Performance Evaluation of an Assisting Device for Training "Normal-Like" Sit To Stand Movement
Journal Title: American Journal of Engineering and Applied Sciences - Year 2017, Vol 10, Issue 3
Abstract
Performance Evaluation of an Assisting Device for Training "Normal-Like" Sit To Stand Movement Pierluigi Rea, Erika Ottaviano and Gianni Castelli DOI : 10.3844/ajeassp.2017.639.648 American Journal of Engineering and Applied Sciences Volume 10, Issue 3 Pages 639-648 Abstract This paper presents a performance evaluation and results on the modelling and simulation of an assisting device to be used as aiding or guiding system for people with reduced mobility. There is a high level of motivation for elderly to perform independently basic Activities of Daily Life (ADL). Therefore, it is of great interest to design and implement reliable assisting devices that are able to help end-users mobility. Sit-To-Stand represent one of the most common ADL and a number of different devices have been proposed to reproduce a "normal-like" movement. In general, a robot for a medical application should be able to interact with a patient in safe conditions, i.e., it must not damage people or surroundings; it must be designed to guarantee high accuracy and low accelerations during the operation. In addition, it should not be too bulky to interact closely with people. It can be advisable to have an easy-in-use and low-cost system, which can be used also in a domestic environment. In this study, a performance evaluation of a Sit-To-Stand assisting device is analyzed in terms of main characteristics, such as kinematic features and actuation requirements. Experimental tests were used to analyze a "normal-like" Sit-To-Stand movement and simulation results have been reported by considering a model of the human body interacting with the proposed assisting device. Copyright © 2017 Pierluigi Rea, Erika Ottaviano and Gianni Castelli. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Authors and Affiliations
Pierluigi Rea, Erika Ottaviano, Gianni Castelli
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- EP ID EP224107
- DOI 10.3844/ajeassp.2017.639.648
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