Abstract
This paper discusses our work on discovering a set of emotional logic rules, derived from physiological data of individuals from a wearable technology perspective. We concentrated the analysis on physiological data such as plethysmography, respiration, galvanic skin response, and temperature that can be detected by wearable sensors. We sourced our data from the DEAP dataset, which is a popular labelled Affective Computing dataset. Our approach implemented a fusion of preprocessing and data mining techniques, to discover logic rules relating to the valence and arousal emotional dimensions. Our findings indicate that while there are similar changes in heart rates or galvanic skin response across individuals during emotional stimuli, every individual has a unique and quantifiable physiological reaction.
| Original language | English |
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| Title of host publication | Proceedings of 2019 International Conference on Machine Learning and Cybernetics, ICMLC 2019 |
| Place of Publication | Kobe, Japan |
| Publisher | IEEE Computer Society |
| Pages | 468-474 |
| Number of pages | 7 |
| ISBN (Electronic) | 9781728128160 |
| DOIs | |
| Publication status | Published - Jul 2019 |
| Event | 18th International Conference on Machine Learning and Cybernetics, ICMLC 2019: ICMLC 2019 - Kobe, Japan Duration: 07 Jul 2019 → 10 Jul 2019 https://translate.google.com/translate?hl=en&sl=ja&u=https://enotice.vtools.ieee.org/public/47253&prev=search (conference info) |
Publication series
| Name | Proceedings - International Conference on Machine Learning and Cybernetics |
|---|---|
| Volume | 2019-July |
| ISSN (Print) | 2160-133X |
| ISSN (Electronic) | 2160-1348 |
Conference
| Conference | 18th International Conference on Machine Learning and Cybernetics, ICMLC 2019 |
|---|---|
| Country/Territory | Japan |
| City | Kobe |
| Period | 07/07/19 → 10/07/19 |
| Internet address |