Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-22T17:09:47.645Z Has data issue: false hasContentIssue false
  • English
  • Français

AssistOn-Finger: An under-actuated finger exoskeleton for robot-assisted tendon therapy

Published online by Cambridge University Press:  17 July 2014

Ismail Hakan Ertas ,
Elif Hocaoglu  and
Volkan Patoglu
Ismail Hakan Ertas
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, 34956 Istanbul, Turkeyhertas@sabanciuniv.edu, elifhocaoglu@sabanciuniv.edu
Elif Hocaoglu
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, 34956 Istanbul, Turkeyhertas@sabanciuniv.edu, elifhocaoglu@sabanciuniv.edu
Volkan Patoglu*
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, 34956 Istanbul, Turkeyhertas@sabanciuniv.edu, elifhocaoglu@sabanciuniv.edu
*
*Corresponding author. E-mail: vpatoglu@sabanciuniv.edu
Get access Rights & Permissions [Opens in a new window]

Summary

We present AssistOn-Finger, a novel under-actuated active exoskeleton for robot-assisted tendon therapy of human fingers. The primary use for the exoskeleton is to assist flexion/extension motions of a finger within its full range, while decreasing voluntary muscle contractions helping to keep the tendon tension levels to stay within acceptable limits, avoiding gap formation or rupture of the suture. The device can also be employed to administer range of motion (RoM)/strengthening exercises. AssistOn-Finger is designed to be passively back-driveable, can cover the whole RoM of patients, and can do so in a natural and coordinated manner. In particular, the device employs human finger as an integral part of its kinematics and when coupled to a human operator, the parallel kinematic structure of exoskeleton supports three independent degrees of freedom, dictated by the kinematics of the human finger. Automatically aligning its joint axes to match finger joint axes, AssistOn-Finger can guarantee ergonomy and comfort throughout the therapy. The self-aligning feature also significantly shortens the setup time required to attach the patient to the exoskeleton. We present the kinematic type selection for the exoskeleton to satisfy the design requirements for tendon therapy applications, detail optimal dimensional synthesis of the device considering trade-offs between multiple design criteria and discuss implementation details of the exoskeleton. We also present feasibility studies conducted on healthy volunteers and provide statistical evidence on the efficacy of exoskeleton driven exercises in keeping the average muscle recruitment and the maximum tendon tension levels as low as human guided therapies.

