Effective stress detection using physiological parameters

In today's word one of the major leading factors to health problem is STRESS. The basic parameters on which stress can be identified are heart rate, galvanic skin response, body temperature, blood pressure, which provides detailed information of the state of mind of a person. These parameters varying from person to person on the basis of certain things such as their body condition, age and gender. The main goal of the system is to analyze the mental stress through physiological data using electrocardiograph in different positions and moods. Different pre-processing techniques can be used for stress detection. In feature extraction discrete wavelet transform can apply. Many classifiers like artificial neural network, support vector machine, Bayesian network, and decision tree are using to get more accurate results based on accuracy.

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

[2]  Atlee Fernandes,et al.  Determination of stress using Blood Pressure and Galvanic Skin Response , 2014, 2014 International Conference on Communication and Network Technologies.

[3]  Gonzalo Bailador,et al.  Stress detection by means of stress physiological template , 2011, 2011 Third World Congress on Nature and Biologically Inspired Computing.

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

[5]  Mykola Pechenizkiy,et al.  Stress detection from speech and Galvanic Skin Response signals , 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

[6]  C. Rotariu,et al.  Mental stress detection using heart rate variability and morphologic variability of EeG signals , 2012, 2012 International Conference and Exposition on Electrical and Power Engineering.

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

[8]  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.

[9]  W. Roth,et al.  Distinguishing emotional from physical activation in ambulatory psychophysiological monitoring. , 2006, Biomedical sciences instrumentation.

[10]  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.

[11]  J.H.M. Tulen,et al.  The effects of physical activities on cardiovascular variability in ambulatory situations [ECG/accelerometry analysis] , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[12]  Begoña García Zapirain,et al.  A Stress Sensor Based on Galvanic Skin Response (GSR) Controlled by ZigBee , 2012, Sensors.