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A user self-reported emotion feedback system

Brouwer, Ruben (2018) A user self-reported emotion feedback system.

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Abstract:The Escalade, a prototype wearable with various sensors, shows great implementations for a mood-sensing method. Mood-sensing is important since it contains vital information useful in many professions and applications generating self-awareness, regarding communication, improving treatments in the therapeutic industry and optimising the caregiver-patient relationship to help promote general well being. One promising way to develop a mood-sensing method is a combination of the Escalade and machine learning. For making use of machine learning, you need a labelled dataset. A combination of physiological sensor data and mood labels to train an AI agent is achievable. Acquiring a mood label is challenging, since collecting spontaneous emotions and self-reported emotions are hard. The user should also be willing to give this self-reported emotion. The focus of this thesis is how to design an engaging mood experience self-sampling system and how to implement this in a prototype. To do so a combination of background research, state of the art research and many design techniques are used. This with a focus on hallway usability tests and user tests. Following from this a prototype is built and evaluated. The evaluation stated that however, the sample size is small, the prototype meets most requirements and is ready for implementation of artificial intelligence. Implemented can be some additional requirements can be implemented in future work.
Item Type:Essay (Bachelor)
Clients:
Sensoree, San Francisco, United States of America
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:53 electrotechnology, 54 computer science, 77 psychology
Programme:Creative Technology BSc (50447)
Link to this item:http://purl.utwente.nl/essays/75479
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