Keywords

Finger exoskeletonTendon therapyRehabilitationDesign optimizationDimensional synthesisUnder-actuation
Type
Articles
Information
Robotica , Volume 32 , Issue 8: Rehabilitation Robotics and Human-Robot Interaction , December 2014 , pp. 1363 - 1382
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Trombly, C. A., “Occupational therapy for physical dysfunction,” Stroke, 454–471 (1989).Google Scholar
2.Dennerlein, J. T., “Finger flexor tendon forces are a complex function of finger joint motions and fingertip forces,” J. Hand therapy 18, 120–127 (2005).Google Scholar
3.Strickland, J. W. and Glogovac, S. V., “Digital function following flexor tendon repair in zone II: A comparison of immobilization and controlled passive motion techniques,” J. Hand Surg. 5A, 537–543 (1980).Google Scholar
4.Tanaka, T., Amadio, P. C., Zhao, C., Zobitz, M. E. and An, K. N., “Flexor digitorum profundus tendon tension during finger manipulation,” J. Hand Theraphy 18, 330–338 (2005).CrossRefGoogle ScholarPubMed
5.Strien, G. V., “Postoperative management of flexor tendon injuries,” Rehabil. Hand 1, 390–409 (1990).Google Scholar
6.Stewart, K. M., “Concepts in hand rehabilitation,” Tendon Injuries 353–392 (1992).Google Scholar
7.Kerr, C. D. and Burczak, J. R., “Dynamic traction after extensor tendon repair in zones 6, 7 and 8: A retrospective study,” J. Hand Surg. 14B, 21–22 (1989).Google Scholar
8.Evans, R. B., “Clinical application of controlled stress to the healing extensor tendon: A review of 112 cases,” Phys. Theraphy 69, 1041–1049 (1989).Google Scholar
9.Strickland, J. W., “Flexor tendon repair,” Hand Clinics 1, 55–68 (1985).CrossRefGoogle ScholarPubMed
10.Halikis, M. N., Manske, P. R., Kubota, H. and Aoki, M., “Effect of immobilization, immediate mobilization, and delayed mobilization on the resistance to digital flexion using a tendon injury model,” J. Hand Surg. 22, 464–472 (1997).Google Scholar
11.Cullen, K. W., Tolhurst, P. and Lang, P. R. E., “Flexor tendon repair in zone 2 followed by controlled active mobilisation,” J. Hand Surg. 14B, 392–395 (1989).Google Scholar
12.Kleinert, H. E., Schepel, S. and Gill, T., “Flexor tendon injuries,” Surg. Clin. North Am. 61, 267–286, (1981).CrossRefGoogle ScholarPubMed
13.Prange, G. B., Jannink, M. J., Groothuis-Oudshoorn, C. G., Hermens, H. J. and Ijzerman, M. J., “Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke,” J. Rehabil. Res. Dev. 43 (2), 171–184 (2006).CrossRefGoogle Scholar
14.Kwakkel, G., Kollen, B. J. and Krebs, H. I., “Effects of robot-assisted therapy on upper limb recovery after stroke: A systematic review,” Neurorehabilitation and Neural Repair 22 (2), 111–121 (2008).Google Scholar
15.Mehrholz, J., Platz, T., Kugler, J. and Pohl, M., “Electromechanical and robot-assisted arm training for improving arm function and activities of daily living after stroke,” Stroke 40 (2009).CrossRefGoogle Scholar
16.Nykanen, K., The Effectiveness of Robot-Aided Upper Limb Therapy in Stroke Rehabilitation: A Systematic Review of Randomized Controlled Studies Master's Thesis (University of Jyvskyl, Institute of Health Sciences, Physiotherapy, 2010).Google Scholar
17.“Theraband website,” http://www.thera-band.com/store/products.php?ProductID=22.Google Scholar
18.“Gripmaster website,” http://www.gripmaster.com.au/index1.htm.Google Scholar
19.“VQ Orthocare website,” http://www.jimmedical.com/products/8091-portable-hand-cpm.Google Scholar
20.“Tyromotion website,” http://www.tyromotion.com/.Google Scholar
21.Kawasaki, H., “Multi-fingered haptic interface robot and its application systems,” Solid State Phenom. 144, 1–8 (2009).Google Scholar
22.Stergiopoulos, P., Fuchs, P. and Laurgeau, C., “Design of a 2-finger hand exoskeleton for VR grasping simulation,” EuroHaptics (2003).Google Scholar
23.Frisoli, A., Salsedo, F., Bergamasco, M. and Carboncini, B. R. M. C., “A force-feedback exoskeleton for upper-limb rehabilitation in virtual reality,” Appl. Bionics Biomech. 6, 115–126 (2009).Google Scholar
24.Mulas, M., Folgheraiter, M. and Gini, G. A., “EMG-controlled Exoskeleton for Hand Rehabilitation,” Proceedings of the IEEE International Conference on Rehabilitation Robotics (2005) pp. 371–374.Google Scholar
