Introduction Socially assistive robots are devices designed to aid users through social interaction and companionship. Social robotics promise to support cognitive health and aging in place for older adults with and without dementia, as well as their care partners. However, while new and more advanced social robots are entering the commercial market, there are still major barriers to their adoption, including a lack of emotional alignment between users and their robots. Affect Control Theory (ACT) is a framework that allows for the computational modeling of emotional alignment between two partners. Methods We conducted a Canadian online survey capturing attitudes, emotions, and perspectives surrounding pet-like robots among older adults ( n = 171), care partners ( n = 28), and persons living with dementia ( n = 7). Results We demonstrate the potential of ACT to model the emotional relationship between older adult users and three exemplar robots. We also capture a rich description of participants’ robot attitudes through the lens of the Technology Acceptance Model, as well as the most important ethical concerns around social robot use. Conclusions Findings from this work will support the development of emotionally aligned, user-centered robots for older adults, care partners, and people living with dementia.
Abstract. This paper describes a novel emotionally intelligent cognitive assistant to engage and help older adults with Alzheimer's disease (AD) to complete activities of daily living (ADL) more independently. Our new system combines two research streams. First, the development of cognitive assistants with artificially intelligent controllers using partially observable Markov decision processes (POMDPs). Second, a model of the dynamics of emotion and identity called Affect Control Theory that arises from the sociological literature on culturally shared sentiments. We present background material on both of these research streams, and then demonstrate a prototype assistive technology that combines the two. We discuss the affective reasoning, the probabilistic and decision-theoretic reasoning, the computer-vision based activity monitoring, the embodied prompting, and we show results in proof-of-concept tests.
In many situations, it is desirable to optimize a sequence of decisions by maximizing a primary objective while respecting some constraints with respect to secondary objectives. Such problems can be naturally modeled as constrained partially observable Markov decision processes (CPOMDPs) when the environment is partially observable. In this work, we describe a technique based on approximate linear programming to optimize policies in CPOMDPs. The optimization is performed offline and produces a finite state controller with desirable performance guarantees. The approach outperforms a constrained version of point-based value iteration on a suite of benchmark problems.
In this paper, we present the first results of the ACT@HOME research project which aims to develop an an artificially intelligent virtual assistant (VA) to engage and help older adults with Alzheimer's disease (AD) to complete activities of daily living (ADL) more independently. In order to define the most appropriate prompting style for each user profile, we performed 12 semi structured qualitative interviews with dyads of elderly care home residents and their family caregiver. During these interviews, we presented the virtual assistant and the different 'static' prompts to support people in the activity of hand washing. We gathered as much feedback and suggestions as possible coming directly from the end users about how to improve the provided prompts and thus, increase acceptability. The results are presented around three extracted themes: a) comments on current design of the virtual assistant, b) perceived usefulness, user adoption and c) suggestions for improvements. These should guide in the future developers of assistive technology to support elderly care home residents.
This paper presents a study conducted to understand how facial expressions in audiovisual prompts given by virtual humans are understood by elderly people on an emotional level with an aim to design emotionally aligned prompts for persons with cognitive disabilities who often need assistance from a caregiver to complete daily living activities such as washing hands, making food, or getting dressed. Artificially intelligent systems have been developed that can assist in such situations. Our long term aim is to enhance such systems by delivering automated prompts that are emotionally aligned with individuals in order to have better human-system interaction in helping with the tasks. This paper presents a set of prompts of male and female virtual humans with a focus on their facial expressions. A user study with elderly persons was conducted with respect to three basic and important dimensions of emotional experience: Evaluation, Potency, and Activity (EPA). Results show that there is significant consensus on E and P dimensions, and some consensus on the A dimension.
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