The next generation of tools for rehabilitation robotics requires advanced human-robot interfaces able to activate the device as soon as patient’s motion intention is raised. This paper investigated the suitability of Support Vector Machine (SVM) classifiers for identification of locomotion intentions from surface electromyography (sEMG) data. A phase-dependent approach, based on foot contact and foot push off events, was employed in order to contextualize muscle activation signals. Good accuracy is demonstrated on experimental data from three healthy subjects. Classification has also been tested for different subsets of EMG features and muscles, aiming to identify a minimal setup required for the control of an EMG-based exoskeleton for rehabilitation purposes.

(далее…)

Категория: Научные статьи | Нет комментариев »

The will of humans with physical disabilities to move has found realization through the development of powered roboticexoskeleton. In this study, an energy-efficient gait pattern and swing trajectory of the powered robotic exoskeleton was proposed through function distribution analysis and the dynamic-manipulability ellipsoid (DME). To verify its feasibility and the effect of the proposed optimal gait pattern from the point view of the integrated system (human and exoskeleton), simulations were performed in the cases of walking on level ground and stair ascent/descent. Experiments such as on the metabolic cost of the human body with or without the assistance of the exoskeleton were conducted, and the power consumption of the exoskeleton was assessed, with the aim of improving the efficiency of the integrated system.

(далее…)

Категория: Научные статьи | Нет комментариев »