A closed-loop drop-foot correction system with gait event detection from the contralateral lower limb using fuzzy logic

In the present paper a closed loop fuzzy control scheme for the correction of the drop-foot syndrome is presented. The control scheme is based on EMG signals from the contralateral, unimpaired lower limb and its efficiency is tested by the application of the controller to a simulated bipedal locomotion with one lower limb suffering from the Drop-Foot Syndrome. Two are the major characteristics of the controller: identification of the phase where the stimulation must be provided using EMG signals from the contralateral, unimpaired lower limb and correction of the excitation signal according to the phase using EMG signals from the collateral impaired lower limb.

[1]  Brian T. Smith,et al.  Application of a neuro-fuzzy network for gait event detection using electromyography in the child with Cerebral palsy , 2005, IEEE Transactions on Biomedical Engineering.

[2]  Liberson Wt,et al.  Functional electrotherapy: stimulation of the peroneal nerve synchronized with the swing phase of the gait of hemiplegic patients. , 1961, Archives of physical medicine and rehabilitation.

[3]  F.E. Zajac,et al.  An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures , 1990, IEEE Transactions on Biomedical Engineering.

[4]  T Laurell,et al.  Myoelectric control of a computer animated hand: A new concept based on the combined use of a tree-structured artificial neural network and a data glove , 2006, Journal of medical engineering & technology.

[5]  Brian T. Smith,et al.  Feasibility of Gait Event Detection Using Intramuscular Electromyography in the Child with Cerebral Palsy , 2004, Neuromodulation : journal of the International Neuromodulation Society.

[6]  Nikolaos Aspragathos,et al.  A study of human locomotion for the design of rehabilitation systems based on fuzzy logic , 2006 .

[7]  R.Fff. Weir,et al.  A heuristic fuzzy logic approach to EMG pattern recognition for multifunctional prosthesis control , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[8]  Alfred D. Grant.  Gait Analysis: Normal and Pathological Function , 2010 .

[9]  Dario Farina,et al.  Simultaneous and Proportional Force Estimation for Multifunction Myoelectric Prostheses Using Mirrored Bilateral Training , 2011, IEEE Transactions on Biomedical Engineering.

[10]  Yoky Matsuoka,et al.  Comparison of control strategies for an EMG controlled orthotic exoskeleton for the hand , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[11]  V. C. Moulianitis,et al.  An approach for the development of a fuzzy logic controller for the correction of the drop-foot syndrome , 2006 .

[12]  F. Zajac.  Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. , 1989, Critical reviews in biomedical engineering.