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Electromyography

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Recurrence quantification analysis and support vector machines for golf handicap and low back pain EMG classification.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
The quantification of non-linear characteristics of electromyography (EMG) must contain information allowing to discriminate neuromuscular strategies during dynamic skills. There are a lack of studies about muscle coordination under motor constrains ...

High-Density Electromyography and Motor Skill Learning for Robust Long-Term Control of a 7-DoF Robot Arm.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Myoelectric control offers a direct interface between human intent and various robotic applications through recorded muscle activity. Traditional control schemes realize this interface through direct mapping or pattern recognition techniques. The for...

An EMG-Controlled Robotic Hand Exoskeleton for Bilateral Rehabilitation.

IEEE transactions on haptics
This paper presents a novel electromyography (EMG)-driven hand exoskeleton for bilateral rehabilitation of grasping in stroke. The developed hand exoskeleton was designed with two distinctive features: (a) kinematics with intrinsic adaptability to pa...

Adaptive myoelectric pattern recognition toward improved multifunctional prosthesis control.

Medical engineering & physics
The non-stationary property of electromyography (EMG) signals in real life settings usually hinders the clinical application of the myoelectric pattern recognition for prosthesis control. The classical EMG pattern recognition approach consists of two...

The influence of push-off timing in a robotic ankle-foot prosthesis on the energetics and mechanics of walking.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robotic ankle-foot prostheses that provide net positive push-off work can reduce the metabolic rate of walking for individuals with amputation, but benefits might be sensitive to push-off timing. Simple walking models suggest that preempt...

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.

Journal of neuroscience methods
BACKGROUND: Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are prom...

Neural network pattern recognition of lingual-palatal pressure for automated detection of swallow.

Dysphagia
We describe a novel device and method for real-time measurement of lingual-palatal pressure and automatic identification of the oral transfer phase of deglutition. Clinical measurement of the oral transport phase of swallowing is a complicated proces...

A comparative study of surface EMG classification by fuzzy relevance vector machine and fuzzy support vector machine.

Physiological measurement
We present a multiclass fuzzy relevance vector machine (FRVM) learning mechanism and evaluate its performance to classify multiple hand motions using surface electromyographic (sEMG) signals. The relevance vector machine (RVM) is a sparse Bayesian ke...

Decomposition of surface EMG signals from cyclic dynamic contractions.

Journal of neurophysiology
Over the past 3 decades, various algorithms used to decompose the electromyographic (EMG) signal into its constituent motor unit action potentials (MUAPs) have been reported. All are limited to decomposing EMG signals from isometric contraction. In t...