engleski

Robot assisted measurement and evaluation of reaching-to-grasp movement

This thesis deals with the assessment of human reach-to-grasp movement through measurement of hand kinematics by using computerized, robot-assisted methods. Objective and accurate assessment of hand prehension is needed to monitor patients progress during therapy and to validate the outcome of rehabilitation treatment in some diseases that influence motor control, such as Parkinson disease, partial spasticity after stroke, etc. It needs to be emphasized that most hand studies come from a more medically-oriented environment resulting in a fairly different approach researchers have towards the subject. Computer-assisted methods and experiments can provide more sensitive and accurate measurements of different parameters of hand prehension while reducing the examination time and resources. In this dissertation we present a robot-assisted experimental procedure for measurement and evaluation of hand preshaping during reach-to-grasp movement. The problem of assessing parameters of reach-to-grasp movements was dealt in a laboratory environment using industrial robot which presented the objects to be grasped, changed their orientation, position, and introduced different perturbations. In the presented experiment we took the advantage of the fact that robot movements can be accurately repeated as many times as desired and that other sensory device such as 3D motion-tracking system can also be incorporated into the experimental setup. In other experiment presented in this dissertation we used two different types of motion-tracking devices (3D optical system, Optotrak, and commercial instrumented glove, 14 sensors Ultra Data Glove) with the aim to answer if the rather simple glove-system can substitute complex and expensive optical system in assessment of hand preshaping during reach-to-grasp. Outcomes of performed experiments are newly defined parameters which can quantitatively describe some aspects of reach-to-grasp movements in healthy population. We also proposed the hand model on which the direct kinematics approach can be applied in order to calculate fingers joints spatial positions and kinematics on the basis of goniometric data measured by commercial instrumented glove. In the following chapters, the data from all performed experiments are shown and analyzed. It is also discussed whether the study could have useful implications to developing future applications in clinical environment.

biomedical engineering; reach-to-grasp movement; hand modelling; hand kinematics; 3D optical motion-capture systems; instrumented glove

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