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Sensors 2015, 15(12), 30571-30583; doi:10.3390/s151229818

Estimation of Human Arm Joints Using Two Wireless Sensors in Robotic Rehabilitation Tasks

Neuro-Bioengineering Research Group, Miguel Hernandez University, Avda. de la Universidad W/N, 03202 Elche, Spain
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Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 27 October 2015 / Revised: 1 December 2015 / Accepted: 2 December 2015 / Published: 4 December 2015
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2015)
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Abstract

This paper presents a novel kinematic reconstruction of the human arm chain with five degrees of freedom and the estimation of the shoulder location during rehabilitation therapy assisted by end-effector robotic devices. This algorithm is based on the pseudoinverse of the Jacobian through the acceleration of the upper arm, measured using an accelerometer, and the orientation of the shoulder, estimated with a magnetic angular rate and gravity (MARG) device. The results show a high accuracy in terms of arm joints and shoulder movement with respect to the real arm measured through an optoelectronic system. Furthermore, the range of motion (ROM) of 50 healthy subjects is studied from two different trials, one trying to avoid shoulder movements and the second one forcing them. Moreover, the shoulder movement in the second trial is also estimated accurately. Besides the fact that the posture of the patient can be corrected during the exercise, the therapist could use the presented algorithm as an objective assessment tool. In conclusion, the joints’ estimation enables a better adjustment of the therapy, taking into account the needs of the patient, and consequently, the arm motion improves faster. View Full-Text
Keywords: kinematic reconstruction; neuro-rehabilitation; end-effector robots; upper limbs; MARG kinematic reconstruction; neuro-rehabilitation; end-effector robots; upper limbs; MARG
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Bertomeu-Motos, A.; Lledó, L.D.; Díez, J.A.; Catalan, J.M.; Ezquerro, S.; Badesa, F.J.; Garcia-Aracil, N. Estimation of Human Arm Joints Using Two Wireless Sensors in Robotic Rehabilitation Tasks. Sensors 2015, 15, 30571-30583.

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