Literature DB >> 34607318

Decoding four hand gestures with a single bipolar pair of electrocorticography electrodes.

Maxime Verwoert1, Mariska J Vansteensel1, Zachary V Freudenburg1, Erik J Aarnoutse1, Frans S S Leijten1, Nick F Ramsey1, Mariana P Branco1.   

Abstract

Objective.Electrocorticography (ECoG) based brain-computer interfaces (BCIs) can be used to restore communication in individuals with locked-in syndrome. In motor-based BCIs, the number of degrees-of-freedom, and thus the speed of the BCI, directly depends on the number of classes that can be discriminated from the neural activity in the sensorimotor cortex. When considering minimally invasive BCI implants, the size of the subdural ECoG implant must be minimized without compromising the number of degrees-of-freedom.Approach.Here we investigated if four hand gestures could be decoded using a single ECoG strip of four consecutive electrodes spaced 1 cm apart and compared the performance between a unipolar and a bipolar montage. For that we collected data of seven individuals with intractable epilepsy implanted with ECoG grids, covering the hand region of the sensorimotor cortex. Based on the implanted grids, we generated virtual ECoG strips and compared the decoding accuracy between (a) a single unipolar electrode (Unipolar Electrode), (b) a combination of four unipolar electrodes (Unipolar Strip), (c) a single bipolar pair (Bipolar Pair) and (d) a combination of six bipolar pairs (Bipolar Strip).Main results.We show that four hand gestures can be equally well decoded using 'Unipolar Strips' (mean 67.4 ± 11.7%), 'Bipolar Strips' (mean 66.6 ± 12.1%) and 'Bipolar Pairs' (mean 67.6 ± 9.4%), while 'Unipolar Electrodes' (61.6 ± 5.9%) performed significantly worse compared to 'Unipolar Strips' and 'Bipolar Pairs'.Significance.We conclude that a single bipolar pair is a potential candidate for minimally invasive motor-based BCIs and encourage the use of ECoG as a robust and reliable BCI platform for multi-class movement decoding.
© 2021 IOP Publishing Ltd.

Entities:  

Keywords:  bipolar; brain–computer interface; electrocorticography; minimally invasive; sign language; unipolar

Mesh:

Year:  2021        PMID: 34607318      PMCID: PMC8744490          DOI: 10.1088/1741-2552/ac2c9f

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.043


  41 in total

1.  Automated electrocorticographic electrode localization on individually rendered brain surfaces.

Authors:  Dora Hermes; Kai J Miller; Herke Jan Noordmans; Mariska J Vansteensel; Nick F Ramsey
Journal:  J Neurosci Methods       Date:  2009-10-27       Impact factor: 2.390

2.  Exceeding chance level by chance: The caveat of theoretical chance levels in brain signal classification and statistical assessment of decoding accuracy.

Authors:  Etienne Combrisson; Karim Jerbi
Journal:  J Neurosci Methods       Date:  2015-01-14       Impact factor: 2.390

3.  Electrocorticographic control of a prosthetic arm in paralyzed patients.

Authors:  Takufumi Yanagisawa; Masayuki Hirata; Youichi Saitoh; Haruhiko Kishima; Kojiro Matsushita; Tetsu Goto; Ryohei Fukuma; Hiroshi Yokoi; Yukiyasu Kamitani; Toshiki Yoshimine
Journal:  Ann Neurol       Date:  2011-11-02       Impact factor: 10.422

4.  Complications of epilepsy surgery after 654 procedures in Sweden, September 1990-1995: a multicenter study based on the Swedish National Epilepsy Surgery Register.

Authors:  B Rydenhag; H C Silander
Journal:  Neurosurgery       Date:  2001-07       Impact factor: 4.654

5.  The influence of psychological state and motivation on brain-computer interface performance in patients with amyotrophic lateral sclerosis - a longitudinal study.

Authors:  Femke Nijboer; Niels Birbaumer; Andrea Kübler
Journal:  Front Neurosci       Date:  2010-07-21       Impact factor: 4.677

6.  Decoding spoken phonemes from sensorimotor cortex with high-density ECoG grids.

Authors:  N F Ramsey; E Salari; E J Aarnoutse; M J Vansteensel; M G Bleichner; Z V Freudenburg
Journal:  Neuroimage       Date:  2017-10-07       Impact factor: 6.556

7.  ALICE: A tool for automatic localization of intra-cranial electrodes for clinical and high-density grids.

Authors:  Mariana P Branco; Anna Gaglianese; Daniel R Glen; Dora Hermes; Ziad S Saad; Natalia Petridou; Nick F Ramsey
Journal:  J Neurosci Methods       Date:  2017-11-01       Impact factor: 2.390

8.  FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data.

Authors:  Robert Oostenveld; Pascal Fries; Eric Maris; Jan-Mathijs Schoffelen
Journal:  Comput Intell Neurosci       Date:  2010-12-23

9.  Classification of Articulator Movements and Movement Direction from Sensorimotor Cortex Activity.

Authors:  E Salari; Z V Freudenburg; M P Branco; E J Aarnoutse; M J Vansteensel; N F Ramsey
Journal:  Sci Rep       Date:  2019-10-02       Impact factor: 4.379

10.  Epidural electrocorticography of phantom hand movement following long-term upper-limb amputation.

Authors:  Alireza Gharabaghi; Georgios Naros; Armin Walter; Alexander Roth; Martin Bogdan; Wolfgang Rosenstiel; Carsten Mehring; Niels Birbaumer
Journal:  Front Hum Neurosci       Date:  2014-05-06       Impact factor: 3.169

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