This paper ponders the effects of introducing an assistive force visual display on a subject's force perception. Correct and incorrect displays were tested and were found to significantly affect the subject's force perception as compared to no visual feedback case. The elbow joint was considered for this study and assisted with four wearable artificial muscles called pneumatic gel muscles (PGMs). It was observed that subjects tend to underestimate the assistive force. The introduction of a visual display could significantly reduce this force underestimation. Moreover, the level of force underestimation was higher in case of higher force values. In other words, the higher the actual force provided, the higher the level of force underestimation in all three conditions: correct, incorrect and no visual feedback. It was also observed that the perceived error (perceived force - actual force) was directly in proportion with the visual error (visual force - actual force).

The increasing use of virtual reality (VR) and augmented reality (AR) systems has opened the possibility of providing immersive experiences to the general population around the world. However, most of the existing systems do not provide highly effective force-feedback experiences to the user. To provide such augmented systems in combination with force-feedback, novel ideas must be introduced that can be easily integrated with the existing VR and AR technologies. This work proposes a first-person VR game integrated with a soft exoskeleton that enhances the quality of interaction between the subject and the virtual environment (VE) through an additional force-feedback element. The effect of introducing the force-feedback element on the user is analyzed by using biosensors and questionnaire feedback. The biosensors are used to measure the level of anxiety induced in the subject during interaction with the virtual environment. Conditions in which this interaction occurs with and without force-feedback are compared. The questionnaire analyzes the perceived change in emotions of users as a result of the introduction of the force-feedback element. This game can be played by most individuals, regardless of age and physical fitness.

We present a novel framework and system for at-home rehabilitative exercise in the absence of a physical therapist. The framework includes metrics for assessing motor performance on a wide variety of exercises. We present our system, the Autonomous Training Assistant, which utilizes this framework and a low-cost accessible exercise device called the Intelligent Stick to deliver feedback as a user trains at home. We evaluated the system's multimodal feedback mechanism in a case study whose results indicate that individual preference may have a significant effect on modality assignment for optimal learning. We conclude with ideas for future work.

In this paper we introduce a novel platform that utilises multi-modal low-cost motion capture technology for the delivery of real-time visual feedback for sports performance. This platform supports the expansion to multi-modal interfaces that utilise haptic and audio feedback, which scales effectively with motor task complexity. We demonstrate an implementation of our platform within the field of sports performance. The platform includes low-cost motion capture through a fusion technique, combining a Microsoft Kinect V2 with two wrist inertial sensors, which make use of the accelerometer and gyroscope sensors, alongside a game-based Graphical User Interface (GUI) for instruction, visual feedback and gamified score tracking.

Socially Relevant Simulation Games (SRSG), a new medium for social interaction, based on real-world skills and skill development, creates a single gaming framework that connects both serious and casual players. Through a detailed case study this paper presents a design process and framework for SRSG, in the context of mixed-reality golf swing simulations. The SRSG, entitled "World of Golf", utilizes a real-time expert system to capture, analyze, and evaluate golf swing metrics. The game combines swing data with players' backgrounds, e.g., handicaps, to form individual profiles. These profiles are then used to implement a golf simulation game using artificially controlled agents who inherit the skill levels of their corresponding human users. The simulation and assessment modules provide the serious player with tools to build golf skills while allowing casual players to engage within a simulated social world. A framework that incorporates simulated golf competitions among these social agents is presented and validated by comparing the usage statistics of 10 PGA Golf Management (PGM) students with 10 non-professional students.