The Delsys Prize - Previous Winners
Decoding a new neural-machine interface for control of artificial limbs
Dr.Ping Zhou, Rehabilitation Institute of Chicago, Northwestern University, Chicago, IL, USA.
Summary
A new neural-machine interface, termed targeted muscle reinnervation (TMR), has been developed to improve the function of upper limb prostheses. The control information contained in TMR was assessed. Our results demonstrate that TMR can provide a rich source of motor control information and this information in turn promises to dramatically improve artificial arm function for people with proximal arm amputations.
Click here for further details >>
Probability-Based Prediction Of Electromyographic Activity In Multiple Muscles
Dr. Andrew Fuglivand, Departments of Physiology and Neurobiology, College of Medicine, University of Arizona, Tuscon, AZ, USA.
Summary
A probability-based method is proposed to predict the patterns of electromyographic activity across multiple muscles during a wide range of movements. A reasonable correspondence between predicted and actual EMG signals is demonstrated with this method. Such an approach ultimately might provide a flexible means to control functional electrical stimulation and thereby expand the repertoire of motor functions available to paralyzed individuals.
Click here for further details >>
Discriminating between normal and abnormal EMG profiles in walking
Dr. A.L. Hof, University of Groningen, Center for Human Movement Sciences, Groningen, The Netherlands
Summary:
A method is proposed to predict the normal EMG activity of human walking at any walking speed. The measured profile is compared to the predicted one and the deviation is calculated. In the deviation, temporal differences are taken heavily into account, while differences in amplitude, which are less relevant, are represented in a separate parameter. The method has already been proven useful in clinical research.
Click here for further details >>
Estimation of Proprioceptive Reflex Gains using Surface EMG
Professor Dr. F.C.T van der Helm, Delft University of Technology, Dept. of Mechanical Engineering, Delft, The Netherlands.
Summary:
Robot manipulators are being used to impose force perturbations to the hand. Hand position, hand force and EMG are being recorded. EMG signals are being pre-processed to estimate the dynamic relation to hand force. By optimizing the perturbation signal and using advanced closed loop system identification algorithms, the position, velocity and force feedback originating from the muscle spindles and Golgi tendon organs can be separated. Results were applied to patients with neurological disorders (CVA, Parkinson).
Click here for further details>>
Error Proofing Human Action in a Manufacturing Environment
Kim Sherman, Senior Project Engineer, Sandalwood.Summary
The current proposal is to use electromyography to monitor quality in automotive assembly plants. Providing hardware to monitor human movements throughout a work cycle can be used to ensure critical required work elements have been performed. The benefit of collecting data real-time while the movements are being performed will eliminate the need for non-value added quality checkpoints, additional equipment testing, and ensuring in station process control.
Click here for further details>>
|