A great deal of effort has been devoted in the past decades in the generic area of tremor management. Specific topics of modelling for objective classification of pathological tremor out of kinematics and physiological data, compensatory technologies and evaluation rating tools are just a few examples of application field. This chapter introduces a comprehensive review of research work in this generic field during the last decades. In particular special focus has been put on the systems approach and thus a specific section on modelling has been included. Aspects related to experimental protocol and tremor pattern identification are reviewed in detail with the aim of drawing a practical guideline when compensatory technology has to be developed. The current status on ambulatory and non-ambulatory tremor reduction technologies is given in the section devoted to tremor management. At the end, we finish our discussion with those aspects related to tremor evaluation.

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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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A system and method for a biological interface system that processes multicellular signals of a patient and controls one or more devices is disclosed. The system includes a sensor that detects the multicellular signals and a processing unit for producing the control signal based on the multicellular signals. The system further includes an automated configuration routine that is used to set or modify the value of one or more system configuration parameters.

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Neuroprosthetic devices based on brain-machine interface technology hold promise for the restoration of body mobility in patients suffering from devastating motor deficits caused by brain injury, neurologic diseases and limb loss. During the last decade, considerable progress has been achieved in this multidisciplinary research, mainly in the brain-machine interface that enacts upper-limb functionality. However, a considerable number of problems need to be resolved before fully functional limb neuroprostheses can be built. To move towards developing neuroprosthetic devices for humans, brain-machine interface research has to address a number of issues related to improving the quality of neuronal recordings, achieving stable, long-term performance, and extending the brain-machine interface approach to a broad range of motor and sensory functions. Here, we review the future steps that are part of the strategic plan of the Duke University Center for Neuroengineering, and its partners, the Brazilian National Institute of Brain-Machine Interfaces and the E´ cole Polytechnique Fe´de´ rale de Lausanne (EPFL) Center for Neuroprosthetics, to bring this new technology to clinical fruition.

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A robotic orthosis has been developed for spinal cord injury patients which consists of an exoskeleton robotic suit with actuators at the hip and knee joints. In this article, a presentation is made on how to generate a gait pattern to control the robotic orthosis. First, the features needed to characterize a gait pattern are defined, and then a description is given of how to extract features from the normal gait patterns contained in experimental encoder data on the hip and knee joints of a person walking normally. Next, the physical meaning of these features in a gait pattern is discussed, and methods of varying the walking speed and step size through the adjustment of features are then considered. It is shown that the desired gait pattern can be obtained by connecting these features with spline interpolation. Finally, a crutch gait pattern is produced using these features, and this is applied to the exoskeleton robot ROBIN-P1 in order to verify the proposed method.

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