SMART WEARABLE STRESS MONITORING DEVICE FOR AUTISTIC CHILDREN
DOI:
https://doi.org/10.11113/jt.v78.9453Keywords:
Stress, tantrums, seizures, autistic children, anxietyAbstract
Vital sign monitoring is the process of recording human physiological signals in order to determine the mental stress level. High stress levels can prove to be dangerous especially for certain individuals such as autistic children who are not able to express mounting levels of stress before it leads to a full anxiety attack. This paper presents the prototype design of a real-time embedded device that accurately measures heart rate and galvanic skin response (GSR) in a non-invasive and non-intrusive way which is then used by the intelligent decision making module that uses fuzzy logic to determine the stress level of the user. Such a device could be used with autistic children in order to give early warning of an impending anxiety attack and help adults to prevent it from happening. The prototype was designed using Arduino mega platform and tested with 35 clinical patients in three experimental settings targeted to induce low stress, medium stress and high stress response. Initial results have shown that the device is capable of detecting and displaying the various stress levels efficiently.Â
References
Carneiro, D., J. C. Castillo, P. Novais, A. F. Caballero, and J. Neves. 2012. Multimodal Behavioral Analysis for Non-Invasive Stress Detection. Expert Systems with Applications. 39(18): 13376-13389.
Motlagh, S. H. R. E., H. Moradi, and H. Pouretemad. 2013. Using General Sound Descriptors for Early Autism Detection. The 97h Asian Control Conference (ASCC 2013). Istanbul, Turkey.
Rahbar, M. H., K. Ibrahim, and P. Assassi. 2011. Knowledge and Attitude of General Practitioners Regarding Autism in Karachi, Pakistan. Journal of Autism Development Disorder. 41(4): 465-74.
Grissom, M. 2013. Neuropsychologist Developmental Assessment & Intervention Center Bedford Hills, NY 10507, Autism Spectrum Disorders. Virtual Health Care Team ® School of Health Professions University of Missouri-Columbia.
Creator of Rhythmic Entertainment Intervention (C. o. REI) - Strong Institute, Autism Case Studies.
Bakker, J., M. Pechenizkiy, and N. Sidorova. 2011. What's Your Current Stress Level? Detection of Stress Patterns from GSR Sensor Data. IEEE 11th International Conference on Data Mining Workshops. 573-580.
Fernandes, A., R. Helawar, R. Lokesh, T. Tari, and A. V. Shahapurkar. 2014. Determination of Stress using Blood Pressure and Galvanic Skin Response. International Conference on Communication and Network Technologies (ICCNT). 165-168.
Bakker, J., M. Pechenizkiy, and N. Sidorova. 2011. What's Your Current Stress Level? Detection of Stress Patterns from GSR Sensor Data. IEEE International Conference on Data Mining (ICDM). 1: 573-580.
Hamid B., A. Sheikhani, M. R. Mohammadi, M. Noroozian, and P. Golabi. 2007. Analyses of EEG Background Activity in Autism Disorders with Fast Fourier Transform and Short-Time Fourier Measure. International Conference on Intelligent and Advanced Systems. 1240-1244.
George, S. E, and J. M. Lating. 2013. A Clinical Guide to the Tretment of The Human Stress Response. 3rd Ed. New York: Springer.
Donna, E. S. 2011. Depression during Pregnancy. New England Journal of Medicine. 365(17): 1605-1611.
Wijsman, J., B. Grundlehner, H. Liu, H. Hermens, and J. Penders. 2011. Towards Mental Stress Detection using Wearable Physiological Sensors. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 1798-1801.
Madhuri, V. J., M. R. Mohan, and R. Kaavya. 2013. Stress Management using Artificial Intelligence. Third International Conference on Advances in Computing and Communications. 54-57.
Goel, I., and D. Kumar. 2015. Design and Implementation of Android Based Wearable Smart Locator Band for People with Autism, Dementia, and Alzheimer. Advances in Electronics. 1-8.
Sharawi, M. S., M. Shibli, and M. I. Sharawi. 2008. Design and Implementation of a Human Stress Detection System: A Biomechanics Approach. IEEE Proceeding of the 5th International Symposium on Mechatronics and its Applications (ISMA08). Amman, Jordan. 1-5.
De Santos Sierra, A., C. S. Avilla, J. G. Casanova, and G. B. del Pozo. 2011. A Stress-Detection System Based on Physiological Signals and Fuzzy Logic. IEEE Transactions on Industrial Electronics. 58(10): 4857-4865.
De Santos Sierra, A., C. S. Avilla, J. G. Casanova, G. B. del Pozo, and V. J. Vera. 2010. Two Stress Detection Schemes Based on Physiological Signals for Real-Time Applications. Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010 Sixth International Conference on. 1-4.
Zhai, J., A. B. Barreto, C. Chin, and C. Li. 2005. Realization of Stress Detection using Psychophysiological Signals for Improvement of Human-Computer Interactions. Proceedings of IEEE Southeast Conference. 415-420.
Madhuri, V. J., M. R. Mohan, and R. Kaavya. 2013. Stress Management using Artificial Intelligence. 2013 Third International Conference on Advances in Computing and Communications (ICACC). 54-57.
Sun, F-T., C. Kuo, H-T. Cheng, S. Buthpitiya, P. Collins, and M. Griss. 2012. Activity-Aware Mental Stress Detection using Physiological Sensors. Lecture Notes of Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 76: 211-230.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
