In order to realize haptic interaction (e.g., holding, pushing, and contacting the object) in virtual environment and mediated haptic communication with human beings (e.g., handshaking), the force feedback is required. Recently there has been a substantial need and interest in haptic displays, which can provide realistic and high fidelity physical interaction in virtual environment. The aim of our research is to implement wearable haptic displays for presentation of realistic feedback (kinesthetic stimulus) to the human arm. We developed wearable devices FlexTorque and FlexTensor that induce forces to the human arm and do not require holding any additional haptic interfaces in the human hand. It is a new technology for Virtual Reality that allows user to explore surroundings freely. The concept of Karate (empty hand) Haptics proposed by us is opposite to conventional interfaces (e.g., Wii Remote, SensAble’s PHANTOM, SPIDAR [1]) that require holding haptic interface in the hand, restricting thus the motion of the fingers in midair. The HapticEye interface allows the blind person to explore the unknown environment in a natural and effective manner. The wearer can literally see the environment by hand.

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Robotic systems that are interfaced with virtual reality gaming and task simulations are increasingly being developed to provide repetitive intensive practice to promote increased compliance and facilitate better outcomes in rehabilitation post-stroke. A major development in the use of virtual environments (VEs) has been to incorporate tactile information and interaction forces into what was previously an essentially visual experience. Robots of varying complexity are being interfaced with more traditional virtual presentations to provide haptic feedback that enriches the sensory experience and adds physical task parameters. This provides forces that produce biomechanical and neuromuscular inter-actions with the VE that approximate real-world movement more accurately than visual-only VEs, simulating the weight and force found in upper extremity tasks. The purpose of this article is to present an overview of several systems that are commercially available for ambulation training and for training movement of the upper extremity. We will also report on the system that we have developed (NJIT-RAVR system) that incorporates motivating and challenging haptic feedback effects into VE simulations to facilitate motor recovery of the upper extremity post-stroke. The NJIT-RAVR system trains both the upper arm and the hand. The robotic arm acts as an interface between the participants and the VEs, enabling multiplanar movements against gravity in a three-dimensional workspace. The ultimate question is whether this medium can provide a motivating, challenging, gaming experience with dramatically decreased physical difficulty levels, which would allow for participation by an obese person and facilitate greater adherence to exercise regimes.

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Within the context of impedance controlled exoskeletons, common actuators have important drawbacks. Either the actuators are heavy, have a complex structure or are poor torque sources, due to gearing or heavy nonlinearity. Considering our application, an impedance controlled gait rehabilitation robot for treadmill-training, we designed an actuation system that might avoid these drawbacks. It combines a lightweight joint and a simple structure with adequate torque source quality. It consists of a servomotor, a flexible Bowden cable transmission, and a force feedback loop based on a series elastic element. A basic model was developed that is shown to describe the basic dynamics of the actuator well enough for design purpose.

Further measurements show that performance is sufficient for use in a gait rehabilitation robot. The demanded force tracking bandwidths were met: 11 Hz bandwidth for the full force range (demanded 4 Hz) and 20 Hz bandwidth for smaller force range (demanded 12 Hz). The mechanical output impedance of the actuator could be reduced to hardly perceptible level. Maxima of about 0.7 Nm peaks for 4 Hz imposed motions appeared, corresponding to less than 2.5% of the maximal force output. These peaks were caused by the stick friction in the Bowden cables.

Spring stiffness variation showed that both a too stiff and a too compliant spring can worsen performance. A stiff spring reduces the maximum allowable controller gain. The relatively low control gain then causes a larger effect of stick in the force output, resulting in a less smooth output in general. Low spring stiffness, on the other side, decreases the performance of the system, because saturation will occur sooner.

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We describe our planned research in using affective feedback from body movement and posture to recognize affective states of users. Bodily expression of af-fect has received far less attention in research than facial expression. The aim of our research is to fur-ther investigate how affective states are communicated through bodily expression and to develop an evalu-ation method for assessing affective states of video gamers based on this knowledge. Current motion cap-ture systems are often intrusive to the user and restricted to lab environments, which results in biasing user experience. We propose a nonintrusive recognition system for bodily expression of affect in a video game context, which can be deployed in the wild.

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The development of HAVE applications encompasses the development of both audiovisual devices and haptic devices to deliver a higher sense of immersion in a 3D space. 2D and 3D audio technologies have been introduced to create the illusion of sound sources placed anywhere in a three-dimensional space. By processing relative left and right speaker signals, apparent sound locations can be perceived at an arbitrary point in space. Visual information in HAVE applications can be characterized by the field of view (FOV), which represents the total visible angular deviation. The FOV needs to cover between 60 and 100^∘ along the horizontal axis in order for the user to be immersed in the virtual environment. This is less than the capability of the human eye, which has an FOV range between 180 and 270^∘, depending on whether the eye is moving or not. The update rate for visual feedback is around 75Hz, and the suggested resolution is on the magnitude of 1,960 ×1,280 pixels, even though it is possible to reach 8,000 ×8,000 pixels.

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