Literature DB >> 28813952

Comparative performance analysis of M-IMU/EMG and voice user interfaces for assistive robots.

Clemente Laureiti, Francesca Cordella, Francesco Scotto di Luzio, Stefano Saccucci, Angelo Davalli, Rinaldo Sacchetti, Loredana Zollo.   

Abstract

People with a high level of disability experience great difficulties to perform activities of daily living and resort to their residual motor functions in order to operate assistive devices. The commercially available interfaces used to control assistive manipulators are typically based on joysticks and can be used only by subjects with upper-limb residual mobilities. Many other solutions can be found in the literature, based on the use of multiple sensory systems for detecting the human motion intention and state. Some of them require a high cognitive workload for the user. Some others are more intuitive and easy to use but have not been widely investigated in terms of usability and user acceptance. The objective of this work is to propose an intuitive and robust user interface for assistive robots, not obtrusive for the user and easily adaptable for subjects with different levels of disability. The proposed user interface is based on the combination of M-IMU and EMG for the continuous control of an arm-hand robotic system by means of M-IMUs. The system has been experimentally validated and compared to a standard voice interface. Sixteen healthy subjects volunteered to participate in the study: 8 subjects used the combined M-IMU/EMG robot control, and 8 subjects used the voice control. The arm-hand robotic system made of the KUKA LWR 4+ and the IH2 Azzurra hand was controlled to accomplish the daily living task of drinking. Performance indices and evaluation scales were adopted to assess performance of the two interfaces.

Entities:  

Mesh:

Year:  2017        PMID: 28813952     DOI: 10.1109/ICORR.2017.8009380

Source DB:  PubMed          Journal:  IEEE Int Conf Rehabil Robot        ISSN: 1945-7898


  2 in total

1.  A teleoperated control approach for anthropomorphic manipulator using magneto-inertial sensors.

Authors:  A Noccaro; F Cordella; L Zollo; G Di Pino; E Guglielmelli; D Formica
Journal:  ROMAN       Date:  2017-12-14

2.  Learning by Demonstration for Motion Planning of Upper-Limb Exoskeletons.

Authors:  Clemente Lauretti; Francesca Cordella; Anna Lisa Ciancio; Emilio Trigili; Jose Maria Catalan; Francisco Javier Badesa; Simona Crea; Silvio Marcello Pagliara; Silvia Sterzi; Nicola Vitiello; Nicolas Garcia Aracil; Loredana Zollo
Journal:  Front Neurorobot       Date:  2018-02-23       Impact factor: 2.650

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.