Recognizing mental stress in chess players using vital sign data
| Autor: | Christopher Eggert, Miguel A. Labrador, Oscar D. Lara |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Android phone
Computer science business.industry medicine.disease_cause Machine learning computer.software_genre Task (project management) Identification (information) Human–computer interaction Mental stress Stress (linguistics) medicine Psychological stress Artificial intelligence business computer Sign (mathematics) |
| Zdroj: | 2013 Proceedings of IEEE Southeastcon. |
| DOI: | 10.1109/secon.2013.6567512 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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