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The gaming system used during the process of neurorehabilitation is developed. It is composed of: acquisition component - Wacom Intuos4 XL tablet, and a computer which processes data and uses them as control signals in Internet game. Monitoring of either personal progress or success of other users using the presented platform is enabled by special evaluation system which provides comparison of the...
In this paper we present the method for WiiMote position control in order to gain motivational feedback in stroke patients who need to train their arm movements. Developed software acts as interface between input system, such as a computer mouse, which patients could use in rehabilitation, and custom made robotized system for controlling of WiiMote. With this software it is possible to transform any...
The assisted movement in humans with paresis of upper extremities is becoming popular for neurorehabilitation. We propose a novel method for trajectory selection and assistance control. This paper presents simulation of a planar two degrees of freedom robot that assists horizontal movement of the hand. The control assumes that during the exercise the hand needs to follow healthy alike trajectories...
Use of haptic robots in neurorehabilitation is gaining interest in the scientific community. One of the most favorable features of such systems is the possibility to integrate biomimetic features in the control. The control requires an action representation which is not available directly. We developed a method for arm movement action representation which considers expert movements as a stochastic...
We present the analysis of the planar manipulandum effects to the trajectory of point to point movements in horizontal plane. This analysis is of significance for the control of a haptic robot that can be used for the rehabilitation of hemiplegic patients. The effects were assessed by comparing data collected in experiments with healthy subjects when performing simple movements that are used in the...
We present the method for classifying kinematical data required for control of a rehabilitation robot for upper extremities. The classification to two cases (success, no-success) was analyzed by two methods: Bayes estimation and artificial neural network (ANN). The results are presented for an example being envisioned for rehabilitation: playing the Wii bowling with the specially constructed pantograph...
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