Parametric Identification Of Lower Limbs During Walking Of A Man
Author(s)
J. Pauk & K. Jaworek
Abstract
The paper presents a new method, which could be used in bioengineering as assessment of walking recovery. The method is identification human gait model. It is based on regression function. The method very accurately represents real data from experiment by model.
1 Introduction
The human body is a mass of complex segments. Walking involves a combination of complex movements of these segments. Computers can’t cope with the full complexity of the human body. We therefore have to make assumption to develop a simple model of the movement of the body which the computer can cope with mathematically and which we can understand. Modelling involves quite sophisticated computer programmes. Presented method is based on identification human gait model from power developed by muscle joints. We obtain coefficients of model that determine human movement. Evaluation parameters of gait is helpful in assessing abnormal gait, to quantify improvement resulting from intervention. Authors proposed a ambulatory system which could support decision making in medicine. This system consists from data base of patients, model of norma and model of different pathologies. The main block is identification human gait in this system. This system is useful in several clinical situations to support decision making relate to treatment (rehabilitation, surgical treatment, medicine, etc.), It provides satisfactory results for normal walking and abnormal gait. We have proposed a new diagnostic tool for gait analysis, which consists from electrogoniometer, digital filter, artificial
Keywords
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