Objectives: To evaluate the clinical efficacy of smartphone-assisted self-rehabilitation in patients with frozen shoulder. Design: A single-center, randomized controlled trial. Setting: Orthopedic department of a university hospital. Subjects: A total of 84 patients with frozen shoulder were recruited. Intervention: Patients were randomly divided into two groups: a smartphone-assisted exercise group (n = 42) and a conventional self-exercise group (n = 42). The study was performed over three months, during which each group performed home-based rehabilitation. Main measures: Visual analogue scale for pain and passive shoulder range of motion were assessed at baseline and after 4, 8, and 12 weeks of treatment. Technology Acceptance Model–2 and Usefulness, Satisfaction, and Ease of Use scores were evaluated in the smartphone group. Results: Initial visual analogue scale for pain of the smartphone group was 6.0 ± 2.2 and ended up with 1.8 ± 2.5 after 12 weeks, whereas the self-exercise group showed 5.8 ± 2.3 for the baseline visual analogue scale for pain and 2.2 ± 1.7 at the end. Significant time-dependent improvements in all measured values were observed in both groups (all Ps < 0.001), but no significant intergroup difference was observed after 4, 8, or 12 weeks of treatment. In the smartphone group, Technology Acceptance Model–2 and Usefulness, Satisfaction, and Ease of Use scores showed high patient satisfaction with smartphone-assisted exercise. Conclusion: There was no difference between home-based exercise using a smartphone application and a conventional self-exercise program for the treatment of frozen shoulder in terms of visual analogue scale for pain and range of motions.

Background Cognitive training using virtual reality (VR) may result in motivational and playful training for patients with mild cognitive impairment and mild dementia. Fully immersive VR sets patients free from external interference and thus encourages patients with cognitive impairment to maintain selective attention. The enriched environment, which refers to a rich and stimulating environment, has a positive effect on cognitive function and mood. Objective The aim of this study was to investigate the feasibility and usability of cognitive training using fully immersive VR programs in enriched environments with physiatrists, occupational therapists (OTs), and patients with mild cognitive impairment and mild dementia. Methods The VR interface system consisted of a commercialized head-mounted display and a custom-made hand motion tracking module. We developed the virtual harvest and cook programs in enriched environments representing rural scenery. Physiatrists, OTs, and patients with mild cognitive impairment and mild dementia received 30 minutes of VR training to evaluate the feasibility and usability of the test for cognitive training. At the end of the test, the usability and feasibility were assessed by a self-report questionnaire based on a 7-point Likert-type scale. Response time and finger tapping were measured in patients before and after the test. Results Participants included 10 physiatrists, 6 OTs, and 11 patients with mild cognitive impairment and mild dementia. The mean scores for overall satisfaction with the program were 5.75 (SD 1.00) for rehabilitation specialists and 5.64 (SD 1.43) for patients. The response time of the dominant hand in patients decreased after the single session of cognitive training using VR, but this was not statistically significant (P=.25). There was no significant change in finger tapping in either the right or left hand (P=.48 and P=.42, respectively). None of the participants reported headaches, dizziness, or any other motion sickness after the test. Conclusions A fully immersive VR cognitive training program may be feasible and usable in patients with mild cognitive impairment and mild dementia based on the positive satisfaction and willingness to use the program reported by physiatrists, OTs, and patients. Although not statistically significant, decreased response time without a change in finger tapping rate may reflect a temporary increase in attention after the test. Additional clinical trials are needed to investigate the effect on cognitive function, mood, and physical outcomes.

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We propose a light and fast hand gesture recognition method using geometric feature for a smartphone based robot and apply it to early childhood mathematics education. The feature of hand gesture is defined by the number of extrema in the plot for the distances between the center point of hand and the outer points of hand from active contour model or snakes. The region of interest (ROI) is continuously updated by Continuously Adaptive Mean Shift Algorithm (CamShift) algorithm, and the snake model is used to make the outer points sequential efficiently. A mathematics learning application for an Android OS smartphone based robot is developed using the hand gesture recognition algorithm. The experiment with Korean children (5-6 years of age) is conducted to evaluate if hand gesture based HRI could promote their mathematics learning. The result suggests that the idea of hand gesture based HRI for early childhood education is feasible and that children can learn mathematics by hand gesture based interaction with a robot. I. INTRODUCTIONRobot technologies have been increasingly applied in education and therapy. The rapid development of HRI technology has provided more possible robot applications and has helped those applications more realistic. For example, vision based HRI technology provided more sophisticated information about human behavior that is necessary for implementation of more feasible applications [1-2], and there have been many different approaches for non-verbal communication interaction for human and robot [3].Recently, smartphones have been ubiquitous parts in our daily life, and so our lives are more connected to things that could be intelligently interactive with human or robots. Moreover, smartphones themselves have a variety of basic sensors such as cameras, inertia sensors and microphones that could be useful for HRI. Especially, various HRI approaches using 2D images were introduced for mobile phone environment [4-10].While there are many different kinds of applications for smartphone based HRI, early childhood education could be one of them. Many studies showed that cross-media and

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