Minimizing task-induced stress in cognitively stimulating activities using an intelligent socially assistive robot
Bibliographic record
Abstract
Dementia is currently a growing epidemic, bringing forth severe health, social, and economic strains. As an alternative to pharmacological measures, current research supports the effectiveness of using cognitive training interventions to slow the decline of or even improve brain functioning in persons with dementia. However, implementing and sustaining these interventions on a long-term basis can be challenging as they demand considerable resources and people. Our research focuses on investigating the potential use of robotic assistants to allow for these interventions to become more accessible to users and caregivers. Namely, the aim of our work is to develop socially assistive robots that can provide cognitive and social stimulation for persons with dementia. In this paper, we study the social interaction attributes of the human-like robot, Brian 2.0, during a one-on-one person-centered cognitively stimulating activity to determine if the robot is capable of minimizing task-induced stress by providing assistance, encouragement, and celebration, while adapting its behavior to a user state during the course of the activity. Our preliminary study shows that the social intelligence of Brian 2.0 is effective in engaging individuals in a cognitively stimulating game while minimizing stress during gameplay.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".