Pathological Sit-To-Stand Models for Control of a Rehabilitation Robotic Device

The aim of the work presented in this paper is to realise the model for the control of a robotic interface for equilibrium assistance during sit-to-stand transfer of patients affected by posture pathology as Multiple Sclerosis and Post-Fall Syndrome . Interactive robotic devices designed as human-centered robotic devices, can give more comfortable and more efficient solutions than traditional technical devices. One supposes the need of a virtual model of the pathology. This model, called "observer", aims at being used in the smoothing control part of this assisting device. A useful property of this observer should be a postural prediction ability. This article presents a study of different solutions : a Neural Trajectory Generator(NTG), a Linear Pre-dictor(LP) and a Neural Predictive Observer (NPO). Records used for the learning have been done from healthy people that stand up normally and quickly. Some tests have also been done with patients affected by cerebellar syndrome Multiple Sclerosis disease. The presented experimental results show the good accuracy of these approaches whatever the speed of the movement.