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
Your Session has timed out. Please sign back in to continue.


Demain, S. , Metcalf, C. D. , Merrett, G. V. , Zheng, D. , and Cunningham, S. , 2013, “ A Narrative Review on Haptic Devices: Relating the Physiology and Psychophysical Properties of the Hand to Devices for Rehabilitation in Central Nervous System Disorders,” Disability Rehabil. Assistive Technol., 8(3), pp. 181–189. [CrossRef]
Heo, P. , Gu, G. M. , Lee, S. , Rhee, K. , and Kim, J. , 2012, “ Current Hand Exoskeleton Technologies for Rehabilitation and Assistive Engineering,” Int. J. Precis. Eng. Manuf., 13(5), pp. 807–824. [CrossRef]
Mao, Y. , and Agrawal, S. K. , 2012, “ Design of a Cable-Driven Arm Exoskeleton (CAREX) for Neural Rehabilitation,” IEEE Trans. Rob., 28(4), pp. 922–931. [CrossRef]
Sugar, T. G. , He, J. , Koeneman, E. J. , Koeneman, J. B. , Herman, R. , Huang, H. , Schultz, R. S. , Herring, D. E. , Wanberg, J. , Balasubramanian, S. , Swenson, P. , and Ward, J. A. , 2007, “ Design and Control of RUPERT: A Device for Robotic Upper Extremity Repetitive Therapy,” IEEE Trans. Neural Syst. Rehabil. Eng., 15(3), pp. 336–346. [CrossRef] [PubMed]
Mehrholz, J. , and Marcus, P. , 2012, “ Electromechanical-Assisted Gait Training After Stroke: A Systematic Review Comparing End-Effector and Exoskeleton Devices,” J. Rehabil. Med., 44(3), pp. 193–199. [CrossRef] [PubMed]
Yin, Y. H. , Fan, Y. J. , and Xu, L. D. , 2012, “ EMG and EPP-Integrated Human–Machine Interface Between the Paralyzed and Rehabilitation Exoskeleton,” IEEE Trans. Inf. Technol. Biomed., 16(4), pp. 542–549. [CrossRef] [PubMed]
Tubiana, R. , Thomine, J. , and Mackin, E. , 1984, Examination of the Hand and Upper Limb, WB Saunders, Philadelphia, PA, p. 79.
Lee, S. W. , Landers, K. A. , and Hyung-Soon, P. , 2014, “ Development of a Biomimetic Hand Exotendon Device (BiomHED) for Restoration of Functional Hand Movement Post-Stroke,” IEEE Trans. Neural Syst. Rehabil. Eng., 22(4), pp. 886–898. [CrossRef] [PubMed]
Jack, D. , Boian, R. , Merians, A. , Adamovich, S. , Tremaine, M. , Recce, M. , Burdea, G. , and Poizner, H. , 2000, “ A Virtual Reality-Based Exercise Program for Stroke Rehabilitation,” 4th ACM SIGCAPH Conference on Assistive Technologies (Assets '00), Arlington, VA, Nov. 13–15, pp. 56–63.
Heuser, A. , Kourtev, H. , Winter, S. , Fensterheim, D. , Burdea, G. , Hentz, V. , and Forducey, P. , 2007, “ Telerehabilitation Using the Rutgers Master II Glove Following Carpal Tunnel Release Surgery: Proof-of-Concept,” IEEE Trans. Neural Syst. Rehabil. Eng., 15(1), pp. 43–49. [CrossRef] [PubMed]
VRLogic, 1999, “Datagloves—Cyberglove,” VRLogic GmbH, Dieburg, Germany, http://www.vrlogic.com/index.php/en/datagloves/cyberglovesystems
Connelly, L. , Jia, Y. , Toro, M. L. , Stoykov, M. E. , Kenyon, R. V. , and Kamper, D. G. , 2010, “ A Pneumatic Glove and Immersive Virtual Reality Environment for Hand Rehabilitative Training After Stroke,” IEEE Trans. Neural Syst. Rehabil. Eng., 18(5), pp. 551–559. [CrossRef] [PubMed]
Arata, J. , Ohmoto, K. , Gassert, R. , Lambercy, O. , Fujimoto, H. , and Wada, I. , 2013, “ A New Hand Exoskeleton Device for Rehabilitation Using a Three-Layered Sliding Spring Mechanism,” IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, May 6–10, pp. 3902–3907.
Diftler, M. A. , Ihrke, C. A. , Bridgwater, L. B. , Davis, D. R. , Linn, D. M. , Laske, E. A. , Ensley, K. G. , and Lee, J. H. , 2014, “ RoboGlove—A Robonaut Derived Multipurpose Assistive Device,” International Conference on Robotics and Automation (ICRA), Hong Kong, May 31–June 7.
Ma, Z. , and Ben-Tzvi, P. , 2015, “ RML Glove—An Exoskeleton Glove Mechanism With Haptics Feedback,” IEEE/ASME Trans. Mechatronics, 20(2), pp. 641–652. [CrossRef]
Kawasaki, H. , Ito, S. , Ishigure, Y. , Nishimoto, Y. , Aoki, T. , Mouri, T. , Sakaeda, H. , and Abe, M. , 2007, “ Development of a Hand Motion Assist Robot for Rehabilitation Therapy by Patient Self-Motion Control,” IEEE International Conference on Robotic Rehabilitation (ICORR 2007), Noordwijk, The Netherlands, June 13–15, pp. 234–240.
Dovat, L. , Lambercy, O. , Gassert, R. , Maeder, T. , Milner, T. , Leong, T. C. , and Burdet, E. , 2008, “ HandCARE: A Cable-Actuated Rehabilitation System to Train Hand Function After Stroke,” IEEE Trans. Neural Syst. Rehabil. Eng., 16(6), pp. 582–591. [CrossRef] [PubMed]
