Intelligent assistive robots can enhance the quality of life of people with dementia and their caregivers. They can increase the independence of older adults, reduce tensions between a person with dementia and their caregiver, and increase social engagement. This article provides a review of assistive robots designed for and evaluated by persons with dementia. Assistive robots that only increased mobility or brain-computer interfaces were excluded. Google Scholar, IEEE Digital Library, PubMed, and ACM Digital Library were searched. A final set of 53 articles covering research in 16 different countries are reviewed. Assistive robots are categorized into five different applications and evaluated for their effectiveness, as well as the robots’ social and emotional capabilities. Our findings show that robots used in the context of therapy or for increasing engagement received the most attention in the literature, whereas the robots that assist by providing health guidance or help with an activity of daily living received relatively limited attention. PARO was the most commonly used robot in dementia care studies. The effectiveness of each assistive robot and the outcome of the studies are discussed, and particularly, the social/emotional capabilities of each assistive robot are summarized. Gaps in the research literature are identified and we provide directions for future work.
Computational models of distributional semantics represent word meanings in terms of words' relationships with all other words in a corpus. Although distributional models are sensitive to topic (e.g., tiger and stripes) and synonymy (e.g., soar and fly), the models have limited sensitivity to part-of-speech (e.g., book and shirt are nouns). How lexical-syntactic knowledge is encoded and how it meshes with semantic representations are open questions. Word co-occurrence relationships define a connected graph such that any two words have some degree of separation on the graph. Models of distributional semantics are typically sensitive to only one or two degrees of separation. By recursively adding higher levels of representations to a computational, holographic model of semantic memory, we build a model sensitive to arbitrary degrees of separation. We find that word associations at four degrees of separation increase the similarity between words that share part-of-speech or syntactic type and improve the ability of the model to construct grammatical sentences. Our model provides evidence that human memory must be sensitive to indirect associations to accommodate lexical syntactic relationships as well as evidence that semantics and syntax exist on a continuum that emerges from a unitary cognitive system.
Introduction In this paper, we study the support needed by professional caregivers of those with dementia, and present a first step toward development of VIPCare, a novel application with the goal of assisting new caregivers at care-centres in interacting with residents with dementia. Methods A mixed-methods study including two questionnaires, two focus groups, and seven co-design sessions with 17 professional caregivers was conducted to (a) understand caregivers’ challenges/approaches used to reduce negative interactions with persons with dementia, (b) identify the existing gaps in supporting information for improving such interactions, and (c) co-design the user interface of an application that aims to help improve interactions between a new professional caregiver and persons with dementia. A pre-questionnaire assessed knowledge of smartphones and attitude toward technology. A post-questionnaire provided an initial evaluation of the designed user interface. Results Focus groups emphasized the importance of role-playing learned through trial and error. The layout/content of the application was then designed in four iterative paper-prototyping sessions with professional caregivers. An iOS/Android-based application was developed accordingly and was modified/improved in three iterative sessions. The initial results supported efficiency of VIPCare and suggested a low task load index. Conclusions We presented a first step toward understanding caregiver needs and developing an application that can help reduce negative interactions between professional caregivers and those with dementia.
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