The purpose of this project is to develop a novel proof-of-concept system in attempt to measure affective states during learning-tasks and investigate whether machine learning models trained with this data has the potential to enhance the learning experience for an individual. By considering biometric signals from a user during a learning session, the affective states anxiety, engagement and boredom will be classified using different signal transformation methods and finally using machine-learning models from the Weka Java API. Data is collected using an Empatica E4 Wristband which gathers skin- and heart related biometric data which is streamed to an Android application via Bluetooth for processing. Several machine-learning algorithms and features were evaluated for best performance.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-61648 |
| Date | January 2017 |
| Creators | Grundtman, Per |
| Publisher | Luleå tekniska universitet, Institutionen för system- och rymdteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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