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Current hand exoskeleton technologies for rehabilitation and assistive engineering

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Abstract

In this paper, we present a comprehensive review of hand exoskeleton technologies for rehabilitation and assistive engineering, from basic hand biomechanics to actuator technologies. Because of rapid advances in mechanical designs and control algorithms for electro-mechanical systems, exoskeleton devices have been developed significantly, but are still limited to use in larger body areas such as upper and lower limbs. However, because of their requirements for smaller size and rich tactile sensing capabilities, hand exoskeletons still face many challenges in many technical areas, including hand biomechanics, neurophysiology, rehabilitation, actuators and sensors, physical human-robot interactions and ergonomics. This paper reviews the state-of-the-art of active hand exoskeletons for applications in the areas of rehabilitation and assistive robotics. The main requirements of these hand exoskeleton devices are also identified and the mechanical designs of existing devices are classified. The challenges facing an active hand exoskeleton robot are also discussed.

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References

  1. Reinkensmeyer, D. J., Emken, J. L. and Cramer, S. C., “Robotics, motor learning, and neurologic recovery,” Annual Review of Biomedical Engineering, Vol. 6, pp. 497–525, 2004.

    Article  Google Scholar 

  2. Taub, E., Miller, N., Novack, T., Cook, E., Fleming, W., Nepomuceno, C., Connell, J. and Crago, J., “Technique to improve chronic motor deficit after stroke,” Archives of Physical Medicine and Rehabilitation, Vol. 74, No. 4, pp. 347–354, 1993.

    Google Scholar 

  3. Mark, V. W. and Taub, E., “Constraint-induced movement therapy for chronic stroke hemiparesis and other disabilities,” Restorative Neurology and Neuroscience, Vol. 22, No. 3–5, pp. 317–336, 2004.

    Google Scholar 

  4. Patton, J. L. and Mussa-Ivaldi, F. A., “Robot-assisted adaptive training: custom force fields for teaching movement patterns,” IEEE Transactions on Biomedical Engineering, Vol. 51, No. 4, pp. 636–646, 2004.

    Article  Google Scholar 

  5. Heller, A., Wade, D. T., Wood, V. A., Sunderland, A., Hewer, R. L. and Ward, E., “Arm function after stroke: measurement and recovery over the first three months,” Journal of Neurology, Neurosurgery, and Psychiatry, Vol. 50, No. 6, pp. 714–719, 1987.

    Article  Google Scholar 

  6. Wade, D. T., Langton-Hewer, R., Wood, V. A., Skilbeck, C. E. and Ismail, H. M., “The hemiplegic arm after stroke: measurement and recovery,” Journal of Neurology, Neurosurgery, and Psychiatry, Vol. 46, No. 6, pp. 521–524, 1983.

    Article  Google Scholar 

  7. Sunderland, A., Tinson, D., Bradley, L. and Hewer, R. L., “Arm function after stroke. An evaluation of grip strength as a measure of recovery and a prognostic indicator,” Journal of Neurology, Neurosurgery, and Psychiatry, Vol. 52, No. 11, pp. 1267–1272, 1989.

    Article  Google Scholar 

  8. Nakayama, H., Jorgensen, H., Raaschou, H. and Olsen, T., “Recovery of upper extremity function in stroke patients: the Copenhagen Stroke Study,” Archives of Physical Medicine and Rehabilitation, Vol. 75, No. 4, pp. 394–398, 1994.

    Article  Google Scholar 

  9. Kapandji, I. A., “The physiology of the joints: annotated diagrams of the mechanics of the human joints,” Churchill Livingstone, 1987.

  10. Moran, C. A., “Anatomy of the Hand,” Physical Therapy, Vol. 69, No. 12, pp. 1007–1013, 1989.

    Google Scholar 

  11. Berme, N., Paul, J. P. and Purves, W. K., “A biomechanical analysis of the metacarpo-phalangeal joint,” Journal of Biomechanics, Vol. 10, No. 7, pp. 409–412, 1977.

    Article  Google Scholar 

  12. Lluch, A., “Intrinsic causes of stiffness of the interphalangeal joints, in: Copeland, S. A., Gschwend, N., Landi, A. and Saffar, P. (Eds.), Joint Stiffness of the Upper Limb,” Taylor & Francis, pp. 259–264, 1997.

