Literature DB >> 28113345

Optimized Motor Imagery Paradigm Based on Imagining Chinese Characters Writing Movement.

Zhaoyang Qiu, Brendan Z Allison, Jing Jin, Yu Zhang, Xingyu Wang, Wei Li, Andrzej Cichocki.   

Abstract

BACKGROUND: motor imagery (MI) is a mental representation of motor behavior. The MI-based brain computer interfaces (BCIs) can provide communication for the physically impaired. The performance of MI-based BCI mainly depends on the subject's ability to self-modulate electroencephalogram signals. Proper training can help naive subjects learn to modulate brain activity proficiently. However, training subjects typically involve abstract motor tasks and are time-consuming.
METHODS: to improve the performance of naive subjects during motor imagery, a novel paradigm was presented that would guide naive subjects to modulate brain activity effectively. In this new paradigm, pictures of the left or right hand were used as cues for subjects to finish the motor imagery task. Fourteen healthy subjects (11 male, aged 22-25 years, and mean 23.6±1.16) participated in this study. The task was to imagine writing a Chinese character. Specifically, subjects could imagine hand movements corresponding to the sequence of writing strokes in the Chinese character. This paradigm was meant to find an effective and familiar action for most Chinese people, to provide them with a specific, extensively practiced task and help them modulate brain activity.
RESULTS: results showed that the writing task paradigm yielded significantly better performance than the traditional arrow paradigm (p < 0.001). Questionnaire replies indicated that most subjects thought that the new paradigm was easier.
CONCLUSION: the proposed new motor imagery paradigm could guide subjects to help them modulate brain activity effectively. Results showed that there were significant improvements using new paradigm, both in classification accuracy and usability.

Entities:  

Mesh:

Year:  2017        PMID: 28113345     DOI: 10.1109/TNSRE.2017.2655542

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


  12 in total

1.  Novel hybrid brain-computer interface system based on motor imagery and P300.

Authors:  Cili Zuo; Jing Jin; Erwei Yin; Rami Saab; Yangyang Miao; Xingyu Wang; Dewen Hu; Andrzej Cichocki
Journal:  Cogn Neurodyn       Date:  2019-10-21       Impact factor: 5.082

2.  EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution.

Authors:  Rami Alazrai; Hisham Alwanni; Yara Baslan; Nasim Alnuman; Mohammad I Daoud
Journal:  Sensors (Basel)       Date:  2017-08-23       Impact factor: 3.576

3.  Relevant Feature Integration and Extraction for Single-Trial Motor Imagery Classification.

Authors:  Lili Li; Guanghua Xu; Feng Zhang; Jun Xie; Min Li
Journal:  Front Neurosci       Date:  2017-06-29       Impact factor: 4.677

4.  An Adaptive Calibration Framework for mVEP-Based Brain-Computer Interface.

Authors:  Teng Ma; Fali Li; Peiyang Li; Dezhong Yao; Yangsong Zhang; Peng Xu
Journal:  Comput Math Methods Med       Date:  2018-02-26       Impact factor: 2.238

5.  A Study of the Effects of Electrode Number and Decoding Algorithm on Online EEG-Based BCI Behavioral Performance.

Authors:  Jianjun Meng; Bradley J Edelman; Jaron Olsoe; Gabriel Jacobs; Shuying Zhang; Angeliki Beyko; Bin He
Journal:  Front Neurosci       Date:  2018-04-06       Impact factor: 4.677

6.  Temporal Combination Pattern Optimization Based on Feature Selection Method for Motor Imagery BCIs.

Authors:  Jing Jiang; Chunhui Wang; Jinghan Wu; Wei Qin; Minpeng Xu; Erwei Yin
Journal:  Front Hum Neurosci       Date:  2020-06-30       Impact factor: 3.169

7.  Frequency Specific Cortical Dynamics During Motor Imagery Are Influenced by Prior Physical Activity.

Authors:  Selina C Wriessnegger; Clemens Brunner; Gernot R Müller-Putz
Journal:  Front Psychol       Date:  2018-10-25

8.  Classification of Movement and Inhibition Using a Hybrid BCI.

Authors:  Jennifer Chmura; Joshua Rosing; Steven Collazos; Shikha J Goodwin
Journal:  Front Neurorobot       Date:  2017-08-15       Impact factor: 2.650

9.  The Study of Visual-Auditory Interactions on Lower Limb Motor Imagery.

Authors:  Zhongliang Yu; Lili Li; Jinchun Song; Hangyuan Lv
Journal:  Front Neurosci       Date:  2018-07-24       Impact factor: 4.677

10.  A Secure Occupational Therapy Framework for Monitoring Cancer Patients' Quality of Life.

Authors:  Md Abdur Rahman; Md Mamunur Rashid; Julien Le Kernec; Bruno Philippe; Stuart J Barnes; Francesco Fioranelli; Shufan Yang; Olivier Romain; Qammer H Abbasi; George Loukas; Muhammad Imran
Journal:  Sensors (Basel)       Date:  2019-11-29       Impact factor: 3.576

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