The automatic assessment of the level of independence of a person, based on the recognition of a set of Activities of Daily Living, is among the most challenging research fields in Ambient Intelligence. The article proposes a framework for the recognition of motion primitives, relying on Gaussian Mixture Modeling and Gaussian Mixture Regression for the creation of activity models. A recognition procedure based on Dynamic Time Warping and Mahalanobis distance is found to: (i) ensure good classification results; (ii) exploit the properties of GMM and GMR modeling to allow for an easy run-time recognition; (iii) enhance the consistency of the recognition via the use of a classifier allowing unknown as an answer

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This trial represents the final stage of the CARESSES project which aimed to develop and evaluate a culturally competent artificial intelligent system embedded into social robots to support older adult wellbeing. A parallel group, single-blind randomised controlled trial was conducted across older adult care homes in England and Japan. Participants randomly allocated to the Experimental Group or Control Group 1 received a Pepper robot for up 18 h across 2 weeks. Two versions of the CARESSES artificial intelligence were tested: a fully culturally competent system (Experimental Group) and a more limited version (Control Group 1). Control Group 2 (Care As Usual) participants did not receive a robot. Quantitative outcomes of interest reported in the current paper were health-related quality of life (SF-36), loneliness (ULS-8), and perceptions of robotic cultural competence (CCATool-Robotics). Thirty-three residents completed all procedures. The difference in SF-36 Emotional Wellbeing scores between Experimental Group and Care As Usual participants over time was significant (F[1] = 6.614, sig = .019, ηp2 = .258), as was the comparison between Any Robot used and Care As Usual (F[1] = 5.128, sig = .031, ηp2 = .146). There were no significant changes in SF-36 physical health subscales. ULS-8 loneliness scores slightly improved among Experimental and Control Group 1 participants compared to Care As Usual participants, but this was not significant. This study brings new evidence which cautiously supports the value of culturally competent socially assistive robots in improving the psychological wellbeing of older adults residing in care settings.

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Cultural competence is a well known requirement for an effective healthcare, widely investigated in the nursing literature. We claim that personal assistive robots should likewise be culturally competent, aware of general cultural characteristics and of the different forms they take in different individuals, and sensitive to cultural differences while perceiving, reasoning, and acting. Drawing inspiration from existing guidelines for culturally competent healthcare and the state-of-the-art in culturally competent robotics, we identify the key robot capabilities which enable culturally competent behaviours and discuss methodologies for their development and evaluation. 1 B. Bruno and A. Sgorbissa are with the

Background This article describes the design of an intervention study that focuses on whether and to what degree culturally competent social robots can improve health and well-being related outcomes among older adults residing long-term care homes. The trial forms the final stage of the international, multidisciplinary CARESSES project aimed at designing, developing and evaluating culturally competent robots that can assist older people according to the culture of the individual they are supporting. The importance of cultural competence has been demonstrated in previous nursing literature to be key towards improving health outcomes among patients. Method This study employed a mixed-method, single-blind, parallel-group controlled before-and-after experimental trial design that took place in England and Japan. It aimed to recruit 45 residents of long-term care homes aged ≥65 years, possess sufficient cognitive and physical health and who self-identify with the English, Indian or Japanese culture (n = 15 each). Participants were allocated to either the experimental group, control group 1 or control group 2 (all n = 15). Those allocated to the experimental group or control group 1 received a Pepper robot programmed with the CARESSES culturally competent artificial intelligence (experimental group) or a limited version of this software (control group 1) for 18 h across 2 weeks. Participants in control group 2 did not receive a robot and continued to receive care as usual. Participants could also nominate their informal carer(s) to participate. Quantitative data collection occurred at baseline, after 1 week of use, and after 2 weeks of use with the latter time-point also including qualitative semi-structured interviews that explored their experience and perceptions further. Quantitative outcomes of interest included perceptions of robotic cultural competence, health-related quality of life, loneliness, user satisfaction, attitudes towards robots and caregiver burden. Discussion This trial adds to the current preliminary and limited pool of evidence regarding the benefits of socially assistive robots for older adults which to date indicates considerable potential for improving outcomes. It is the first to assess whether and to what extent cultural competence carries importance in generating improvements to well-being. Trial registration Name of the registry: ClinicalTrials.gov Trial registration number: NCT03756194. Date of registration: 28 November 2018. URL of trial registry record.