In this article, we describe the development of a human-robot interaction concept for service robots to assist elderly people in the home with physical tasks. Our approach is based on the insight that robots are not yet able to handle all tasks autonomously with sufficient reliability in the complex and heterogeneous environments of private homes. We therefore employ remote human operators to assist on tasks a robot cannot handle completely autonomously. Our development methodology was user-centric and iterative, with six user studies carried out at various stages involving a total of 241 participants. The concept is under implementation on the Care-O-bot 3 robotic platform. The main contributions of this article are (1) the results of a survey in form of a ranking of the demands of elderly people and informal caregivers for a range of 25 robot services, (2) the results of an ethnography investigating the suitability of emergency teleassistance and telemedical centers for incorporating robotic teleassistance, and (3) a user-validated human-robot interaction concept with three user roles and corresponding three user interfaces designed as a solution to the problem of engineering reliable service robots for home environments

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The implications for the inclusion of robots in the daily lives of frail older adults, especially in relation to these population needs, have not been extensively studied. The "Multi-Role Shadow Robotic System for Independent Living" (SRS) project has developed a remotely-controlled, semi-autonomous robotic system to be used in domestic environments. The objective of this paper is to document the iterative procedure used to identify, select and prioritize user requirements. Seventy-four requirements were identified by means of focus groups, individual interviews and scenario-based interviews. The list of user requirements, ordered according to impact, number and transnational criteria, revealed a high number of requirements related to basic and instrumental activities of daily living, cognitive and social support and monitorization, and also involving privacy, safety and adaptation issues. Analysing and understanding older users' perceptions and needs when interacting with technological devices adds value to assistive technology and ensures that the systems address currently unmet needs.

Abstract:In this study, we present the design and implementation of Arabic text classification in regard to university students' opinions through different algorithms such as Support Vector Machine (SVM) and Naive Bayes (NB). The aim of the study is to develop a framework to analyse Twitter "tweets" as having negative, positive or neutral sentiments in education or, in other words, to illustrate the relationship between the sentiments conveyed in Arabic tweets and the students' learning experiences at universities. Two experiments were carried out, one using negative and positive classes only and the other one with a neutral class. The results show that in Arabic, a sentiments SVM with an n-gram feature achieved higher accuracy than NB both with using negative and positive classes only and with the neutral class.