A Storytelling Robot for People with Dementia

Keeping people with dementia and family members involved in the storytelling process

Bachelor Thesis (2025)
Author(s)

Sutac (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Mark Neerincx – Mentor (TU Delft - Interactive Intelligence)

P.G.T. Raingeard de la Blétière – Mentor (TU Delft - Interactive Intelligence)

C. Lofi – Graduation committee member (TU Delft - Web Information Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2025
Language
English
Graduation Date
25-06-2025
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Storytelling has many benefits for people with dementia (PwD), such as improved well-being, confidence and communication. However, there is not much research on robots conducting such activities in dementia care. Thus, the goal of this project was to implement a system that can facilitate a storytelling session between PwD and their family members, keeping them involved through the entire process.

The system uses a Large Language Model (LLM), specifically Gemma 3, to generate responses to user's messages based on carefully written prompts. Other strategies used to facilitate this system are separation of the storytelling phases, turn-taking, story personalisation based on participant's wishes and empathetic responses to participant's responses. To test the system, personas based on PwD and their family members were used.

The results showed that the system successfully facilitates a storytelling session, following the different phases and keeping the participants involved in the process. However, some unexpected behaviour was noticed, for example not switching from one phase to the other on time. These findings demonstrate the potential of LLM-based storytelling robots in dementia care, while also underlining the need for further refinement and testing with real users.

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