Background: Cognitive deficits arise with age and can increase the risk for subjective cognitive decline (SCD) and mild cognitive impairment (MCI), which may result in dementia, leading to health problems, care dependency and institutionalization. Computer-based cognitive interventions (CCIs) have the potential to act as important counteraction functions in preserving or improving cognition concomitant to available pharmacological treatment. The aim was to assess the effectiveness of CCIs performed individually with a personal or tablet computer, game console, virtual, augmented, or mixed reality application on cognition in community-dwelling people with SCD, MCI and dementia. Methods: A systematic review with meta-analyses of randomized controlled trials (RCTs) was performed. The systematic literature search was conducted in MEDLINE, CINAHL, Embase, Cochrane CENTRAL, IEEE Xplore Digital Library, Web of Science, Scopus and PsycINFO. In addition, a search for gray literature and backward citation searching were carried out. To judge on the evidence, two reviewers independently used the Cochrane Risk of Bias Tool. The standardized mean difference (SDM) for pooling comparable studies using the random-effects model was applied. Results: Twenty-four RCTs were identified, of which 1 RCT examined CCIs in individuals with SCD, 18 RCTs with MCI, and 6 RCTs with dementia. Most interventions were conducted with personal computers. Meta-analyses with 12 RCTs showed significant effects of computer-based cognitive interventions for people with MCI in the domains memory, working memory, attention/concentration/processing speed and executive functioning, but no significant improvements in global cognition and language. Regarding dementia a meta-analysis pooled with 4 RCTs demonstrated a tendency towards, but no significant increase of memory functions (SMD 0.33, CI 95% [-0.10, 0.77]). One RCT regarding SCD reported significant improvements in memory functions for participants conducting a cognitive training on a personal computer. Conclusions: The results demonstrated that CCIs have beneficial effects on domain-specific cognition in people with MCI but no significant effects on people with dementia. In terms of SCD, one study showed significant improvements in memory functions. It seems that the beneficial effect for cognitive preservation or improvement due to CCIs occurs at the earliest intervention state. However, more research on SCD is needed. Trial registration: PROSPERO International Prospective Register of Systematic Reviews CDR42020184069.

Human attention processes play a major role in the optimization of human-robot interaction (HRI) systems. This work describes a novel methodology to measure and predict situation awareness and from this overall performance from gaze features in real-time. The awareness about scene objects of interest is described by 3D gaze analysis using data from wearable eye tracking glasses and a precise optical tracking system. A probabilistic framework of uncertainty considers coping with measurement errors in eye and position estimation. Comprehensive experiments on HRI were conducted with typical tasks including handover in a lab based prototypical manufacturing environment. The methodology is proven to predict standard measures of situation awareness (SAGAT, SART) as well as performance in the HRI task in real-time and will open new opportunities for human factors based performance optimization in HRI applications.

Background: New technologies, like socially assistive robots (SARs), may have the potential to support caregivers at home. Still, the evidence for people with dementia in home care is unclear because a lot of studies are performed in a laboratory or institutional setting, and mainly use robots in prototype stages.Objective: This study aims to explore the effects of the refined, commercially-available, humanoid SAR Pepper combined with a tablet PC–based dementia training program (Coach Pepper) versus an exclusively tablet PC–based dementia training program on psychosocial and physical outcomes of people with dementia living at home, including caregivers and dementia trainers. We hypothesize that Coach Pepper has a more positive effect on the primary outcome motivation (stable or decreased apathy) of people with dementia.Methods: A mixed methods study will be performed, including a randomized controlled, parallel, 2-arm study with a complementary qualitative part. This sample includes 40 PWD living at home and 40 relatives, each complemented with five professional caregivers and dementia trainers. The intervention group will receive Coach Pepper (a SAR connected with a tablet PC–based dementia training program), and the control group will receive exclusively tablet PC–based training without the SAR. The duration of the intervention will be three weeks per household. Data will be collected at baseline and during and after the intervention by standardized questionnaires, sensor data of the robot, and tablet PC, as well as semistructured interviews, focus groups, and observation.Results: To date, no results are available for this study protocol. The study intervention started in May 2019 and will end in Spring 2020.Conclusions: The intervention of this study can be seen as a nonpharmacological intervention, including cognitive and physical training by a robot. This study will help to further refine SAR for the specific needs of people with dementia living at home.International Registered Report Identifier (IRRID): DERR1-10.2196/14927

This work is about the relevance of Gibson's concept of affordances for visual perception in interactive and autonomous robotic systems. In extension to existing functional views on visual feature representations, we identify the importance of learning in perceptual cueing for the anticipation of opportunities for interaction of robotic agents. We investigate how the originally defined representational concept for the perception of affordances - in terms of using either optical flow or heuristically determined 3D features of perceptual entities should be generalized to using arbitrary visual feature representations. In this context we demonstrate the learning of causal relationships between visual cues and predictable interactions, and emphasize on a novel framework for cueing and hypothesis verification of affordances that could play an important role in future robot control architectures. We argue that affordance based perception should enable systems to react to environment stimuli both more efficient and autonomous, and provide a potential to plan on the basis of responses to more complex perceptual configurations. We verify the concept with a concrete implementation applying state-of-the-art visual descriptors and regions of interest within a simulated robot scenario and prove that these features were successfully selected for predicting opportunities of robot interaction

To examine the expectations of informal caregivers, nurses, and dementia trainers regarding the support of (physical and psychosocial) human needs by humanoid social assistive robots (SARs) in deme...