, IEEE Transactions on Intelligent Transportation Systems.

[30]  Lotfi A. Zadeh,et al.  Fuzzy logic = computing with words , 1996, IEEE Trans. Fuzzy Syst..

[31]  Jae-Yeon Shin,et al.  Estimation of stress status using biosignal and fuzzy theory , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).

[32]  Liu Guang-yuan,et al.  Emotion Recognition of Physiological Signals Based on Adaptive Hierarchical Genetic Algorithm , 2009, 2009 WRI World Congress on Computer Science and Information Engineering.

[33]  Gonzalo Bailador,et al.  A Stress-Detection System Based on Physiological Signals and Fuzzy Logic , 2011, IEEE Transactions on Industrial Electronics.

[34]  Armando Barreto,et al.  Stress detection in computer users through non-invasive monitoring of physiological signals. , 2006, Biomedical sciences instrumentation.

[35]  Melody Moore Jackson,et al.  A galvanic skin response interface for people with severe motor disabilities , 2004, Assets '04.