Literature DB >> 19700814

Evaluation of a modified Fitts law brain-computer interface target acquisition task in able and motor disabled individuals.

E A Felton1, R G Radwin, J A Wilson, J C Williams.   

Abstract

A brain-computer interface (BCI) is a communication system that takes recorded brain signals and translates them into real-time actions, in this case movement of a cursor on a computer screen. This work applied Fitts' law to the evaluation of performance on a target acquisition task during sensorimotor rhythm-based BCI training. Fitts' law, which has been used as a predictor of movement time in studies of human movement, was used here to determine the information transfer rate, which was based on target acquisition time and target difficulty. The information transfer rate was used to make comparisons between control modalities and subject groups on the same task. Data were analyzed from eight able-bodied and five motor disabled participants who wore an electrode cap that recorded and translated their electroencephalogram (EEG) signals into computer cursor movements. Direct comparisons were made between able-bodied and disabled subjects, and between EEG and joystick cursor control in able-bodied subjects. Fitts' law aptly described the relationship between movement time and index of difficulty for each task movement direction when evaluated separately and averaged together. This study showed that Fitts' law can be successfully applied to computer cursor movement controlled by neural signals.

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Year:  2009        PMID: 19700814      PMCID: PMC4075430          DOI: 10.1088/1741-2560/6/5/056002

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  28 in total

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Journal:  J Neurophysiol       Date:  1992-05       Impact factor: 2.714

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Journal:  Behav Brain Res       Date:  1996-05       Impact factor: 3.332

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Authors:  Marcel Mutsaarts; Bert Steenbergen; Harold Bekkering
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10.  Electrocorticographically controlled brain-computer interfaces using motor and sensory imagery in patients with temporary subdural electrode implants. Report of four cases.

Authors:  Elizabeth A Felton; J Adam Wilson; Justin C Williams; P Charles Garell
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  18 in total

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Authors:  Sung-Phil Kim; John D Simeral; Leigh R Hochberg; John P Donoghue; Gerhard M Friehs; Michael J Black
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Review 2.  The body-machine interface: a new perspective on an old theme.

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4.  Upper Body-Based Power Wheelchair Control Interface for Individuals With Tetraplegia.

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Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2015-06-01       Impact factor: 3.802

Review 5.  Challenges and opportunities for next-generation intracortically based neural prostheses.

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6.  Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array.

Authors:  J D Simeral; S-P Kim; M J Black; J P Donoghue; L R Hochberg
Journal:  J Neural Eng       Date:  2011-03-24       Impact factor: 5.379

7.  Real-time two-dimensional asynchronous control of a computer cursor with a single subdural electrode.

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8.  Long term, stable brain machine interface performance using local field potentials and multiunit spikes.

Authors:  Robert D Flint; Zachary A Wright; Michael R Scheid; Marc W Slutzky
Journal:  J Neural Eng       Date:  2013-08-05       Impact factor: 5.379

9.  Mental workload during brain-computer interface training.

Authors:  Elizabeth A Felton; Justin C Williams; Gregg C Vanderheiden; Robert G Radwin
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Review 10.  Closed-loop brain-machine-body interfaces for noninvasive rehabilitation of movement disorders.

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Journal:  Ann Biomed Eng       Date:  2014-05-15       Impact factor: 3.934

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