Literature DB >> 24838070

Performance measurement for brain-computer or brain-machine interfaces: a tutorial.

David E Thompson1, Lucia R Quitadamo, Luca Mainardi, Khalil Ur Rehman Laghari, Shangkai Gao, Pieter-Jan Kindermans, John D Simeral, Reza Fazel-Rezai, Matteo Matteucci, Tiago H Falk, Luigi Bianchi, Cynthia A Chestek, Jane E Huggins.   

Abstract

OBJECTIVE: Brain-computer interfaces (BCIs) have the potential to be valuable clinical tools. However, the varied nature of BCIs, combined with the large number of laboratories participating in BCI research, makes uniform performance reporting difficult. To address this situation, we present a tutorial on performance measurement in BCI research. APPROACH: A workshop on this topic was held at the 2013 International BCI Meeting at Asilomar Conference Center in Pacific Grove, California. This paper contains the consensus opinion of the workshop members, refined through discussion in the following months and the input of authors who were unable to attend the workshop. MAIN
RESULTS: Checklists for methods reporting were developed for both discrete and continuous BCIs. Relevant metrics are reviewed for different types of BCI research, with notes on their use to encourage uniform application between laboratories. SIGNIFICANCE: Graduate students and other researchers new to BCI research may find this tutorial a helpful introduction to performance measurement in the field.

Entities:  

Mesh:

Year:  2014        PMID: 24838070      PMCID: PMC4185283          DOI: 10.1088/1741-2560/11/3/035001

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


  52 in total

Review 1.  Brain-computer interfaces for communication and control.

Authors:  Jonathan R Wolpaw; Niels Birbaumer; Dennis J McFarland; Gert Pfurtscheller; Theresa M Vaughan
Journal:  Clin Neurophysiol       Date:  2002-06       Impact factor: 3.708

2.  Predictive spelling with a P300-based brain-computer interface: Increasing the rate of communication.

Authors:  D B Ryan; G E Frye; G Townsend; D R Berry; S Mesa-G; N A Gates; E W Sellers
Journal:  Int J Hum Comput Interact       Date:  2011-01-01       Impact factor: 3.353

3.  Towards a system-paced near-infrared spectroscopy brain-computer interface: differentiating prefrontal activity due to mental arithmetic and mental singing from the no-control state.

Authors:  Sarah D Power; Azadeh Kushki; Tom Chau
Journal:  J Neural Eng       Date:  2011-10-06       Impact factor: 5.379

4.  Toward using confidence intervals to compare correlations.

Authors:  Guang Yong Zou
Journal:  Psychol Methods       Date:  2007-12

5.  A unified probabilistic approach to improve spelling in an event-related potential-based brain-computer interface.

Authors:  Pieter-Jan Kindermans; Hannes Verschore; Benjamin Schrauwen
Journal:  IEEE Trans Biomed Eng       Date:  2013-05-13       Impact factor: 4.538

6.  A closed-loop human simulator for investigating the role of feedback control in brain-machine interfaces.

Authors:  John P Cunningham; Paul Nuyujukian; Vikash Gilja; Cindy A Chestek; Stephen I Ryu; Krishna V Shenoy
Journal:  J Neurophysiol       Date:  2010-10-13       Impact factor: 2.714

7.  Using the electrocorticographic speech network to control a brain-computer interface in humans.

Authors:  Eric C Leuthardt; Charles Gaona; Mohit Sharma; Nicholas Szrama; Jarod Roland; Zac Freudenberg; Jamie Solis; Jonathan Breshears; Gerwin Schalk
Journal:  J Neural Eng       Date:  2011-04-07       Impact factor: 5.379

8.  (C)overt attention and visual speller design in an ERP-based brain-computer interface.

