RÉSUMÉ
Currently available prosthetic hands are capable of actuating anywhere from five to 30 degrees of freedom (DOF). However, grasp control of these devices remains unintuitive and cumbersome. To address this issue, we propose directly extracting finger commands from the neuromuscular system via electrodes implanted in residual innervated muscles and regenerative peripheral nerve interfaces (RPNIs). Two persons with transradial amputations had RPNIs created by suturing autologous free muscle grafts to their transected median, ulnar, and dorsal radial sensory nerves. Bipolar electrodes were surgically implanted into their ulnar and median RPNIs and into their residual innervated muscles. The implanted electrodes recorded local electromyography (EMG) with Signal-to-Noise Ratios ranging from 23 to 350 measured across various movements. In a series of single-day experiments, participants used a high speed pattern recognition system to control a virtual prosthetic hand in real-time. Both participants were able to transition between 10 pseudo-randomly cued individual finger and wrist postures in the virtual environment with an average online accuracy of 86.5% and latency of 255 ms. When the set was reduced to five grasp postures, average metrics improved to 97.9% online accuracy and 135 ms latency. Virtual task performance remained stable across untrained static arm positions while supporting the weight of the prosthesis. Participants also used the high speed classifier to switch between robotic prosthetic grips and complete a functional performance assessment. These results demonstrate that pattern recognition systems can use the high-quality EMG afforded by intramuscular electrodes and RPNIs to provide users with fast and accurate grasp control. SUMMARY: Surgically implanted electrodes recorded finger-specific electromyography enabling reliable finger and grasp control of an upper limb prosthesis.
RÉSUMÉ
Spasticity in stroke patients interferes with coordinated muscle firing patterns of the lower extremity leading to gait abnormalities. The goal of this study was to improve ankle function during walking by augmenting treadmill gait retraining with a visual EMG biofeedback technique. Eight stroke patients who could ambulate between 0.5 and 0.9 m/s participated in the study. The training consisted of 12 sessions of treadmill walking during which the activity of the tibialis anterior and gastrocnemius lateralis muscles of the affected side was displayed on a computer screen. Targets were shown to indicate to the subject when to activate the monitored muscles. Gait evaluations were performed before and after the training period to test the hypothesis that ankle mechanics improved following the intervention. Improvements in gait function were characterized by changes in temporal gait parameters and lower extremity kinematics and kinetics. Subjects showed an increase in gait speed, time of single leg support on the affected side, ankle power generation at push-off and a reduction in knee extensor moment. These results indicate that treadmill gait retraining augmented via visual EMG-biofeedback facilitates improvements in hemiparetic gait.
RÉSUMÉ
The aim of this study was to examine the ankle joint during level walking, stair ascent, and stair descent to determine models for use in the design of prosthetic and orthotic systems. Ten healthy subjects were asked to walk (1) across a level walkway, (2) up, and (3) down an instrumented stairway. Sagittal plane kinematic and kinetic data were analyzed to obtain ankle biomechanics during the stance phase of each task. Each stance phase was broken down into sub-phases based on the power trajectory. The ideal model was taken to be the simplest combination of mechanical elements (springs, dampers, and torque actuators) that could reproduce the patterns observed in ankle biomechanics. Besides, we studied the transitions from level walking to stair ascent and from stair descent to level walking and showed that mechanical elements can be used to model these transitions as well. These results are promising to the design of next generation ankle orthotic and prosthetic systems because they show that relatively simple mechanical elements can be utilized to mimic ankle biomechanics.