Control of Multifunctional Prosthetic Hands by Processing the Electromyographic Signal.

The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedded in its structure, actuators and tendons, and a complex hierarchical control. Despite this complexity, the efforts required to the user to carry out the different movements is quite small (albeit after an appropriate and lengthy training). On the contrary, prosthetic hands are just a pale replication of the natural hand, with significantly reduced grasping capabilities and no sensory information delivered back to the user. Several attempts have been carried out to develop multifunctional prosthetic devices controlled by electromyographic (EMG) signals (myoelectric hands), harness (kinematic hands), dimensional changes in residual muscles, and so forth, but none of these methods permits the "natural" control of more than two DoFs. This article presents a review of the traditional methods used to control artificial hands by means of EMG signal, in both the clinical and research contexts, and introduces what could be the future developments in the control strategy of these devices.

[1]  R. N. Scott,et al.  A three-state myo-electric control , 1966, Medical and biological engineering.

[2]  R.N. Scott,et al.  A new strategy for multifunction myoelectric control , 1993, IEEE Transactions on Biomedical Engineering.

[3]  G Staude,et al.  Objective motor response onset detection in surface myoelectric signals. , 1999, Medical engineering & physics.

[4]  S. SCHULZ,et al.  A new ultralight anthropomorphic hand , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[5]  M. Alexander,et al.  Principles of Neural Science , 1981 .

[6]  Werner Wolf,et al.  Onset Detection in Surface Electromyographic Signals: A Systematic Comparison of Methods , 2001, EURASIP J. Adv. Signal Process..

[7]  Mark R. Cutkosky,et al.  Robotic grasping and fine manipulation , 1985 .

[8]  Toshio Tsuji,et al.  EMG-based human-robot interface for rehabilitation aid , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[9]  Edward A. Clancy,et al.  Adaptive whitening of the electromyogram to improve amplitude estimation , 2000, IEEE Transactions on Biomedical Engineering.

[10]  Han-Pang Huang,et al.  DSP-based controller for a multi-degree prosthetic hand , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[11]  Teuvo Kohonen,et al.  An introduction to neural computing , 1988, Neural Networks.

[12]  R R Riso,et al.  Strategies for providing upper extremity amputees with tactile and hand position feedback--moving closer to the bionic arm. , 1999, Technology and health care : official journal of the European Society for Engineering and Medicine.

[13]  S Micera,et al.  Improving detection of muscle activation intervals. , 2001, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[14]  Bruce C. Wheeler,et al.  EMG feature evaluation for movement control of upper extremity prostheses , 1995 .

[15]  D S Childress,et al.  Cineplasty as a control input for externally powered prosthetic components. , 2001, Journal of rehabilitation research and development.

[16]  Christian Balkenius,et al.  Neural Control of a Virtual Prosthesis , 1998 .

[17]  Frank Henry Netter,et al.  Anatomy, physiology, and metabolic disorders , 1987 .

[18]  Nikolaos G. Bourbakis,et al.  Neural and fuzzy robotic hand control , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[19]  S Micera,et al.  An algorithm for detecting the onset of muscle contraction by EMG signal processing. , 1998, Medical engineering & physics.

[20]  D Graupe,et al.  Multifunctional prosthesis and orthosis control via microcomputer identification of temporal pattern differences in single-site myoelectric signals. , 1982, Journal of biomedical engineering.

[21]  Metin Akay,et al.  Wavelet applications in medicine , 1997 .

[22]  S Micera,et al.  A two DoF finger for a biomechatronic artificial hand. , 2002, Technology and health care : official journal of the European Society for Engineering and Medicine.

[23]  Ronald R. Coifman,et al.  Entropy-based algorithms for best basis selection , 1992, IEEE Trans. Inf. Theory.

[24]  S Micera,et al.  A hybrid approach to EMG pattern analysis for classification of arm movements using statistical and fuzzy techniques. , 1999, Medical engineering & physics.

[25]  Yoji Umetani,et al.  The Development of Soft Gripper for the Versatile Robot Hand , 1978 .

[26]  Evangelia Micheli-Tzanakou,et al.  Supervised and unsupervised pattern recognition: feature extraction and computational intelligence , 2000 .

[27]  P J Sparto,et al.  Wavelet and short-time Fourier transform analysis of electromyography for detection of back muscle fatigue. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[28]  Maryhelen Stevenson,et al.  Signal representation for classification of the transient myoelectric signal , 1998 .

[29]  Paolo Dario,et al.  Design and development of an underactuated prosthetic hand , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[30]  Toshiyuki Kondo,et al.  Estimation of forearm movement from EMG signal and application to prosthetic hand control , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[31]  S Micera,et al.  On automatic identification of upper-limb movements using small-sized training sets of EMG signals. , 2000, Medical engineering & physics.

[32]  Jun Yu,et al.  Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study , 2000, IEEE Transactions on Biomedical Engineering.

[33]  Matthew T. Mason,et al.  Robot Hands and the Mechanics of Manipulation , 1985 .

[34]  C.I. Christodoulou,et al.  Unsupervised pattern recognition for the classification of EMG signals , 1999, IEEE Transactions on Biomedical Engineering.

