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Co-STAR: Cognitive Stimulation Therapy by an Autonomous Robot for Dementia -- A One-Week In-Home Study

Researchers developed a social robot that autonomously delivers cognitive stimulation therapy (CST) to people with dementia in their homes. A one-week study with nine participants found high adherence rates (nearly 50% of sessions completed), surpassing typical caregiver-led CST. Family members played a key role in initiating sessions and occasionally joining activities, enhancing engagement. The work demonstrates the feasibility of socially assistive robots for scalable in-home dementia care.

SourcearXiv RoboticsAuthor: Emmanuel Akinrintoyo, Nicole Salomons

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[Submitted on 7 Jul 2026]

Title:Co-STAR: Cognitive Stimulation Therapy by an Autonomous Robot for Dementia -- A One-Week In-Home Study

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Abstract:Cognitive therapies have been shown to enhance the quality of life and well-being of people living with dementia (PwDs). However, their use remains limited due to a shortage of trained professionals and the significant time and training required of informal caregivers. To address this gap, we developed and deployed a social robot capable of autonomously delivering cognitive stimulation therapy (CST) in the home. Nine PwDs participated in a one-week ($7$ days) study that involved daily robot-led sessions. Participants engaged positively with the system, completing nearly half of the scheduled sessions, an adherence rate higher than typically observed in caregiver-led CST. Our findings also highlight the crucial role of family members, who often supported session initiation and occasionally joined the activities, enriching the interactions. This work demonstrates the feasibility and potential of socially assistive robots to deliver in-home cognitive therapy, offering a scalable approach to extend access to dementia care.

Comments: Accepted for publication at the IEEE RO-MAN Conference 2026

Subjects:

Robotics (cs.RO)

Cite as: arXiv:2607.05709 [cs.RO]

(or arXiv:2607.05709v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2607.05709

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Emmanuel Akinrintoyo [view email] [v1] Tue, 7 Jul 2026 00:19:22 UTC (2,480 KB)

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