Title :
Recognizing mental stress in chess players using vital sign data
Author :
Eggert, Christian ; Lara, Oscar D. ; Labrador, M.A.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
Abstract :
The identification of psychological stress can provide important feedback in order to perform critical activities. While a certain amount of stress may increase performance, an overly stressful reaction may hinder it. Because subjective bias can make it difficult to accurately recognize psychological stress, it would be advantageous for an external system to perform the task instead. We present a platform for psychological stress detection using physiological sensors during a chess match. The sensors are inside an unobtrusive chest strap that can be worn by the player during a match. By playing games on an Android phone, the system can apply machine learning techniques to the player´s vital sign data to give important feedback such as which moves caused the player to become stressed during a match.
Keywords :
Linux; computer games; learning (artificial intelligence); psychology; smart phones; Android phone; chess players; machine learning techniques; mental stress recognition; psychological stress identification; vital sign data; Feature extraction; Games; Heart rate; Physiology; Psychology; Sensors; Stress; Human activity recognition; structural pattern recognition;
Conference_Titel :
Southeastcon, 2013 Proceedings of IEEE
Conference_Location :
Jacksonville, FL
Print_ISBN :
978-1-4799-0052-7
DOI :
10.1109/SECON.2013.6567512