[35]  S. Pourmehdi,et al.  An externally powered, multichannel, implantable stimulator-telemeter for control of paralyzed muscle , 1998, IEEE Transactions on Biomedical Engineering.

[36]  K. Englehart,et al.  Classification of the myoelectric signal using time-frequency based representations. , 1999, Medical engineering & physics.

[37]  Wenwei Yu,et al.  EMG prosthetic hand controller discriminating ten motions using real-time learning method , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[38]  P. Agnew Functional effectiveness of a myo-electric prosthesis compared with a functional split-hook prosthesis: A single subject experiment , 1981, Prosthetics and orthotics international.

[39]  Bart Kosko,et al.  Fuzzy Engineering , 1996 .

[40]  D Howard,et al.  Dimensional change in muscle as a control signal for powered upper limb prostheses: a pilot study. , 1999, Medical engineering & physics.

[41]  Hong Liu,et al.  DLR-Hand II: next generation of a dextrous robot hand , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[42]  A Smith,et al.  Hybrid functional electrical stimulation orthosis system for the upper limb: effects on spasticity in chronic stable hemiplegia. , 1998, American journal of physical medicine & rehabilitation.

[43]  Cupo Me,et al.  Clinical evaluation of a new, above-elbow, body-powered prosthetic arm: a final report. , 1998 .

[44]  Shigeo Abe,et al.  A method for fuzzy rules extraction directly from numerical data and its application to pattern classification , 1995, IEEE Trans. Fuzzy Syst..

[45]  George N. Saridis,et al.  EMG Pattern Analysis and Classification for a Prosthetic Arm , 1982, IEEE Transactions on Biomedical Engineering.

[46]  Jelena Kovacevic,et al.  Wavelets and Subband Coding , 2013, Prentice Hall Signal Processing Series.

[47]  R N Scott,et al.  Myoelectric prostheses: state of the art. , 1988, Journal of medical engineering & technology.

[48]  Silvestro Micera,et al.  The development of a novel biomechatronic hand-ongoing research and preliminary results , 2001, 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Proceedings (Cat. No.01TH8556).

[49]  R.N. Scott,et al.  The application of neural networks to myoelectric signal analysis: a preliminary study , 1990, IEEE Transactions on Biomedical Engineering.

[50]  F. K. Lam,et al.  Fuzzy EMG classification for prosthesis control. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[51]  Sushmita Mitra,et al.  Neuro-fuzzy rule generation: survey in soft computing framework , 2000, IEEE Trans. Neural Networks Learn. Syst..

[52]  Daniel Graupe,et al.  Functional Separation of EMG Signals via ARMA Identification Methods for Prosthesis Control Purposes , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[53]  R. H. Meier,et al.  Comprehensive Management of the Upper-Limb Amputee , 1989, Springer New York.

[54]  Peter J. Kyberd,et al.  MARCUS: a two degree of freedom hand prosthesis with hierarchical grip control , 1995 .

[55]  P. Bonato From the guest editor - recent advancements in the analysis of dynamic EMG data , 2001, IEEE Engineering in Medicine and Biology Magazine.

[56]  G A Hunter,et al.  Electrically powered prostheses for the adult with an upper limb amputation. , 1985, The Journal of bone and joint surgery. British volume.

[57]  Thomas H. Speeter Primitive based control of the Utah/MIT dextrous hand , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[58]  Clément Gosselin,et al.  Design Of A Hand Prosthesis Based On Kinematics Principles , 1995 .

[59]  Peter J. Kyberd,et al.  An Intelligent Anthropomorphic Hand, with Automatic Grasp , 1998, Robotica.

[60]  Chris Lovchik,et al.  The Robonaut hand: a dexterous robot hand for space , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[61]  M. Kramer Nonlinear principal component analysis using autoassociative neural networks , 1991 .

[62]  I. Kapandji The Physiology of the Joints , 1988 .

[63]  R.N. Scott,et al.  Myoelectric signal analysis using neural networks , 1990, IEEE Engineering in Medicine and Biology Magazine.

[64]  John M. Miguelez Critical Factors in Electrically Powered Upper-Extremity Prosthetics , 2002 .

[65]  P. Dario,et al.  Neural interfaces for regenerated nerve stimulation and recording. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[66]  R. Johansson,et al.  Properties of cutaneous mechanoreceptors in the human hand related to touch sensation. , 1984, Human neurobiology.

[67]  Silvestro Micera,et al.  A Hybrid Approach for EMG Pattern Analyis for Classification of Arm Movements , 1999 .

[68]  C.S. Pattichis,et al.  Time-scale analysis of motor unit action potentials , 1999, IEEE Transactions on Biomedical Engineering.

[69]  R. Johansson,et al.  Tactile sensibility in the human hand: relative and absolute densities of four types of mechanoreceptive units in glabrous skin. , 1979, The Journal of physiology.

[70]  Euljoon Park,et al.  Adaptive filtering of the electromyographic signal for prosthetic control and force estimation , 1995, IEEE Transactions on Biomedical Engineering.

[71]  F. Netter Atlas of Human Anatomy , 1967 .