    Google Scholar 

  13. Kapandji, I. A., “The Physiology of the Joints — Volume I: Upper Limb, 5th ed.,” Churchill Livingstone, 1982.

  14. Hollister, A. and Giurintano, D., “Thumb movements, motions, and moments,” Journal of Hand Therapy, Vol. 8, No. 2, pp. 106–114, 1995.

    Article  Google Scholar 

  15. Imaeda, T., An, K. and Cooney, W., “Functional anatomy and biomechanics of the thumb,” Hand Clinics, Vol. 8, No. 1, pp. 9–15, 1992.

    Google Scholar 

  16. Barr, A. and Bear-Lehman, J., “Biomechanics of the wrist and hand, in: Nordin, M. and Frankel, V. H. (Eds.), Basic Biomechanics of the Musculoskeletal System, 3rd ed.,” Lippincott Williams & Wilkins, pp. 358–387, 2001.

  17. Taylor, C. L. and Schwarz, R. J., “The anatomy and mechanics of the human hand,” Artificial Limbs, Vol. 2, No. 2, pp. 22–35, 1955.

    Google Scholar 

  18. Elliot, D. and McGrouther, D. A., “The excursions of the long extensor tendons of the hand,” The Journal of Hand Surgery: British & European Volume, Vol. 11, No. 1, pp. 77–80, 1986.

    Article  Google Scholar 

  19. Armstrong, T. J. and Chaffin, D. B., “An investigation of the relationship between displacements of the finger and wrist joints and the extrinsic finger flexor tendons,” Journal of Biomechanics, Vol. 11, No. 3, pp. 119–128, 1978.

    Article  Google Scholar 

  20. Kuczynski, K., “The proximal interphalangeal joint: anatomy and causes of stiffness in the fingers,” Journal of Bone and Joint Surgery-British Volume, Vol. 50, No. 3, pp. 656–663, 1968.

    Google Scholar 

  21. Shrewsbury, M. and Johnson, R., “Ligaments of the distal interphalangeal joint and the mallet position,” The Journal of Hand Surgery, Vol. 5, No. 3, pp. 214–216, 1980.

    Google Scholar 

  22. Worsnopp, T. T., Peshkin, M. A., Colgate, J. E. and Kamper, D. G., “An Actuated Finger Exoskeleton for Hand Rehabilitation Following Stroke,” Proc. of the IEEE International Conference on Rehabilitation Robotics, pp. 896–901, 2007.

  23. Fontana, M., Dettori, A., Salsedo, F. and Bergamasco, M., “Mechanical design of a novel Hand Exoskeleton for accurate force displaying,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 1704–1709, 2009.

  24. Wege, A. and Hommel, G., “Development and control of a hand exoskeleton for rehabilitation of hand injuries,” Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3046–3051, 2005.

  25. In, H. K., Cho, K.-J., Kim, K. R. and Lee, B. S., “Jointless structure and under-actuation mechanism for compact hand exoskeleton,” Proc. of the IEEE International Conference on Rehabilitation Robotics, pp. 1–6, 2011.

  26. Kadowaki, Y., Noritsugu, T., Takaiwa, M., Sasaki, D. and Kato, M., “Development of Soft Power-Assist Glove and Control Based on Human Intent,” Journal of Robotics and Mechatronics, Vol. 23, No. 2, pp. 281–291, 2011.

    Google Scholar 

  27. Stergiopoulos, P., Fuchs, P. and Laurgeau, C., “Design of a 2-finger hand exoskeleton for VR grasping simulation,” Proc. of the Eurohaptics, pp. 80–93, 2003.

  28. Nakagawara, S., Kajimoto, H., Kawakami, N., Tachi, S. and Kawabuchi, I., “An Encounter-Type Multi-Fingered Master Hand Using Circuitous Joints,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 2667–2672, 2005.

  29. Wang, J., Li, J., Zhang, Y. and Wang, S., “Design of an exoskeleton for index finger rehabilitation,” Proc. of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 5957–5960, 2009.

  30. In, H. K. and Cho, K. J., “Compact Hand Exoskeleton Robot for the Disabled,” Proc. of the International Conference on Ubiquitous Robots and Ambient Intelligence, 2009.

