Engaging people with dementia (PWD) in meaningful activities is the key to promote their quality of life. Design towards a higher level of user engagement has been extensively studied within the human-computer interaction community, however, few extend to PWD. It is generally considered that increased richness of experiences can lead to enhanced engagement. Therefore, this paper explores the effects of rich interaction in terms of the role of system interactivity and multimodal stimuli by engaging participants in context-enhanced human-robot interaction activities. The interaction with a social robot was considered context-enhanced due to the additional responsive sensory feedback from an augmented reality display. A field study was conducted in a Dutch nursing home with 16 residents. The study followed a two by two mixed factorial design with one within-subject variable - multimodal stimuli - and one between-subject variable - system interactivity. A mixed method of video coding analysis and observational rating scales was adopted to assess user engagement comprehensively. Results disclose that when additional auditory modality was included besides the visual-tactile stimuli, participants had significantly higher scores on attitude, more positive behavioral engagement during activity, and a higher percentage of communications displayed. The multimodal stimuli also promoted social interaction between participants and the facilitator. The findings provide sufficient evidence regarding the significant role of multimodal stimuli in promoting PWD’s engagement, which could be potentially used as a motivation strategy in future research to improve emotional aspects of activity-related engagement and social interaction with the human partner.

The well-being of people with dementia (PWD) living in long-term care facilities is hindered due to disengagement and social isolation. Animal-like social robots are increasingly used in dementia care as they can provide companionship and engage PWD in meaningful activities. While most previous human–robot interaction (HRI) research studied engagement independent from the context, recent findings indicate that the context of HRI sessions has an impact on user engagement. This study aims to explore the effects of contextual interactions between PWD and a social robot embedded in the augmented responsive environment. Three experimental conditions were compared: reactive context-enhanced robot interaction; dynamic context-enhanced interaction with a static robot; a control condition with only the dynamic context presented. Effectiveness evaluations were performed with 16 participants using four observational rating scales on observed engagement, affective states, and apathy related behaviors. Findings suggested that the higher level of interactivity of a social robot and the interactive contextualized feedback helped capture and maintain users’ attention during engagement; however, it did not significantly improve their positive affective states. Additionally, the presence of either a static or a proactive robot reduced apathy-related behaviors by facilitating purposeful activities, thus, motivating behavioral engagement.

The appearance characteristics of ceramic color are an important factor in determining the user’s aesthetic perception of the product. Given the problem that ceramic color varies and the user’s visual sensory evaluation of color is highly subjective and uncertain, a method of quantifying ceramic color characteristics based on the Back Propagation (BP) neural network algorithm is proposed. The semantic difference method and statistical method were used to obtain quantified data from ceramic color perceptual semantic features and were combined with a neural network to study the association between ceramic color features and user perceptual-cognitive evaluation. A BP neural network was used to build a ceramic color perceptual semantic mapping model, using color semantic quantified values as the input layer, color L, A, and B component values as the output layer, and model training to predict the sample. The output color L, A, and B components are used as the input layer and the color scheme was designed. The above method can effectively solve the mapping problem between the appearance characteristics of ceramic color and perceptual semantics and provide a decision basis for ceramic product color design. The case application of color design of daily-use ceramic products was conducted to verify the effectiveness and feasibility of the quantitative research method of ceramic color imagery.