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Research Papers

Design and Analysis of a Cable-Driven Articulated Rehabilitation System for Gait Training

[+] Author and Article Information
Aliakbar Alamdari

Mechanical and Aerospace Engineering,
SUNY at Buffalo,
Buffalo, NY 14260
e-mail: aalamdar@buffalo.edu

Venkat Krovi

Professor
Fellow ASME
Mechanical and Aerospace Engineering,
SUNY at Buffalo,
Buffalo, NY 14260
e-mail: vkrovi@buffalo.edu

1Corresponding author.

Manuscript received September 14, 2015; final manuscript received December 11, 2015; published online May 4, 2016. Assoc. Editor: James Schmiedeler.

J. Mechanisms Robotics 8(5), 051018 (May 04, 2016) (12 pages) Paper No: JMR-15-1266; doi: 10.1115/1.4032274 History: Received September 14, 2015; Revised December 11, 2015

Assisted motor therapies play a critical role in enhancing functional musculoskeletal recovery and neurological rehabilitation. Our long-term goal is to assist and automate the performance of repetitive motor-therapy of the human lower limbs. Hence, in this paper, we examine the viability of a light-weight and reconfigurable hybrid (articulated-multibody and cable) robotic system for assisting lower-extremity rehabilitation and analyze its performance. A hybrid cable-actuated articulated-multibody system is formed when multiple cables are attached from a ground-frame to various locations on an articulated-linkage-based orthosis. Our efforts initially focus on developing an analysis and simulation framework for the kinematics and dynamics of the cable-driven lower limb orthosis. A Monte Carlo approach is employed to select configuration parameters including cuff sizes, cuff locations, and the position of fixed winches. The desired motions for the rehabilitative exercises are prescribed based upon motion patterns from a normative subject cohort. We examine the viability of using two controllers—a joint-space feedback-linearized PD controller and a task-space force-control strategy—to realize trajectory- and path-tracking of the desired motions within a simulation environment. In particular, we examine performance in terms of (i) coordinated control of the redundant system; (ii) reducing internal stresses within the lower-extremity joints; and (iii) continued satisfaction of the unilateral cable-tension constraints throughout the workspace.

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Figures

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Fig. 1

ROPES: A cable-driven robotic rehabilitation system for lower-extremity. Motors 1, 2, 3, and 4 are placed in appropriate positions to generate positive cable tensions to move lower limbs in the sagittal plane along the desired trajectory, and likewise motors 5, 6, and 7 are placed in frontal plane to generate positive cable tensions based upon the prescribed lateral exercises for lower limbs.

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Fig. 2

A cable-driven robotic rehabilitation system, in which Ti, ti are cable tension and cable unit vector, respectively; diy and dix are cuff size and its position in the local frame; Kti is tensional spring for increasing the WFW

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Fig. 3

Ankle, knee, and hip moment versus angle curve for representative subject walking at 1.25 m/s. Quasi-stiffness is calculated based on the slope of the best-line fit to the moment-angle curve for ankle plantar-flexion (KAp), ankle dorsiflexion (KAd), knee flexion (KKf), knee extension (KKe), and hip extension (KHe) and flexion (KHf) [2931].

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Fig. 4

Hip, knee, ankle, and normalized ground reaction forces of healthy subject during walking with different speeds. These values are considered as desired angles and forces, in trajectory tracking problem [50].

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Fig. 5

The distance of each cuff from the local frame origin as shown in Fig. 2

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Fig. 6

The trend of each cuff radius

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Fig. 7

The trend of cable placements on the fixed frame

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Fig. 8

Block diagram of trajectory tracking controller for human user lower limbs

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Fig. 9

Hip, knee, ankle, and cable length variations during a gait cycle

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Fig. 10

Cable tension forces in ROPES

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Fig. 11

Internal forces/moments at the lower-extremity joints due to cable tensions

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Fig. 12

A block diagram for impedance control of human user lower limbs by creating a virtual force to the ankle point to move it along the target path

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Fig. 13

The magnitude of foot angle (thin cyan line) on the target path (thick red line), and upper and lower bound around the foot angle (dashed-line blue curve)

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Fig. 14

The magnitude of force-field (small black arrows) around the ankle path (thick red line), and the stream of forces around the path (blue thin curve lines)

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