  31. Brokaw, E. B., Black, I., Holley, R. J. and Lum, P. S., “Hand Spring Operated Movement Enhancer (HandSOME): A Portable, Passive Hand Exoskeleton for Stroke Rehabilitation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 19, No. 4, pp. 391–399, 2011.

    Article  Google Scholar 

  32. Otto Bock HealthCare, “WaveFlex Hand CPM Device,” http://www.ottobock.ca/cps/rde/xchg/ob_us_en/hs.xsl/15712.html

  33. Patterson Medical, “Kinetec Maestra Portable Hand CPM,” http://www.pattersonmedical.com/app.aspx?cmd=get_product&id=74161

  34. Mulas, M., Folgheraiter, M. and Gini, G., “An EMG-controlled exoskeleton for hand rehabilitation,” Proc. of the 9th International Conference on Rehabilitation Robotics, pp. 371–374, 2005.

  35. Tong, K. Y., Ho, S. K., Pang, P. M. K., Hu, X. L., Tam, W. K., Fung, K. L., Wei, X. J., Chen, P. N. and Chen, M., “An intention driven hand functions task training robotic system,” Proc. of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3406–3409, 2010.

  36. Iqbal, J., Tsagarakis, N. G., Fiorilla, A. E. and Caldwell, D. G., “A portable rehabilitation device for the Hand,” Proc. of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3694–3697, 2010.

  37. Schabowsky, C., Godfrey, S., Holley, R. and Lum, P., “Development and pilot testing of HEXORR: Hand EXOskeleton Rehabilitation Robot,” Journal of NeuroEngineering and Rehabilitation, Vol. 7, No. 1, p. 36, 2010.

  38. Chiri, A., Giovacchini, F., Vitiello, N., Cattin, E., Roccella, S., Vecchi, F. and Carrozza, M. C., “HANDEXOS: Towards an exoskeleton device for the rehabilitation of the hand,” Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1106–1111, 2009.

  39. Chiri, A., Vitiello, N., Giovacchini, F., Roccella, S., Vecchi, F. and Carrozza, M. C., “Mechatronic Design and Characterization of the Index Finger Module of a Hand Exoskeleton for Post-stroke Rehabilitation,” IEEE/ASME Transactions on Mechatronics, Vol. PP, No. 99, pp. 1–11, 2011.

    Google Scholar 

  40. Wege, A. and Zimmermann, A., “Electromyography sensor based control for a hand exoskeleton,” Proc. of the IEEE International Conference on Robotics and Biomimetics, pp. 1470–1475, 2007.

  41. Ueki, S., Kawasaki, H., Ito, S., Nishimoto, Y., Abe, M., Aoki, T., Ishigure, Y., Ojika, T. and Mouri, T., “Development of a Hand-Assist Robot With Multi-Degrees-of-Freedom for Rehabilitation Therapy,” IEEE/ASME Transactions on Mechatronics, Vol. 17, No. 1, pp. 136–146, 2012.

    Article  Google Scholar 

  42. Li, J., Zheng, R., Zhang, Y. and Yao, J., “iHandRehab: An interactive hand exoskeleton for active and passive rehabilitation,” Proc. of the IEEE International Conference on Rehabilitation Robotics, pp. 1–6, 2011.

  43. Sarakoglou, I., Tsagarakis, N. G. and Caldwell, D. G., “Occupational and physical therapy using a hand exoskeleton based exerciser,” Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 3, pp. 2973–2978, 2004.

    Google Scholar 

  44. Jones, C. L., Wang, F., Osswald, C., Kang, X., Sarkar, N. and Kamper, D. G., “Control and kinematic performance analysis of an Actuated Finger Exoskeleton for hand rehabilitation following stroke,” Proc. of the 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, pp. 282–287, 2010.

  45. Ren, Y., Park, H.-S. and Zhang, L.-Q., “Developing a whole-arm exoskeleton robot with hand opening and closing mechanism for upper limb stroke rehabilitation,” Proc. of the IEEE International Conference on Rehabilitation Robotics, pp. 761–765, 2009.

