Literature DB >> 20064765

Discreet discrete commands for assistive and neuroprosthetic devices.

Stephen T Foldes1, Dawn M Taylor.   

Abstract

Many new assistive devices are available for individuals paralyzed below the neck due to spinal cord injury. Severely paralyzed individuals must be able to command their complex assistive devices using remaining activity from the neck up. Electromyographic (EMG) sensors enable people to use contractions of head and neck muscles to generate multiple proportional command signals. Electroencephalographic (EEG) signals can also be used to generate commands for assistive device control by conveying information about imagined or attempted movements. Fully-implanted wireless biopotential detection systems are now being developed to reliably detect EMGs, EEGs, or a mixture of the two from recording electrodes implanted just under the skin or scalp thus eliminating the need for externally worn hardware on the head or face. This present study shows how novel patterns of jaw muscle contractions, detected via biopotential sensors on the scalp surface or implanted just under the scalp, can be used to generate reliable discrete EMG commands, which can be differentiated from patterns generated during normal activities, such as chewing. These jaw contractions can be detected with sensors already in place to detect other muscle- or brain-based command signals thus adding to the functionality of current device control systems.

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Year:  2009        PMID: 20064765     DOI: 10.1109/TNSRE.2009.2033428

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  4 in total

Review 1.  Neuroprosthetic technology for individuals with spinal cord injury.

Authors:  Jennifer L Collinger; Stephen Foldes; Tim M Bruns; Brian Wodlinger; Robert Gaunt; Douglas J Weber
Journal:  J Spinal Cord Med       Date:  2013-07       Impact factor: 1.985

2.  Steering a tractor by means of an EMG-based human-machine interface.

Authors:  Jaime Gomez-Gil; Israel San-Jose-Gonzalez; Luis Fernando Nicolas-Alonso; Sergio Alonso-Garcia
Journal:  Sensors (Basel)       Date:  2011-07-11       Impact factor: 3.576

3.  Speaking and cognitive distractions during EEG-based brain control of a virtual neuroprosthesis-arm.

Authors:  Stephen T Foldes; Dawn M Taylor
Journal:  J Neuroeng Rehabil       Date:  2013-12-21       Impact factor: 4.262

Review 4.  Hybrid Brain-Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review.

Authors:  Keum-Shik Hong; Muhammad Jawad Khan
Journal:  Front Neurorobot       Date:  2017-07-24       Impact factor: 2.650

  4 in total

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