25.Worsnopp, T., Peshkin, M., Colgate, J. and Kamper, D., “An Actuated Finger Exoskeleton for Hand Rehabilitation following Stroke,” Proceedings of the IEEE International Conference on Rehabilitation Robotics (Jun. 2007) pp. 896–901.Google Scholar
26.Adamovich, S. V., Fluet, G. G., Mathai, A., Qiu, Q., Lewis, J. and Merians, A. S., “Design of a complex virtual reality simulation to train finger motion for persons with hemiparesis: A proof of concept study,” J. NeuroEngineering Rehabil. 6 (1), 1–13 (2009).CrossRefGoogle ScholarPubMed
27.Jack, D., Boian, R., Merians, A. S., Tremaine, M., Burdea, G. C. and Adamovich, S. V., “Virtual reality-enhanced stroke rehabilitation,” IEEE Trans. Neural Syst. Rehabil. Eng. 9, 308–318 (2001).Google Scholar
28.Avizanno, C. A., Barbagli, F., Frisoli, A. and Bergamasco, M., “The Hand Force Feedback: Analysis and Control of a Haptic Device for the Human Hand,” Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (2000) pp. 989–994.Google Scholar
29.Wege, A. and Hommel, G., “Development and Control of a Hand Exoskeleton for Rehabilitation of Hand Injuries,” Proceedings of the International Conference on Intelligent Robots and Systems (2005) pp. 3046–3051.Google Scholar
30.Mali, U. and Munih, M., “HIFE-haptic interface for finger exercise,” IEEE/ASME Trans Mechatronics 11, 93–102 (2006).Google Scholar
31.Fu, Y., Wang, P., Wang, S., Liu, H. and Zhang, F., “Design and Development of a Portable Exoskeleton based cpm Machine for Rehabilitation of Hand Injuries,” Proceedings of the IEEE International Conference on Robotics and Biomimetics (Dec. 2007) pp. 1476–1481.Google Scholar
32.Fu, Y., Wang, P. and Wang, S., “Development of a Multi-DoF Exoskeleton Based Machine for Injured Fingers,” IEEE International Conference on Intelligent Robots and Systems (Sep. 2008) pp. 1946–1951.Google Scholar
33.Ertas, I. H., Hocaoglu, E., Barkana, D. E. and Patoglu, V., “Finger Exoskeleton for Treatment of Tendon Injuries,” Proceedings of the IEEE International Conference on Rehabilitation Robotics (2009).CrossRefGoogle Scholar
34.Lum, P. S., Mulroy, S., Amdur, R. L., Requejo, P., Prilutsky, B. I. and Dromerick, A. W., “Gains in upper extremity function after stroke via recovery or compensation: Potential differential effects on amount of real-world limb use,” Top. Stroke Rehabil. 16 (4), 237–253 (2009).CrossRefGoogle ScholarPubMed
35.Becker, J. C. and Thakor, N. V., “A study of the range of motion of human fingers with application to anthropomorphic designs,” IEEE Trans. Biomed. Eng. 35, 110–117 (1988).Google Scholar
36.Alexander, B. and Viktor, K., “Proportions of hand segments,” Int. J. Morphology 8 (3), 755–758 (2010).Google Scholar
37.Mouri, T., Kawasaki, H., Nishimoto, Y., Aoki, T., Ishigure, Y. and Tanahashi, M., “Robot hand imitating disabled person for education/training of rehabilitation,” J. Robot. Mechatronics 20 (2), 280–288 (2008).CrossRefGoogle Scholar
38.Valero-Cuevas, F. J., Zajac, F. E. and Burgar, C. G., “Large index finger tip forces are produced by subject-independent patterns of muscle excitation,” J. Biomech. 31, 693–703 (1998).CrossRefGoogle Scholar
39.Tanaka, T., Amadio, P. C., Zhao, C., Zobitx, M. E., Yang, C. and An, K.-N., “Gliding characteristics and gap formation for locking and grasping tendon repairs: A biomechanical study in a human cadaver model,” J. Hand Surg. 29A (1), 6–14 (2004).Google Scholar
40.Patoglu, V., Ertek, G., Oz, O., Zoroglu, D. and Kremer, G., “Design Requirements for a Finger Rehabilitation Robot: Results from a Survey of Engineers and Health Professionals,” Proceedings of the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE (2010).Google Scholar
41.Birglen, L., Laliberte, T. and Gosselin, C., Underactuated Robotic Hands (Springer, Berlin, 2008).Google Scholar
42.Cabas, R., Cabas, L. M. and Balaguer, C., “Optimized Design of the Underactuated Robotic Hand,” Proceedings of the International Conference on Robotics and Automation (May, 2006), pp. 982–987.Google Scholar
43.Nacy, S. M., Hassan, S. S. and Bakhy, S. H., “Geometric optimization of three-phalanx prosthesis underactuated fingers using particles swarm algorithm,” Am. J. Eng. Appl. Sci. 2 (2), 381–387 (2009).Google Scholar
44.Wu, L. C., Carbone, G. and Ceccarelli, M., “Designing an underactuated mechanism for a 1 active dof finger operation,” Mech. Mach. Theory 44 (2), 336–348 (Feb. 2009).Google Scholar
