This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user’s feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and develo-ping a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo — Spain, presenting great acceptability by spinal chord injury patients and clinical staff.

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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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The Parasitic Humanoid (PH) is a wearable robotic human interface for sampling, modeling, and assisting nonverbal human behavior. This anthropomorphic robot senses the behavior of the wearer and has the internal models to learn the process of human sensory motor integration, thereafter it begins to predict the next behavior of the wearer using the learned models. When the reliability of the prediction is sufficient, the PH outputs the difference from the actual behavior as a request for motion to the wearer by motion induction using sensory illusion. Through the symbiotic interaction, the internal model and the process of human sensory motor integration approximate each other asymptotically. This process is available to transmit modalities such as senses of sight, hearing, touch, force and balance with human embodiment. This synergistic multimodal communication between distant people wearing PH can realize experience-sharing, skill transmission, and human behavior supports.

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