Enrique is a recently graduated Ph.D. and a member of the Collective Contextual Intelligence Research Group, Tecnologico de Monterrey University, Mexico. His research interests include: Ambient Intelligence, Human Activity Recognition, Machine learning, Pervasive Healthcare, Wearable sensors, etc.
email: e.g.mx (at) ieee.org
Stress Detection through Smartphones' data. With the new advent of wearable devices and their associated embedded sensors, it has become possible to collect data from which contextual and behavioral information can be extracted. This work focuses on detecting different stress levels in working environments by analyzing sensor data from smartphones.
Papers: Garcia-Ceja, E., Venet Osmani, Oscar Mayora. "Automatic Stress Detection in Working Environments from Smartphones' Accelerometer Data: A First Step". Biomedical and Health Informatics, IEEE Journal of, vol. 20, no. 4, pp. 1053-1060, July 2016.
Papers: Garcia-Ceja, E., R. Brena, J.C. Carrasco-Jimenez, L. Garrido. "Long-Term Activity Recognition from Wristwatch Accelerometer Data". Sensors journal v.14, No.12, pp.22500-22524, doi:10.3390/s141222500, MDPI, 2014. [pdf]
Papers: Garcia-Ceja, E. & Brena, R. & Galván-Tejada, C. "Contextualized Hand Gesture Recognition with Smartphones". MCPR 2014: 6th Mexican Conference on Pattern Recognition, June 25-28th, Cancun, Mexico, Lecture Notes in Computer Science Volume 8495, pp 122-131, 2014. [pdf]