Abstract and Proportional Myoelectric Control for Multi-Fingered Hand Prostheses

Powered hand prostheses with many degrees of freedom are moving from research into the market for prosthetics. In order to make use of the prostheses’ full functionality, it is essential to study efficient ways of high dimensional myoelectric control. Human subjects can rapidly learn to employ electromyographic (EMG) activity of several hand and arm muscles to control the position of a cursor on a computer screen, even if the muscle-cursor map contradicts directions in which the muscles would act naturally. But can a similar control scheme be translated into real-time operation of a dexterous robotic hand? We found that despite different degrees of freedom in the effector output, the learning process for controlling a robotic hand was surprisingly similar to that for a virtual two-dimensional cursor. Control signals were derived from the EMG in two different ways, with a linear and a Bayesian filter, to test how stable user intentions could be conveyed through them. Our analysis indicates that without visual feedback, control accuracy benefits from filters that reject high EMG amplitudes. In summary, we conclude that findings on myoelectric control principles, studied in abstract, virtual tasks can be transferred to real-life prosthetic applications.

[1]  Martha Flanders,et al.  Coordination of Hand Shape , 2011, The Journal of Neuroscience.

[2]  S. Vijayakumar,et al.  The role of feed-forward and feedback processes for closed-loop prosthesis control , 2011, Journal of NeuroEngineering and Rehabilitation.

[3]  Philip R. Troyk,et al.  Implantable Myoelectric Sensors (IMESs) for Intramuscular Electromyogram Recording , 2009, IEEE Transactions on Biomedical Engineering.

[4]  Todd A Kuiken,et al.  Target Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses. , 2011, Journal of rehabilitation research and development.

[5]  Robert D. Lipschutz,et al.  Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. , 2009, JAMA.

[6]  T. Kuiken,et al.  Quantifying Pattern Recognition—Based Myoelectric Control of Multifunctional Transradial Prostheses , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[7]  J. Tukey,et al.  Variations of Box Plots , 1978 .

[8]  Christian Cipriani,et al.  Real-time myoelectric control of a multi-fingered hand prosthesis using principal components analysis , 2012, Journal of NeuroEngineering and Rehabilitation.

[9]  Christian Cipriani,et al.  Principal components analysis based control of a multi-dof underactuated prosthetic hand , 2010, Journal of NeuroEngineering and Rehabilitation.

[10]  Stephanie Westendorff,et al.  Acquisition of myoelectric signals to control a hand prosthesis with implantable epimysial electrodes , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[11]  Christian Cipriani,et al.  The SmartHand transradial prosthesis , 2011, Journal of NeuroEngineering and Rehabilitation.

[12]  T. Kuiken,et al.  Improved Myoelectric Prosthesis Control Using Targeted Reinnervation Surgery: A Case Series , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[13]  Robert D. Lipschutz,et al.  Targeted reinnervation for enhanced prosthetic arm function in a woman with a proximal amputation: a case study , 2007, The Lancet.

[14]  Terence D Sanger,et al.  Bayesian filtering of myoelectric signals. , 2007, Journal of neurophysiology.

[15]  Andrew Jackson,et al.  Learning a Novel Myoelectric-Controlled Interface Task , 2008, Journal of neurophysiology.

[16]  Ahmad R. Sharafat,et al.  Application of Higher Order Statistics to Surface Electromyogram Signal Classification , 2007, IEEE Transactions on Biomedical Engineering.

[17]  Marc H Schieber,et al.  Hand function: peripheral and central constraints on performance. , 2004, Journal of applied physiology.

[18]  A. Jackson,et al.  Flexible Cortical Control of Task-Specific Muscle Synergies , 2012, The Journal of Neuroscience.

[19]  Huosheng Hu,et al.  Myoelectric control systems - A survey , 2007, Biomed. Signal Process. Control..