  46. Kinetic Muscles Inc., “Hand Physical Therapy with The Hand Mentor™,” http://www.kineticmuscles.com/hand-physicaltherapy-hand-mentor.html

  47. Takahashi, C. D., Der-Yeghiaian, L., Le, V., Motiwala, R. R. and Cramer, S. C., “Robot-based hand motor therapy after stroke,” Brain, Vol. 131, No. 2, pp. 425–437, 2008.

    Article  Google Scholar 

  48. Wu, J., Huang, J., Wang, Y. and Xing, K., “A Wearable Rehabilitation Robotic Hand Driven by PM-TS Actuators, in: Liu, H., Ding, H., Xiong, Z. and Zhu, X. (Eds.), Intelligent Robotics and Applications,” Springer, Vol. 6425, pp. 440–450, 2010.

  49. Martinez, L. A., Olaloye, O. O., Talarico, M. V., Shah, S. M., Arends, R. J. and BuSha, B. F., “A power-assisted exoskeleton optimized for pinching and grasping motions,” Proc. of the IEEE Annual Northeast Bioengineering Conference, pp. 1–2, 2010.

  50. Rotella, M. F., Reuther, K. E., Hofmann, C. L., Hage, E. B. and BuSha, B. F., “An orthotic hand-assistive exoskeleton for actuated pinch and grasp,” Proc. of the IEEE Annual Northeast Bioengineering Conference, pp. 1–2, 2009.

  51. Baker, M. D., McDonough, M. K., McMullin, E. M., Swift, M. and BuSha, B. F., “Orthotic Hand-Assistive Exoskeleton,” Proc. of the IEEE 37th Annual Northeast Bioengineering Conference, pp. 1–2, 2011.

  52. Hasegawa, Y., Mikami, Y., Watanabe, K. and Sankai, Y., “Five-fingered assistive hand with mechanical compliance of human finger,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 718–724, 2008.

  53. Hasegawa, Y., Tokita, J., Kamibayashi, K. and Sankai, Y., “Evaluation of fingertip force accuracy in different support conditions of exoskeleton,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 680–685, 2011.

  54. Shields, B. L., Main, J. A., Peterson, S. W. and Strauss, A. M., “An anthropomorphic hand exoskeleton to prevent astronaut hand fatigue during extravehicular activities,” Proc. of the IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, Vol. 27, No. 5, pp. 668–673, 1997.

    Article  Google Scholar 

  55. Yamada, Y., Morizono, T., Sato, S., Shimohira, T., Umetani, Y., Yoshida, T. and Aoki, S., “Proposal of a SkilMate finger for EVA gloves,” Proc. of the IEEE International Conference on Robotics and Automation, Vol. 2, pp. 1406–1412, 2001.

    Google Scholar 

  56. Benjuya, N. and Kenney, S. B., “Myoelectric Hand Orthosis,” Journal of Prosthetics and Orthotics, Vol. 2, No. 2, pp. 149–154, 1990.

    Google Scholar 

  57. DiCicco, M., Lucas, L. and Matsuoka, Y., “Comparison of control strategies for an EMG controlled orthotic exoskeleton for the hand,” Proc. of the IEEE International Conference on Robotics and Automation, Vol. 2, pp. 1622–1627, 2004.

    Google Scholar 

  58. Lucas, L., DiCicco, M. and Matsuoka, Y., “An EMG-controlled hand exoskeleton for natural pinching,” Journal of Robotics and Mechatronics, Vol. 16, No. 5, pp. 482–488, 2004.

    Google Scholar 

  59. Sasaki, D., Noritsugu, T., Takaiwa, M. and Yamamoto, H., “Wearable power assist device for hand grasping using pneumatic artificial rubber muscle,” Proc. of the IEEE International Workshop on Robot and Human Interactive Communication, pp. 655–660, 2004.

  60. Tadano, K., Akai, M., Kadota, K. and Kawashima, K., “Development of grip amplified glove using bi-articular mechanism with pneumatic artificial rubber muscle,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 2363–2368, 2010.

  61. Takagi, M., Iwata, K., Takahashi, Y., Yamamoto, S. I., Koyama, H. and Komeda, T., “Development of a grip aid system using air cylinders,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 2312–2317, 2009.