45.Yao, S., Ceccarelli, M., Carbone, G. and Lu, Z., “An Optimal Design for a New Underactuated Finger Mechanism,” The Second European Conference on Mechanism Science (2008) pp. 149–157.Google Scholar
46.Birglen, L. and Gosselin, C., “Optimal design of 2-phalanx underactuated fingers,” (2004) pp. 110–116.Google Scholar
47.Unal, R., Kiziltas, G. and Patoglu, V., “A Multi-criteria Design Optimization Framework for Haptic Interfaces,” Proceedings of the Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (Mar. 2008) 231–238.Google Scholar
48.Unal, R., Kiziltas, G. and Patoglu, V., “Multi-criteria Design Optimization of Parallel Robots,” Proceedings of the IEEE Conference on Robotics, Automation and Mechatronics (Sep. 2008) pp. 112–118.Google Scholar
49.Das, I. and Dennis, J. E., “Normal-boundary intersection: A new method for generating the pareto surface in nonlinear multi-criteria optimization problems,” SIAM J. Optim. 8 (3), 631–657 (1998).Google Scholar
50.Stocco, L., Salcudean, S. E. and Sassani, F., “Fast constrained global minimax optimization of robot parameters,” Robotica 16 (6), 595–605 (1998).Google Scholar
51.Jiting, Li, Wand Shuang, W., Ruoyin, Zheng, Yuru, Zhang and Zhongyuan, Chen, “Development of a hand exoskeleton system for index finger rehabilitation,” Chin. J. Mech. Eng. 24 (5), 215–224 (2011).Google Scholar
52.Kursa, K., Lattanza, L., Diao, E. and Rempel, D., “In vivo flexor tendon forces increase with finger and wrist flexion during active finger flexion and extension,” J Orthopaedic Res. 24, 763–769 (2006).Google Scholar
53.DeLuca, C. J., “The use of surface electromyography in biomechanics,” J. Appl. Biomech. 13, 135–163 (1997).Google Scholar
54.Farina, D., Merletti, R. and Enoka, M. R., “The extraction of neural strategies from the surface EMG,” J. Appl. Physiol. 96, 1486–1495 (2004).Google Scholar
55.Kollmitzer, J., Ebenbichler, R. G. and Kopf, A., “Reliability of surface electromyographic measurements,” Clin. Neurophysiol. 110, 725–734 (1999).CrossRefGoogle ScholarPubMed
56.Powell, E. S. and Trail, I. A., “Forces transmitted along human flexor tendons - The effect of extending the fingers against the resistance provided by rubber bands,” J. Hand Surg. 1–4 (2009).Google Scholar
57.Sancho-Bru, J. L., Perez-Gonzalez, A., Vergara-Monedero, M. and Giurintano, D., “3D dynamic model of human finger for studying free movements,” J. Biomech. 34, 1491–1500 (2001).Google Scholar
58.Pollard, N. S. and Gilbert, R. C., “Tendon Arrangement and Muscle Force Requirements for Humanlike Force Capabilities in a Robotic Finger,” Proceedings of the IEEE International Conference on Rehabilitation Robotics (2002) pp. 3755–3762.Google Scholar
59.Vigouroux, L., Quaine, F., Labarre-Vila, A. and Moutet, F., “Estimation of finger muscle tendon tensions and pulley forces during specific sport-climbing grip techniques,” J. Biomech. 39, 2583–2592 (2006).Google Scholar
60.Valero-Cuevas, F. J., Yi, J. W., Brown, D., McNamara, R. V., Paul, C. and Lipson, H., “The tendon network of the fingers performs anatomical computation at a macroscopic scale,” IEEE Trans. Biomed. Eng. 54, 1161–1166 (2007).Google Scholar
61.Vigouroux, L., Quaine, F., Labarre-Vila, A., Amarantini, D. and Moutet, F., “Using EMG data to constrain optimization procedure improves finger tendon tension estimations during static fingertip force production,” J. Biomech. 40, 2846–2856 (2007).Google Scholar
62.Long, C. and Brown, M. E., “Electromyographic kinesiology of the hand. Muscles moving the long finger,” J. Bone Joint Surg. 46, 1683–1706 (1964).CrossRefGoogle ScholarPubMed
63.Preedy, V. R. (ed.), Handbook of Anthropometry: Physical Measures of Human Form in Health and Disease (Springer, New York, 2012).Google Scholar
64.Warlow, O. and Lawson, S., “Factors Influencing Calculated Tendon Tensions in Two Established Phalangeal Models,” In: Computer Methods in Biomechanics and Biomedical Engineering (2010).Google Scholar
65.Maquirriain, J., “Achilles tendon rupture: Avoiding tendon lengthening during surgical repair and rehabilitation,” Yale J. Biol. Med. 84 (3), 289–300 (2011).Google Scholar
66.Dennerlein, J. T., Diao, E., Mote, C. D. and Rempel, D. M., “In vivo finger flexor tendon force while tapping on a keyswitch,” J. Orthopaedic Res. 17, 178–184 (1999).Google Scholar