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This paper presents a novel approach to train how to juggle using a sensor system based on one of the most commercial, sophisticated and accessible input devices, the Wii Remote controller. This platform, particularly its infrared camera, is used to develop a real-time sensor system for hand motion tracking and fit it into a virtual reality interface. The quality of our algorithm was tested through this 3D virtual interface, which has the finality to give the user visual feedback of his/her hand positions, and created for the user the sensation of juggling.

This paper presents a novel and low-cost interface designed for real-time human locomotion speed recognition, which fits with the exploration of kinesthetic virtual environments (VE). According to the interface paradigm, the human locomotion recognition feeds VE navigation control. An experimental session has been organized in order to acquire acceleration data related to locomotion of 10 healthy subjects (men and women) aging between 23 and 35 years. A treadmill has been used to capture the velocity at which subjects were moving. Our system was designed to optimize classification performances in human locomotion speed recognition in real-time. The recognized human speed locomotion has been shown to enhance users' sensation of presence in the virtual environment. A simple scenario has been developed to assess the system functionality. The experiments carried out show that our system is excellent at classifying a wide range of human locomotion and can be used both in virtual and augmented reality (VR) environments for improved interaction.

This paper presents a novel use of sensor sytem for human gait recognition evolution to be employed in virtual environments exploration. The system allows free human motion inside a virtual environment employing human gait recognition. Experimental sessions have been organized in order to acquire acceleration data related to walking and running of several subjects. We present an algorithm that recognizes a person gait in real-time. The recognized motion can be used to enhance the presence of the user in the virtual environment. A simple scenario has been developed to assess the system functionality. The experiments carried out show that our system is suitable to classify human motion, count steps and, moreover, can be used both in virtual and augmented reality (VR) environments for an improved interaction.