  62. Toya, K., Miyagawa, T. and Kubota, Y., “Power-Assist Glove Operated by Predicting the Grasping Mode,” Journal of System Design and Dynamics, Vol. 5, No. 1, pp. 94–108, 2011.

    Article  Google Scholar 

  63. Moromugi, S., Koujina, Y., Ariki, S., Okamoto, A., Tanaka, T., Feng, M. Q. and Ishimatsu, T., “Muscle stiffness sensor to control an assistance device for the disabled,” Artificial Life and Robotics, Vol. 8, No. 1, pp. 42–45, 2004.

    Article  Google Scholar 

  64. Makaran, J. E., Dittmer, D. K., Buchal, R. O. and MacArthur, D. E., “The SMART Wrist-Hand Orthosis (WHO) for Quadriplegic Patients,” Journal of Prosthetics and Orthotics, Vol. 5, No. 3, pp. 73–76, 1993.

    Article  Google Scholar 

  65. Vas, P., “Sensorless vector and direct torque control,” Oxford University Press, 1998.

  66. Sul, S. K., “Control of electric machine drive systems,” Wiley-IEEE Press, 2011.

  67. Kim, S. H., “DC, AC, BLDC motor control,” Bogdoo, 2010.

  68. Gopura, R. A. R. C. and Kiguchi, K., “Mechanical designs of active upper-limb exoskeleton robots: State-of-the-art and design difficulties,” Proc. of the IEEE International Conference on Rehabilitation Robotics, pp. 178–187, 2009.

  69. Tondu, B. and Lopez, P., “Modeling and control of McKibben artificial muscle robot actuators,” IEEE Control Systems Magazine, Vol. 20, No. 2, pp. 15–38, 2000.

    Article  Google Scholar 

  70. Noritsugu, T., Takaiwa, M. and Sasaki, D., “Development of power assist wear using pneumatic rubber artificial muscles,” Journal of Robotics and Mechatronics, Vol. 21, No. 5, pp. 607–613, 2009.

    Google Scholar 

  71. Takashima, K., Noritsugu, T., Rossiter, J., Guo, S. and Mukai, T., “Development of curved type pneumatic artificial rubber muscle using shape-memory polymer,” Proc. of the SICE Annual Conference, pp. 1691–1695, 2011.

  72. Bar-Cohen, Y., “EAP as artificial muscles: progress and challenges,” Proc. of the Smart Structures and Materials 2004: Electroactive Polymer Actuators and Devices (EAPAD), Vol. 5385, pp. 10–16, 2004.

    Google Scholar 

  73. Mirfakhrai, T., Madden, J. D. W. and Baughman, R. H., “Polymer artificial muscles,” Materials Today, Vol. 10, No. 4, pp. 30–38, 2007.

    Article  Google Scholar 

  74. Bar-Cohen, Y., “Electro-active polymers: current capabilities and challenges,” Proc. of the SPIE, the International Society for Optical Engineering, Vol. 4695, pp. 1–7, 2002.

    Google Scholar 

  75. Deole, U., Lumia, R., Shahinpoor, M. and Bermudez, M., “Design and test of IPMC artificial muscle microgripper,” Journal of Micro-Nano Mechatronics, Vol. 4, No. 3, pp. 95–102, 2008.

    Article  Google Scholar 

  76. Abolfathi, P. P., “Development of an Instrumented and Powered Exoskeleton for the Rehabilitation of the Hand,” Ph.D. Thesis, School of Aerospace, Mechanical and Mechatronic Engineering, University of Sydney, 2007.

  77. Duncheon, C., “Robots will be of service with muscles, not motors,” Industrial Robot: An International Journal, Vol. 32, No. 6, pp. 452–455, 2005.

    Article  Google Scholar 

  78. Herr, H. and Kornbluh, R., “New horizons for orthotic and prosthetic technology: artificial muscle for ambulation,” Proc. of SPIE, Vol. 5385, pp. 1–9, 2004.

    Article  Google Scholar 

  79. Otsuka, K. and Wayman, C. M., “Shape memory materials,” Cambridge University Press, 1999.

  80. Mavroidis, C., Pfeiffer, C. and Mosley, M., “Conventional Actuators, Shape Memory Alloys and Electrorheological Fluids, in: Bar-Cohen, Y. (Ed.), Invited Chapter in Automation, Miniature Robotics and Sensors for Non-Destructive Testing and Evaluation,” The American Society for Nondestructive Testing, pp. 189–214, 2000.

