Assistive robotics and particularly robot coaches may be very helpful for rehabilitation healthcare. In this context, we propose a method based on Gaussian Process Latent Variable Model (GP-LVM) to transfer knowledge between a physiotherapist, a robot coach and a patient. Our model is able to map visual human body features to robot data in order to facilitate the robot learning and imitation. In addition, we propose to extend the model to adapt the robots’ understanding to patients’ physical limitations during assessment of rehabilitation exercises. Experimental evaluation demonstrates promising results for both robot imitation and model adaptation according to patients’ limitations.
Only few approaches addressed the challenge of physical rehabilitation through coaching robot systems. While several studies showed the potential of virtual agents @cite_13 @cite_7 and physical robots @cite_8 to enhance engagement and learning in health, physical activity or social contexts, Fasola @cite_16 showed better assessment by the elderly subjects of the physical robot coach compared to virtual systems. Robots for coaching physical exercises have been recently presented @cite_14 @cite_10 @cite_5 . These approaches employed robots with few degrees of freedom that facilitates the imitation process. However, such robots do not allow realistic movements. Moreover, Takenori @cite_5 did not provide any feedback or active guidance to the patient.
@cite_14 @cite_7 @cite_8 @cite_10 @cite_5 @cite_16 @cite_13
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The application of a robot to rehabilitation has become a matter of great concern. This paper deals with functional recovery therapy, one important aspect of physical rehabilitation. Single-joint therapy machines have already been achieved. However, for more efficient therapy, multjoint robots are necessary to achieve more realistic motion patterns. This kind of robot must have a high level of safety for humans. A pneumatic actuator may be available for such a robot, because of the compliance of compressed air. A pneumatic rubber artificial muscle manipulator has been applied to construct a therapy robot with two degrees of freedom (DOF). Also, an impedance control strategy is employed to realize various motion modes for the physical therapy modes. Further, for efficient rehabilitation, it is desirable to comprehend the physical condition of the patient. Thus, the mechanical impedance of the human arm is used as an objective evaluation of recovery, and an estimation method is proposed. Experiments show the suitability of the proposed rehabilitation robot system. We present a socially assistive robot (SAR) system designed to engage elderly users in physical exercise. We discuss the system approach, design methodology, and implementation details, which incorporate insights from psychology research on intrinsic motivation, and we present five clear design principles for SAR-based therapeutic interventions. We then describe the system evaluation, consisting of a multi-session user study with older adults (n = 33), to evaluate the effectiveness of our SAR exercise system and to investigate the role of embodiment by comparing user evaluations of similar physically and virtually embodied coaches. The results validate the system approach and effectiveness at motivating physical exercise in older adults according to a variety of user performance and outcomes measures. The results also show a clear preference by older adults for the physically embodied robot coach over the virtual coach in terms of enjoyableness, helpfulness, and social attraction, among other factors. The impact of the world-wide ageing population has commenced with respect to society in developed countries. Several researchers focused on exploring new methods to improve the quality of life of elderly individuals by allowing them to remain independent and healthy to the maximum possible extent. For example, new walking aids are designed to allow elderly individuals to remain mobile in a safe manner because the importance of walking is well-known. The aim of the present study involves designing a humanoid robot guide as a walking trainer for elderly individuals. It is hypothesized that the same service robot provides an assistive and social contribution with respect to interaction between elderly users by motivating them to walk more and simultaneously provides assistance, such as physical assistance and gait monitoring, while walking. This study includes a detailed statement of the research problem as well as a literature review of existing studies related to walking companion robots. A user-centred design approach is adopted to report the results of the current first feasibility study by using a commercially available humanoid robot known as Pepper developed by Softbank-Aldebaran. A quantitative questionnaire was used to investigate all elements that assess intrinsic motivation in users while performing a given activity. Conversely, basic gait data were acquired through a video analysis to test the capability of the robot to modify the gait of human users. The results in terms of the feedback received from elderly subjects and the literature review improve the design of the walking trainer for elderly individuals. In this paper we present the results of a qualitative study with therapists to inform social robotics and human robot interaction (HRI) for engagement in rehabilitative therapies. Our results add to growing evidence that socially assistive robots (SARs) could play a role in addressing patients' low engagement with self-directed exercise programmes. Specifically, we propose how SARs might augment or offer more pro-active assistance over existing technologies such as smartphone applications, computer software and fitness trackers also designed to tackle this issue. In addition, we present a series of design implications for such SARs based on therapists' expert knowledge and best practices extracted from our results. This includes an initial set of SAR requirements and key considerations concerning personalised and adaptive interaction strategies.