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Electromyography

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A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots.

Computers in biology and medicine
A patient-specific electromyography (EMG)-driven neuromuscular model (PENm) is developed for the potential use of human-inspired gait rehabilitation robots. The PENm is modified based on the current EMG-driven models by decreasing the calculation tim...

Running With an Elastic Lower Limb Exoskeleton.

Journal of applied biomechanics
Although there have been many lower limb robotic exoskeletons that have been tested for human walking, few devices have been tested for assisting running. It is possible that a pseudo-passive elastic exoskeleton could benefit human running without th...

Can shoulder joint reaction forces be estimated by neural networks?

Journal of biomechanics
To facilitate the development of future shoulder endoprostheses, a long term load profile of the shoulder joint is desired. A musculoskeletal model using 3D kinematics and external forces as input can estimate the mechanical load on the glenohumeral ...

Non-Invasive, Temporally Discrete Feedback of Object Contact and Release Improves Grasp Control of Closed-Loop Myoelectric Transradial Prostheses.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Human grasping and manipulation control critically depends on tactile feedback. Without this feedback, the ability for fine control of a prosthesis is limited in upper limb amputees. Although various approaches have been investigated in the past, at ...

Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robotic ankle exoskeletons can provide assistance to users and reduce metabolic power during walking. Our research group has investigated the use of proportional myoelectric control for controlling robotic ankle exoskeletons. Previously, ...

A Spiking Neural Network in sEMG Feature Extraction.

Sensors (Basel, Switzerland)
We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demo...

Pain Intensity Recognition Rates via Biopotential Feature Patterns with Support Vector Machines.

PloS one
BACKGROUND: The clinically used methods of pain diagnosis do not allow for objective and robust measurement, and physicians must rely on the patient's report on the pain sensation. Verbal scales, visual analog scales (VAS) or numeric rating scales (N...

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

Prosthetics and orthotics international
BACKGROUND: Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operatin...

Robustness and Reliability of Synergy-Based Myocontrol of a Multiple Degree of Freedom Robotic Arm.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In this study, we test the feasibility of the synergy- based approach for application in the realistic and clinically oriented framework of multi-degree of freedom (DOF) robotic control. We developed and tested online ten able-bodied subjects in a se...