Authors:  Matthias S Treder; Benjamin Blankertz
Journal:  Behav Brain Funct       Date:  2010-05-28       Impact factor: 3.759

9.  Reach and grasp by people with tetraplegia using a neurally controlled robotic arm.

Authors:  Leigh R Hochberg; Daniel Bacher; Beata Jarosiewicz; Nicolas Y Masse; John D Simeral; Joern Vogel; Sami Haddadin; Jie Liu; Sydney S Cash; Patrick van der Smagt; John P Donoghue
Journal:  Nature       Date:  2012-05-16       Impact factor: 49.962

10.  Continuous three-dimensional control of a virtual helicopter using a motor imagery based brain-computer interface.

Authors:  Alexander J Doud; John P Lucas; Marc T Pisansky; Bin He
Journal:  PLoS One       Date:  2011-10-26       Impact factor: 3.240

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  18 in total

1.  A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain-machine interfaces.

Authors:  Samuel R Nason; Alex K Vaskov; Matthew S Willsey; Elissa J Welle; Hyochan An; Philip P Vu; Autumn J Bullard; Chrono S Nu; Jonathan C Kao; Krishna V Shenoy; Taekwang Jang; Hun-Seok Kim; David Blaauw; Parag G Patil; Cynthia A Chestek
Journal:  Nat Biomed Eng       Date:  2020-07-27       Impact factor: 25.671

Review 2.  Review: Human Intracortical Recording and Neural Decoding for Brain-Computer Interfaces.

Authors:  David M Brandman; Sydney S Cash; Leigh R Hochberg
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2017-03-02       Impact factor: 3.802

3.  Initial constructs for patient-centered outcome measures to evaluate brain-computer interfaces.

Authors:  Elena M Andresen; Melanie Fried-Oken; Betts Peters; Donald L Patrick
Journal:  Disabil Rehabil Assist Technol       Date:  2015-03-25

4.  Brain-computer interface control along instructed paths.

Authors:  P T Sadtler; S I Ryu; E C Tyler-Kabara; B M Yu; A P Batista
Journal:  J Neural Eng       Date:  2015-01-21       Impact factor: 5.379

5.  Automated Artifact Rejection Algorithms Harm P3 Speller Brain-Computer Interface Performance.

Authors:  David E Thompson; Md Rakibul Mowla; Katie J Dhuyvetter; Joseph W Tillman; Jane E Huggins
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2020-03-02

6.  Neural control of finger movement via intracortical brain-machine interface.

Authors:  Z T Irwin; K E Schroeder; P P Vu; A J Bullard; D M Tat; C S Nu; A Vaskov; S R Nason; D E Thompson; J N Bentley; P G Patil; C A Chestek
Journal:  J Neural Eng       Date:  2017-12       Impact factor: 5.379

7.  Enhancing P300-BCI performance using latency estimation.

Authors:  Md Rakibul Mowla; Jane E Huggins; David E Thompson
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2017-06-28

8.  Identifying Engineering, Clinical and Patient's Metrics for Evaluating and Quantifying Performance of Brain-Machine Interface (BMI) Systems.

Authors:  Jose L Contreras-Vidal
Journal:  Conf Proc IEEE Int Conf Syst Man Cybern       Date:  2014-10-05

9.  Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface.

Authors:  Beata Jarosiewicz; Anish A Sarma; Daniel Bacher; Nicolas Y Masse; John D Simeral; Brittany Sorice; Erin M Oakley; Christine Blabe; Chethan Pandarinath; Vikash Gilja; Sydney S Cash; Emad N Eskandar; Gerhard Friehs; Jaimie M Henderson; Krishna V Shenoy; John P Donoghue; Leigh R Hochberg
Journal:  Sci Transl Med       Date:  2015-11-11       Impact factor: 17.956

10.  Implementation of an Embedded Web Server Application for Wireless Control of Brain Computer Interface Based Home Environments.

Authors:  Eda Akman Aydın; Ömer Faruk Bay; İnan Güler
Journal:  J Med Syst       Date:  2015-11-07       Impact factor: 4.460

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