Endo, T. , Tanimura, S. , and Kawasaki, H. , 2013, “ Development of Tool-Type Devices for a Multi-Fingered Haptic Interface Robot,” IEEE Trans. Rob., 29(1), pp. 68–81. [CrossRef]
QAL Medical, 2014, “ 6000X WaveFlex Hand CPM,” QAL Medical LLC, Marinette, WI, http://qalmedical.com/waveflex-hand-cpm-device/
Schabowsky, C. , Godfrey, S. , Holley, R. , and Lum, P. , 2010, “ Development and Pilot Testing of HEXORR: Hand EXOskeleton Rehabilitation Robot,” J. NeuroEng. Rehabil., 7(1), p. 36. [CrossRef]
Takahashi, C. D. , Der-Yeghiaian, L. , Le, V. , and Cramer, S. , 2005, “ A Robotic Device for Hand Motor Therapy After Stroke,” IEEE 9th International Conference on Rehabilitation Robotics: Frontiers of the Human-Machine Interface (ICORR 2005), Chicago, IL, June 28–July 1, pp. 17–20.
Kadowaki, Y. , Noritsugu, T. , Takaiwa, M. , Sasaki, D. , and Kato, M. , 2011, “ Development of Soft Power-Assist Glove and Control Based on Human Intent,” J. Rob. Mechatronics, 23(2), pp. 281–291. [CrossRef]
Polygerinos, P. , Wang, Z. , Galloway, K. C. , Wood, R. J. , and Walsh, C. J. , 2014, “ Soft Robotic Glove for Combined Assistance and At-Home Rehabilitation,” Rob. Auton. Syst., 73, pp. 135–143. [CrossRef]
Vanoglio, F. , Luisa, A. , Garofali, F. , and Mora, C. , 2013, “ Evaluation of the Effectiveness of Gloreha (Hand Rehabilitation Glove) on Hemiplegic Patients. Pilot Study,” XIII Congress of Italian Society of Neurorehabilitation, Bari, Italy, Apr. 18–20.
Ma, Z. , and Ben-Tzvi, P. , 2015, “ Sensing and Force-Feedback Exoskeleton (SAFE) Robotic Glove,” IEEE Trans. Neural Syst. Rehabil. Eng., 23(6), pp. 992–1002. [CrossRef] [PubMed]
Ma, Z. , and Ben-Tzvi, P. , 2015, “ Design and Optimization of a Five-Finger Haptic Glove Mechanism,” ASME J. Mech. Rob., 7(4), p. 041008. [CrossRef]
Ma, Z. , Ben-Tzvi, P. , and Danoff, J. , 2015, “ Hand Rehabilitation Learning System With an Exoskeleton Robotic Glove,” IEEE Trans. Neural Syst. Rehabil. Eng. (in press).
Marin, J.-M. , Mengersen, K. , and Robert, C. P. , 2005, “ Bayesian Modelling and Inference on Mixtures of Distributions,” Handbook of Statistics 25, Elsevier, Amsterdam, pp. 459–507.
Tomasi, G. , van den Berg, F. , and Anderson, C. A. , 2004, “ Correlation Optimized Warping and Dynamic Time Warping as Preprocessing Methods for Chromatographic Data,” J. Chemom., 18(5), pp. 231–241. [CrossRef]
Ren, Y. , Park, H. S. , and Zhang, L. Q. , 2009, “ Developing a Whole-Arm Exoskeleton Robot With Hand Opening and Closing Mechanism for Upper Limb Stroke Rehabilitation,” IEEE International Conference on Rehabilitation Robotics (ICORR 2009), Kyoto, Japan, June 23–26, pp. 761–765.
Burdea, G. , and Coiffet, P. , 2003, Virtual Reality Technology, 2nd ed., Wiley, New York.
Ohashi, T. , Szemes, P. , Korondi, P. , and Hashimoto, H. , 1999, “ Nonlinear Disturbance Compensation for Haptic Device,” IEEE International Symposium on Industrial Electronics (ISIE '99), Bled, Slovenia, July 12–16, pp. 304–309.


Grahic Jump Location
Fig. 5

Overview of the rehabilitation learning system

Grahic Jump Location
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

Grahic Jump Location
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

Grahic Jump Location
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)

Grahic Jump Location
Fig. 1

CAD model of the hand and SAFER glove system

Grahic Jump Location
Fig. 6

SAFER glove prototype worn on a right hand

Grahic Jump Location
Fig. 7

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

Grahic Jump Location
Fig. 8

Flowchart of the control algorithm for free motion test

Grahic Jump Location
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.

Grahic Jump Location
Fig. 9

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

Grahic Jump Location
Fig. 10

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

Grahic Jump Location
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

Grahic Jump Location
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

Grahic Jump Location
Fig. 13

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

Grahic Jump Location
Fig. 14

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

Grahic Jump Location
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

Grahic Jump Location
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

Grahic Jump Location
Fig. 18

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

Grahic Jump Location
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)



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In