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Technical Brief

Real-Time Estimation of Glenohumeral Joint Rotation Center With Cable-Driven Arm Exoskeleton (CAREX)—A Cable-Based Arm Exoskeleton

[+] Author and Article Information
Ying Mao

GE Global Research,
1 Research Circle,
Niskayuna, NY 12309
e-mail: yingmao@ge.com

Xin Jin

Department of Mechanical Engineering,
Columbia University,
New York, NY 10027
e-mail: xj2146@columbia.edu

Sunil K. Agrawal

Professor
Department of Mechanical Engineering,
Columbia University,
New York, NY 10027
e-mail: Sunil.Agrawal@columbia.edu

1Corresponding author.

2Ying Mao is currently affiliated with GE Global Research. All work presented in this paper was completed prior to joining GE at University of Delaware.

Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANISMS AND ROBOTICS. Manuscript received February 21, 2012; final manuscript received September 26, 2013; published online December 27, 2013. Assoc. Editor: Kazem Kazerounian.

J. Mechanisms Robotics 6(1), 014502 (Dec 27, 2013) (5 pages) Paper No: JMR-12-1017; doi: 10.1115/1.4025926 History: Received February 21, 2012; Revised September 26, 2013

In the past few years, the authors have proposed several prototypes of a Cable-driven upper ARm EXoskeleton (CAREX) for arm rehabilitation. One of the assumptions of CAREX was that the glenohumeral joint rotation center (GH-c) remains stationary in the inertial frame during motion, which leads to inaccuracy in the kinematic model and may hamper training performance. In this paper, we propose a novel approach to estimate GH-c using measurements of shoulder joint angles and cable lengths. This helps in locating the GH-c center appropriately within the kinematic model. As a result, more accurate kinematic model can be used to improve the training of human users. An estimation algorithm is presented to compute the GH-c in real-time. The algorithm was implemented on the latest prototype of CAREX. Simulations and preliminary experimental results are presented to validate the proposed GH-c estimation method.

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Figures

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Fig. 1

Left: Coordinate frames of CAREX. Right: Close-up view of a subject wearing CAREX. (A: Shoulder cuff. B: Upper arm cuff. C: Forearm cuff. D: Extension bar. E: Orientation sensor. F: Rotary encoder. G: Load cells.)

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Fig. 2

A sketch of shoulder complex with the exoskeleton. O0 is the origin of inertial frame. O6 is the origin of upper arm local coordinate frame. G is the glenohumeral joint rotation center. Si and Ui are cable attachment points of cable i on the shoulder cuff and upper arm cuff, respectively. li is the length of cable i.

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Fig. 3

Two dots connected by a dash line represent a pair of candidates for GH-c. (a) The ideal case: Every pair of candidates shares a common point for GH-c. (b) The actual case: One of the candidates of every pair clusters around the actual position of GH-c.

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Fig. 4

Flowchart of the GH-c estimation algorithm

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Fig. 5

Top row: Estimated GH-c trajectory in the presence of joint angle measurement noise and cable length measurement error. Middle row: Estimation error of GH-c. Bottom row: Shoulder joint angles q1, q2, q3.

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Fig. 6

Estimated GH-c path compared to a model

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