Results 101 to 110 of about 4,837 (154)

Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted Features. [PDF]

open access: yesFront Bioeng Biotechnol, 2020
Côté-Allard U   +5 more
europepmc   +1 more source
Some of the next articles are maybe not open access.

Related searches:

Myoelectric control systems—A survey

Biomedical Signal Processing and Control, 2007
Abstract The development of an advanced human–machine interface has always been an interesting research topic in the field of rehabilitation, in which biomedical signals, such as myoelectric signals, have a key role to play. Myoelectric control is an advanced technique concerned with the detection, processing, classification, and application of ...
Huosheng Hu   +1 more
exaly   +2 more sources

Myoelectric Control in Neurorehabilitation

Critical Reviews in Biomedical Engineering, 2010
A myoelectric signal, or electromyogram (EMG), is the electrical manifestation of a muscle contraction. Through advanced signal processing techniques, information on the neural control of muscles can be extracted from the EMG, and the state of the neuromuscular system can be inferred.
Jiang, Ning   +4 more
openaire   +3 more sources

Artificial proprioception for myoelectric control

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013
The typical control of myoelectric interfaces, be it in real-life prosthetic applications or laboratory settings, largely relies on visual feedback, while proprioceptive feedback from controlling muscles is not very informative about the task carried out.
Tobias Pistohl   +4 more
openaire   +2 more sources

Myoelectric Controlled Thumb

2018 3rd International Conference for Convergence in Technology (I2CT), 2018
Our human fingers are provided specific roles which finally results into various hand motions and functions. The thumb plays a special role because it takes part in several activities. So, a thumb loss because of traumatic accidents or other reasons can prove terrible because appropriate functions of the hand will get sternly restricted.
Yash Patel, Sharmila Nageswaran
openaire   +1 more source

Spatial Filtering for Robust Myoelectric Control

IEEE Transactions on Biomedical Engineering, 2012
Pattern recognition techniques have been applied to extract information from electromyographic (EMG) signals that can be used to control electrical powered hand prostheses. In this paper, optimized spatial filters that enhance separation properties of EMG signals are investigated.
Janne Mathias Hahne   +2 more
openaire   +2 more sources

Home - About - Disclaimer - Privacy