  81. Kamen, G., “Electromyographic Kinesiology, in: Robertson, D. G. E. (Ed.), Research Methods in Biomechanics,” Human Kinetics, 2004.

  82. Rosen, J., Brand, M., Fuchs, M. B. and Arcan, M., “A myosignal-based powered exoskeleton system,” IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, Vol. 31, No. 3, pp. 210–222, 2001.

    Article  Google Scholar 

  83. Triolo, R. J. and Moskowitz, G. D., “The theoretical development of a multichannel time-series myoprocessor for simultaneous limb function detection and muscle force estimation,” IEEE Transactions on Biomedical Engineering, Vol. 36, No. 10, pp. 1004–1017, 1989.

    Article  Google Scholar 

  84. Clancy, E. A. and Hogan, N., “Relating agonist-antagonist electromyograms to joint torque during isometric, quasi-isotonic, nonfatiguing contractions,” IEEE Transactions on Biomedical Engineering, Vol. 44, No. 10, pp. 1024–1028, 1997.

    Article  Google Scholar 

  85. Nam, Y. S., Kim, S. N. and Baek, S.-R., “Calculation of Knee Joint Moment in Isometric and Isokinetic Knee Motion,” Int. J. Precis. Eng. Manuf., Vol. 12, No. 5, pp. 921–924, 2011.

    Article  Google Scholar 

  86. Duque, J., Masset, D. and Malchaire, J., “Evaluation of handgrip force from EMG measurements,” Applied Ergonomics, Vol. 26, No. 1, pp. 61–66, 1995.

    Article  Google Scholar 

  87. Hoozemans, M. J. M. and van Dieën, J. H., “Prediction of handgrip forces using surface EMG of forearm muscles,” Journal of Electromyography and Kinesiology, Vol. 15, No. 4, pp. 358–366, 2005.

    Article  Google Scholar 

  88. DiDomenico, A. and Nussbaum, M. A., “Estimation of forces exerted by the fingers using standardised surface electromyography from the forearm,” Ergonomics, Vol. 51, No. 6, pp. 858–871, 2008.

    Article  Google Scholar 

  89. Choi, C., Kwon, S., Park, W., Lee, H. and Kim, J., “Real-time pinch force estimation by surface electromyography using an artificial neural network,” Medical Engineering and Physics, Vol. 32, No. 5, pp. 429–436, 2010.

    Article  Google Scholar 

  90. Yu, H. L., Chase, R. A. and Strauch, B., “Atlas of hand anatomy and clinical implications,” Mosby Inc., 2004.

  91. De Luca, C. J. and Merletti, R., “Surface myoelectric signal cross-talk among muscles of the leg,” Electroencephalography and Clinical Neurophysiology, Vol. 69, No. 6, pp. 568–575, 1988.

    Article  Google Scholar 

  92. Martin, B. J., Armstrong, T. J., Foulke, J. A., Natarajan, S., Klinenberg, E., Serina, E. and Rempel, D., “Keyboard Reaction Force and Finger Flexor Electromyograms during Computer Keyboard Work,” Human Factors: The Journal of the Human Factors and Ergonomics Society, Vol. 38, No. 4, pp. 654–664, 1996.

    Article  Google Scholar 

  93. Lukowicz, P., Hanser, F., Szubski, C. and Schobersberger, W., “Detecting and Interpreting Muscle Activity with Wearable Force Sensors,” Pervasive Computing, Vol. 3968, pp. 101–116, 2006.

    Article  Google Scholar 

  94. Kasuya, M., Seki, M., Kawamura, K. and Fujie, M. G., “Subtle grip force estimation from EMG and muscle stiffness — Relationship between muscle character frequency and grip force,” Proc. of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4116–4119, 2011.

  95. Barry, D. T. and Cole, N. M., “Muscle sounds are emitted at the resonant frequencies of skeletal muscle,” IEEE Transactions on Biomedical Engineering, Vol. 37, No. 5, pp. 525–531, 1990.

