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Body weight-transfer plays an important role in many exercises. The correlation of the body posture, movement, and weight-transfer will mutually affect the trainee to do well in performances such as Tai-Chi exercise. According to the traditional way of learning Tai-Chi, we proposed Stillness Moves, a physical training system for Tai-Chi, which captures and records users' skeleton movement and weight-transfer information for offering real-time and summary visual feedback. Based on above, we provide a gradual learning program in physical training, which combines body movement and weight-transfer learning. We evaluated our system and compared the performance without and with weight-transfer guidance in the user study. The result demonstrated that weight-transfer guidance is beneficial for trainee learning the Tai-Chi moves. For difficult moves, the trainee should learn the weight-transfer first, then, learning the body movement.

Automatic screen rotation improves viewing experience and usability of mobile devices, but current gravity-based approaches do not support postures such as lying on one side, and manual rotation switches require explicit user input. iRotateGrasp automatically rotates screens of mobile devices to match users' viewing orientations based on how users are grasping the devices. Our insight is that users' grasps are consistent for each orientation, but significantly differ between different orientations. Our prototype used a total of 44 capacitive sensors along the four sides and the back of an iPod Touch, and uses support vector machine (SVM) to recognize grasps at 25Hz. We collected 6-users' usage under 108 different combinations of posture, orienta-tion, touchscreen operation, and left/right/both hands. Our offline analysis showed that our grasp-based approach is promising, with 80.9% accuracy when training and testing on different users, and up to 96.7% if users are willing to train the system. Our user study (N=16) showed that iRo-tateGrasp had an accuracy of 78.8% and was 31.3% more accurate than gravity-based rotation.

This paper presents i-m-Space, an interactive multimedia rehabilitation space that helps the post-surgery recovery of breast cancer patients. Our goal is to improve patients' physical therapy and psychological relaxation experience through careful applications of multimedia technology. i-m-Space consists of three types of breathing-based relaxation and three types for interactive exercise-based rehabilitation. Our inter-disciplinary team includes medical professionals, multimedia engineers, designers, and artists. We have implemented i-m-Space in an experimental space in collaboration a local breast cancer foundation. To evaluation i-m-Space, we have recruited several patients who recently recovered from breast cancer to use i-m-Space and to share their first-hand experiences. Our contributions includes the following: 1) injecting a sense of fun and playfulness into traditional therapy to attract patients; 2) providing therapists with sufficient flexibility so they can personalize therapy sessions for each patient; 3) maintaining safety of patients.

In this paper, we explore the challenges in applying and investigate methodologies to improve direct-touch interaction on intangible displays. Direct-touch interaction simplifies object manipulation, because it combines the input and display into a single integrated interface. While traditional tangible display-based direct-touch technology is commonplace, similar direct-touch interaction within an intangible display paradigm presents many challenges. Given the lack of tactile feedback, direct-touch interaction on an intangible display may show poor performance even on the simplest of target acquisition tasks. In order to study this problem, we have created a prototype of an intangible display. In the initial study, we collected user discrepancy data corresponding to the interpretation of 3D location of targets shown on our intangible display. The result showed that participants performed poorly in determining the z-coordinate of the targets and were imprecise in their execution of screen touches within the system. Thirty percent of positioning operations showed errors larger than 30mm from the actual surface. This finding triggered our interest to design a second study, in which we quantified task time in the presence of visual and audio feedback. The pseudo-shadow visual feedback was shown to be helpful both in improving user performance and satisfaction.