Literature DB >> 20618232

Transradial prosthesis: artificial vision for control of prehension.

Strahinja Došen1, Dejan B Popović.   

Abstract

We present a practical system for controlling the prehension of a transradial prosthesis. The system is mounted on the artificial hand and comprises simple hardware and software that are convenient for real-time implementation. The hardware consists of a standard web camera and an ultrasound distance sensor. The control algorithm mimics biological mechanisms for the control of grasping and uses the measured distance to the target object and the method of computer vision to estimate the object's size and orientation. Based on these estimates, the algorithm outputs the following commands for the control of prehension: (i) the type of grasp and the aperture size appropriate for the target object; and (ii) the angle through which the wrist should be rotated (pronation/supination) in order to properly position the hand for the grasp. We have tested the system's performance with different targets (planar geometric shapes, real-life objects) under static conditions (i.e., when the system is stationary) and dynamic conditions (i.e., when the system moves toward the target). The size estimation was more accurate in the static experiments (error < 36%). Importantly, the system showed to be very robust with respect to the estimation errors, and the correct control commands were generated in most of the tested cases. The presented system is only one component of the hand controller, related strictly to the prehension phase of grasping. The final solution is envisioned as a combination of the presented system, inertial sensors (hand orientation), and a myoelectric control (triggering).
© 2010, Copyright the Authors. Artificial Organs © 2010, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

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Mesh:

Year:  2011        PMID: 20618232     DOI: 10.1111/j.1525-1594.2010.01040.x

Source DB:  PubMed          Journal:  Artif Organs        ISSN: 0160-564X            Impact factor:   3.094


  9 in total

1.  Cognitive vision system for control of dexterous prosthetic hands: experimental evaluation.

Authors:  Strahinja Dosen; Christian Cipriani; Milos Kostić; Marco Controzzi; Maria C Carrozza; Dejan B Popović
Journal:  J Neuroeng Rehabil       Date:  2010-08-23       Impact factor: 4.262

Review 2.  Recent trends in assistive technology for mobility.

Authors:  Rachel E Cowan; Benjamin J Fregly; Michael L Boninger; Leighton Chan; Mary M Rodgers; David J Reinkensmeyer
Journal:  J Neuroeng Rehabil       Date:  2012-04-20       Impact factor: 4.262

3.  Learning arm/hand coordination with an altered visual input.

Authors:  Simona Denisia Iftime Nielsen; Strahinja Dosen; Mirjana B Popović; Dejan B Popović
Journal:  Comput Intell Neurosci       Date:  2010-07-19

4.  Improving bimanual interaction with a prosthesis using semi-autonomous control.

Authors:  Robin Volkmar; Strahinja Dosen; Jose Gonzalez-Vargas; Marcus Baum; Marko Markovic
Journal:  J Neuroeng Rehabil       Date:  2019-11-14       Impact factor: 4.262

5.  A Hybrid 3D Printed Hand Prosthesis Prototype Based on sEMG and a Fully Embedded Computer Vision System.

Authors:  Maria Claudia F Castro; Wellington C Pinheiro; Glauco Rigolin
Journal:  Front Neurorobot       Date:  2022-01-24       Impact factor: 2.650

6.  Improving Robotic Hand Prosthesis Control With Eye Tracking and Computer Vision: A Multimodal Approach Based on the Visuomotor Behavior of Grasping.

Authors:  Matteo Cognolato; Manfredo Atzori; Roger Gassert; Henning Müller
Journal:  Front Artif Intell       Date:  2022-01-25

7.  Microsoft kinect-based artificial perception system for control of functional electrical stimulation assisted grasping.

Authors:  Matija Strbac; Slobodan Kočović; Marko Marković; Dejan B Popović
Journal:  Biomed Res Int       Date:  2014-08-19       Impact factor: 3.411

Review 8.  Proceedings of the first workshop on Peripheral Machine Interfaces: going beyond traditional surface electromyography.

Authors:  Claudio Castellini; Panagiotis Artemiadis; Michael Wininger; Arash Ajoudani; Merkur Alimusaj; Antonio Bicchi; Barbara Caputo; William Craelius; Strahinja Dosen; Kevin Englehart; Dario Farina; Arjan Gijsberts; Sasha B Godfrey; Levi Hargrove; Mark Ison; Todd Kuiken; Marko Marković; Patrick M Pilarski; Rüdiger Rupp; Erik Scheme
Journal:  Front Neurorobot       Date:  2014-08-15       Impact factor: 2.650

Review 9.  A Survey of Teleceptive Sensing for Wearable Assistive Robotic Devices.

Authors:  Nili E Krausz; Levi J Hargrove
Journal:  Sensors (Basel)       Date:  2019-11-28       Impact factor: 3.576

  9 in total

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