# \"Gynmy\": Designing and Testing a Robot for Physical and Cognitive Training of Older Adults
## 1 Introduction
It has been shown that social robots can improve the quality of older adults' lives and compensate for the shortage of caregivers and personal trainers [28; 29]. Social assistive robots are advancing in many daily living applications for older adults [30; 31; 32; 33; 34], such as service robots which detect risks (such as in [35]), emergencies [36] and daily behaviors [37], offer medicine reminders [35], follow the user [38], assist with cooking [35; 39], setting the table [40], cleaning [41], dressing [42; 43] and feeding [44; 45] and companionship [46; 47]. In contrast to a human trainer, a robotic trainer is more flexible in terms of location and availability over time [26]. Studies show that people in general, and older adults in particular, prefer a physical robot over a virtual agent as an exercise trainer; they rate their interactions with physical robots as more engaging and more enjoyable and consider the trainers themselves to be more effective than virtual agents [28; 48]. Similarly, for cognitive training, research shows that robots can be used to improve cognition [27; 49], although there are cheaper alternatives such as computer and mobile phone applications. However, social robots add value due to their multi-functionality (for example, combining physical and cognitive training [50]) and their novelty as a means of interaction. This feature itself can stimulate brain activity [27]. In designing social robotic systems, the incorporation of a capacity to motivate users improves the quality and effectiveness of human-robot interaction [51]. In addition, research suggests that theory-based interventions can increase physical activity by 10-15% compared with structured exercise training [52]. In keeping with these observations, a meta-analysis of interventions to promote physical activity [53] revealed that theory-based interventions have a larger effect on physical performance than interventions that are not based on a theory, while the effect of motivational interventions is on the willingness to take up a physical activity. Different motivational theories such as \"flow theory\" [54] and \"self-determination theory\" (SDT) [55] have been applied to the design of technological interventions to encourage physical activity. Flow theory can be applied to a situation in which people are fully invested in an activity and likely to ignore other possible calls on their attention. This is likely to occur under three conditions: (1) where the system has a clear set of goals, (2) where the user can obtain clear and instant feedback and (3) where the demands of the intervention match the skills of the user. Approaches based on flow theory link enjoyment to motivation, and they have been applied in exergames [23]. These observations recommend that integrating fun and exercise can enhance enjoyment and lead people to be more motivated to engage in physical activity. SDT-inspired interventions [22] are focused on three psychological needs that are presumed to provide the basis of human motivation: relatedness, competence and autonomy. When the activity supports the user's autonomy and self-determination, it increases intrinsic motivation, which positively affects adherence to an exercise regime and to long-term behavior change. Two studies presented their own design methodology for a robotic trainer that will increase motivation for physical activity based on SDT and flow theory principles [28; 56]. Those principles include the provision of positive feedback, the avoidance of negative feedback, matching the nature of the interaction to the characteristics of the user and offering a range of challenging activities and exercise games with a variety of difficulty levels. Furthermore, this approach focuses on the fluidity of the interaction in order to avoid boredom and frustration among users. Both SDT and flow theory emphasize the importance of clear and instant feedback for the maintenance of motivation.