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Research Papers

The Design Evolution of a Sensing and Force-Feedback Exoskeleton Robotic Glove for Hand Rehabilitation Application

[+] Author and Article Information
Pinhas Ben-Tzvi

Robotics and Mechatronics Laboratory,
Mechanical Engineering Department,
Virginia Tech,
635 Prices Fork Road (0238),
Blacksburg, VA 24061
e-mail: bentzvi@vt.edu

Jerome Danoff

Milken Institute School of Public Health,
Department of Exercise and Nutrition Sciences,
The George Washington University,
950 New Hampshire Avenue, NW,
Washington, DC 20052

Zhou Ma

US Med Innovations,
6930 Carroll Avenue,
Takoma Park, MD 20912

Manuscript received September 12, 2015; final manuscript received December 9, 2015; published online May 4, 2016. Assoc. Editor: Venkat Krovi.

J. Mechanisms Robotics 8(5), 051019 (May 04, 2016) (9 pages) Paper No: JMR-15-1252; doi: 10.1115/1.4032270 History: Received September 12, 2015; Revised December 09, 2015

This paper presents the design evolution of the sensing and force-feedback exoskeleton robotic (SAFER) glove with application to hand rehabilitation. The hand grasping rehabilitation system is designed to gather kinematic and force information from the human hand and then playback the motion to assist a user in common hand grasping movements, such as grasping a bottle of water. Grasping experiments were conducted where fingertip contact forces were measured by the SAFER glove. These forces were then modeled based on a machine learning approach to obtain the learned contact force distributions. Using these distributions, fingertip force trajectories were generated with a Gaussian mixture regression (GMR) method. To demonstrate the glove's effectiveness to manipulate the hand, experiments were performed using the glove to demonstrate grasping capabilities on several objects. Instead of defining a grasping force, contact force trajectories were used to control the SAFER glove in order to actuate a user's hand while carrying out a learned grasping task.

Copyright © 2016 by ASME
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Figures

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Fig. 1

CAD model of the hand and SAFER glove system

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Fig. 2

(a) CAD model of the index finger mechanism of the glove showing the cable transmission model and (b) kinematic diagram of the finger–glove system

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Fig. 3

(a) Two-dimensional workspace comparison between index finger and the glove mechanism and (b) 3D workspace of the thumb (inner workspace) versus glove thumb mechanism (outer workspace)

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Fig. 4

Three generations of the SAFER glove prototype worn on a hand: (a) and (b) first generation, (c) and (d) second generation, and (e) and (f) third generation

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Fig. 5

Overview of the rehabilitation learning system

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Fig. 6

SAFER glove prototype worn on a right hand

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Fig. 7

DTW result for index force data related to grasping a bottle of water experiment: (a) raw data and (b) DTW results

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Fig. 8

Flowchart of the control algorithm for free motion test

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Fig. 9

Human index finger trajectories for two close/open maneuvers acquired by user 1 in test #1

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Fig. 10

Contact force (a) and actuator current (b) measured in free movement test for user 1

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Fig. 11

Demonstration of experiments for grasping different objects with the third generation SAFER glove: (a) an empty bottle, (b) a bottle of liquid, (c) a tennis ball, and (d) a marker pen

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Fig. 12

Demonstration of grasping motion and force reading from the index finger in grasping a bottle of water test: (left) fingertip motion and (right) fingertip force

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Fig. 13

The GMM model result: (left) finger motion and (right) finger force

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Fig. 14

Generated force trajectory with GMR: (left) finger motion and (right) finger force

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Fig. 15

The glove system (third generation) fitted on a wooden hand: (a) and (b) the front and back views of the wooden hand and (c) and (d) the front and back views of the glove system worn on the wooden hand

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Fig. 16

Wooden hand executing manipulation tasks. Top row: the wooden hand approached the tennis ball (by the author), grasped it, and lifted it (assisted by the author) from the table. Bottom row: the wooden hand was controlled to grasp a bottle of water.

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Fig. 17

Assisting hand motion experiment: the user's hand approaches the tennis ball, grasps it with the glove, and lifts it from the table

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Fig. 18

The force results (index finger) recorded from the glove grasping the objects from Fig. 16

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Fig. 19

Index finger motion and force during assisting grasping of a tennis ball: (a) fingertip trajectories and (b) force between the finger and the glove (G, solid line) and force between the finger and the object (F, dotted line)

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