    Article  Google Scholar 

  96. Youn, W. and Kim, J., “Estimation of elbow flexion force during isometric muscle contraction from mechanomyography and electromyography,” Medical and Biological Engineering and Computing, Vol. 48, No. 11, pp. 1149–1157, 2010.

    Article  Google Scholar 

  97. Silva, J., Heim, W. and Chau, T., “A Self-Contained, Mechanomyography-Driven Externally Powered Prosthesis,” Archives of Physical Medicine and Rehabilitation, Vol. 86, No. 10, pp. 2066–2070, 2005.

    Article  Google Scholar 

  98. Xie, H.-B., Zheng, Y.-P. and Guo, J.-Y., “Classification of the mechanomyogram signal using a wavelet packet transform and singular value decomposition for multifunction prosthesis control,” Physiological Measurement, Vol. 30, No. 5, pp. 441–457, 2009.

    Article  Google Scholar 

  99. Akataki, K., Mita, K., Watakabe, M. and Itoh, K., “Mechanomyogram and force relationship during voluntary isometric ramp contractions of the biceps brachii muscle,” European Journal of Applied Physiology, Vol. 84, No. 1, pp. 19–25, 2001.

    Article  Google Scholar 

  100. Madeleine, P., Farina, D., Merletti, R. and Arendt-Nielsen, L., “Upper trapezius muscle mechanomyographic and electromyographic activity in humans during low force fatiguing and non-fatiguing contractions,” European Journal of Applied Physiology, Vol. 87, No. 4, pp. 327–336, 2002.

    Article  Google Scholar 

  101. Youn, W. and Kim, J., “Feasibility of using an artificial neural network model to estimate the elbow flexion force from mechanomyography,” Journal of Neuroscience Methods, Vol. 194, No. 2, pp. 386–393, 2011.

    Article  Google Scholar 

  102. Mascaro, S. A. and Asada, H. H., “Photoplethysmograph fingernail sensors for measuring finger forces without haptic obstruction,” IEEE Transactions on Robotics and Automation, Vol. 17, No. 5, pp. 698–708, 2001.

    Article  Google Scholar 

  103. Nakatani, M., Shiojima, K., Kinoshita, S., Kawasoe, T., Koketsu, K. and Wada, J., “Wearable contact force sensor system based on fingerpad deformation,” Proc. of the IEEE World Haptics Conference, pp. 323–328, 2011.

  104. Abboudi, R. L., Glass, C. A., Newby, N. A., Flint, J. A. and Craelius, W., “A biomimetic controller for a multifinger prosthesis,” IEEE Transactions on Rehabilitation Engineering, Vol. 7, No. 2, pp. 121–129, 1999.

    Article  Google Scholar 

  105. Curcie, D. J., Flint, J. A. and Craelius, W., “Biomimetic finger control by filtering of distributed forelimb pressures,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 9, No. 1, pp. 69–75, 2001.

    Article  Google Scholar 

  106. Craelius, W., “The Bionic Man: Restoring Mobility,” Science, Vol. 295, No. 5557, pp. 1018–1021, 2002.

    Article  Google Scholar 

  107. Kuttuva, M., Burdea, G., Flint, J. and Craelius, W., “Manipulation Practice for Upper-Limb Amputees Using Virtual Reality,” Presence: Teleoperators and Virtual Environments, Vol. 14, No. 2, pp. 175–182, 2005.

    Article  Google Scholar 

  108. Phillips, S. L. and Craelius, W., “Residual kinetic imaging: a versatile interface for prosthetic control,” Robotica, Vol. 23, No. 3, pp. 277–282, 2005.

    Article  Google Scholar 

  109. Wininger, M., Kim, N. and Craelius, W., “Pressure signature of the forearm as a predictor of grip force,” Journal of Rehabilitation Research and Development, Vol. 45, No. 6, pp. 883–892, 2008.

    Article  Google Scholar 

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Heo, P., Gu, G.M., Lee, Sj. et al. Current hand exoskeleton technologies for rehabilitation and assistive engineering. Int. J. Precis. Eng. Manuf. 13, 807–824 (2012). https://doi.org/10.1007/s12541-012-0107-2

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  • DOI: https://doi.org/10.1007/s12541-012-0107-2

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