In this paper, the feasible scheme is proposed to do visual operation and to interact with dynamic system in the 3D virtual reality environment by VR toolbox of MATLAB. Using V-realm Builder toolbox to build 3D virtual model for 5dof upper-limb rehabilitation robot, then it simulates this model in the 3D virtual scene of MATLAB and observes the simulation state of dynamic system in the virtual reality environment through simulink interface. The simulation results show that the virtual-reality system of 5dof upper-limb rehabilitation robot runs well and can emulate the features of real rehabilitation robot, laying a solid foundation for rehabilitation evaluation system and telemedicine.

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Biotechnology is a science that is growing rapidly. The objective of this project is to advance in the field. Specifically it aims to study applications of kinematics in the field of human-machine interfaces namely exoskeleton and prosthesis designs for the human hand. The methodology used in this project consists of three phases. First a theoretical model of the hand kinematics is defined from medical literature. This is done by synthesizing the hand into its simplified parameters to define a robotic model. The adjustment of the theoretical model to a hand is then done by capturing the movement using computer vision. This is done by using markers on each nail to be able to estimate their poses which consist of their spatial orientation and position. This sequence permits estimating the movement of the entire hand. Dimensional kinematic synthesis is finally applied to adapt the theoretical model to the dataset provided by computer vision. This is done by defining the equations of the movement of the theoretical hand model and is then solved by a numerical solver. This allows the creation of a persona-lized hand model that can then be used for the study of correspondences between electromyography (EMG) and the movements of the hand. In conclusion, this project has designed a robust algorithm for the tracking and estimation of the poses of the nails of the hand. It has also defined the movement equations and created an application to solve them. This has led to the nding of many nonanthropomorphic models that can be of use in the design of exoskeletons.

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В рубрике СВОЙ БИЗНЕС / КОНКУРС-2011 в журнале Forbes опубликовано описание проекта:Экзоскелетный разгрузочный комплекс. Название компании Общество с Ограниченной Ответственностью «Студенческий Научный Центр»

Краткое содержание проекта

Экзоскелетный разгрузочный комплекс конструктивно состоит из трех элементов:
1. Верхняя часть — силовой элемент, расположенный вдоль позвоночника;
2. Средняя часть — конструкция, напоминающая альпинистскую систему, которая служит для крепления элементов нижней части комплекса;
3. Нижняя часть — уникальная система из шарниров и параллелограммов, обеспечивающая перераспределение веса тела при полном сохранении подвижности. Комплекс может выполнять целый спектр задач и использоваться в медицинских, оздоровительных или спортивных целях, корректировать осанку, применяться при лечении заболеваний спины, устранять нагрузку на позвоночник, фиксировать различные части опорно-двигательного аппарата и т.д. Уникальные нововведения: применение экзоскелетной системы и механизм переноса веса тела или его частей на бедра.

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Категория: Экзоскелетный разгрузочный комплекс | 11 комментариев »

The number of people who need rehabilitation increases day by day because of reasons such as laceration, aging, work accidents and etc. Therefore, the need of rehabilitation aids is constantly increasing. There are many research studies about assistive technologies in rehabilitation. Especially, rehabilitation robots have a great importance. Existing rehabilitation robot studies have mostly focused on position and force control. Thus, it is muscular activation that should be evaluated to enhance control results, because the same joint trajectory and/or joint torque can be achieved through different muscular combinations. In this study a muscular activation controlled rehabilitation robot system for lower limbs is proposed. A probabilistic artificial neural network model, which can estimate posteriori probability, was used for discrimination of EMG patterns for robot control with EMG signals.

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