Journal of Rehabilitation Research & Development (JRRD)

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Volume 53 Number 3, 2016
   Pages 345 — 358

Abstract — Effect of clinical parameters on the control of myoelectric robotic prosthetic hands

Manfredo Atzori, PhD;1* Arjan Gijsberts, PhD;2 Claudio Castellini, PhD;3 Barbara Caputo, PhD;2 Anne-Gabrielle Mittaz Hager, PhD;4 Simone Elsig;4 Giorgio Giatsidis, MD;5 Franco Bassetto, MD;5 Henning Müller, PhD1

1Information Systems Institute at the University of Applied Sciences Western Switzerland (HES-SO Valais), Sierre, Switzerland; 2Department of Computer, Control, and Management Engineering, University of Rome, Roma, Italy; 3Robotics and Mechatronics Center of the DLR—German Aerospace Center, Oberpfaffenhofen, Germany; 4School of Health Sciences, Physiotherapy at the University of Applied Sciences Western Switzerland (HES-SO Valais), Leukerbad, Switzerland; 5Clinic of Plastic Surgery, Padova University Hospital, Padova, Italy

Abstract — Improving the functionality of prosthetic hands with noninvasive techniques is still a challenge. Surface electromyography (sEMG) currently gives limited control capabilities; however, the application of machine learning to the analysis of sEMG signals is promising and has recently been applied in practice, but many questions still remain. In this study, we recorded the sEMG activity of the forearm of 11 male subjects with transradial amputation who were mentally performing 40 hand and wrist movements. The classification performance and the number of independent movements (defined as the subset of movements that could be distinguished with >90% accuracy) were studied in relationship to clinical parameters related to the amputation. The analysis showed that classification accuracy and the number of independent movements increased significantly with phantom limb sensation intensity, remaining forearm percentage, and time since amputation. The classification results suggest the possibility of naturally controlling up to 11 movements of a robotic prosthetic hand with almost no training. Knowledge of the relationship between classification accuracy and clinical parameters adds new information regarding the nature of phantom limb pain as well as other clinical parameters, and it can lay the foundations for future "functional amputation" procedures in surgery.

Key words: myoelectric prosthesis, phantom limb pain, phantom limb sensation, prosthesis, prosthetic hand, residual limb, residual limb length, robotic prosthesis, sEMG, transradial amputation.

View HTML ¦ View PDF ¦ Contents Vol. 53, No.3

This article and any supplementary material should be cited as follows:
Atzori M, Gijsberts A, Castellini C, Caputo B, Hager AM, Elsig S, Giatsidis G, Bassetto F, Müller H. Effect of clinical parameters on the control of myoelectric robotic prosthetic hands. J Rehabil Res Dev. 2016;53(3):345–58.
ORCID: Manfredo Atzori, PhD: 0000-0001-5397-2063; Claudio Castellini, PhD: 0000-0002-7346-2180; Barbara Caputo, PhD: 0000-0001-7169-0158; Anne-Gabrielle Mittaz Hager, PhD: 0000-0001-9461-2937; Simone Elsig: 0000-0003-2364-1671; Franco Bassetto, MD: 0000-0003-4105-8252; Henning Müller, PhD: 0000-0001-6800-9878

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Last Reviewed or Updated  Wednesday, May 4, 2016 10:29 AM

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