Brain-computer interface based on detection of movement intention as a means of brain wave modulation enhancement

被引:0
作者
Pulido Castro, Sergio D. [1 ,2 ]
Lopez Lopez, Juan M. [1 ]
机构
[1] Escuela Colombiana Ingn Julio Garavito, Biomed Engn Program, Ave Carrera 45 N 205-59, Bogota 111166000, Colombia
[2] Univ Rosario, Biomed Engn Program, Carrera 24 63C-69, Bogota 111221, Colombia
来源
13TH INTERNATIONAL CONFERENCE ON MEDICAL INFORMATION PROCESSING AND ANALYSIS | 2017年 / 10572卷
关键词
Movement intention; brain-computer interface; brain wave modulation; SINGLE-TRIAL DETECTION; MOTOR IMAGERY; EEG; BCI;
D O I
10.1117/12.2285960
中图分类号
R-058 [];
学科分类号
摘要
Movement intention (MI) is the mental state in which it is desired to make an action that implies movement. There are certain signals that are directly related with MI; mainly obtained in the primary motor cortex. These signals can be used in a brain-computer interface (BCI). BCIs have a wide variety of applications for the general population, classified in two groups: optimization of conventional neuromuscular performances and enhancement of conventional neuromuscular performances beyond normal capacities. The main goal of this project is to analyze if neural rhythm modulation enhancement could be achieved by practicing, through a BCI based on MI detection, which was designed in a previous study. A six-session experiment was made with eight healthy subjects. Each session was composed by two stages: a training stage and a testing stage, which allowed control of a videogame. The scores in the game were recorded and analyzed. Changes in alpha and beta bands were also analyzed in order to observe if attention could in fact be enhanced. The obtained results were partially satisfactory, as most subjects showed a clear improvement in performance at some point in the trials. As well, the alpha to beta wave ratio of all the tasks was analyzed to observe if there are changes as the experiment progresses. The results are promising, and a different protocol must be implemented to assess the impact of the BCI on the attention span, which can be analyzed with the alpha and beta waves.
引用
收藏
页数:10
相关论文
共 29 条
[1]   EEG-Based Strategies to Detect Motor Imagery for Control and Rehabilitation [J].
Ang, Kai Keng ;
Guan, Cuntai .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2017, 25 (04) :392-401
[2]   Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG [J].
Bai, Ou ;
Lin, Peter ;
Vorbach, Sherry ;
Li, Jiang ;
Furlani, Steve ;
Hallett, Mark .
CLINICAL NEUROPHYSIOLOGY, 2007, 118 (12) :2637-2655
[3]   Two Brains, One Game: Design and Evaluation of a Multiuser BCI Video Game Based on Motor Imagery [J].
Bonnet, Laurent ;
Lotte, Fabien ;
Lecuyer, Anatole .
IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, 2013, 5 (02) :185-198
[4]   Identification of movement-related cortical potentials with optimized spatial filtering and principal component analysis [J].
Boye, Andreas Trollund ;
Kristiansen, Ulrik Qvist ;
Billinger, Martin ;
do Nascimento, Omar Feix ;
Farina, Dario .
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2008, 3 (04) :300-304
[5]   Attention enhancement system using virtual reality and EEG biofeedback [J].
Cho, BH ;
Lee, JM ;
Ku, JH ;
Jang, DP ;
Kim, JS ;
Kim, IY ;
Lee, JH ;
Kim, SI .
IEEE VIRTUAL REALITY 2002, PROCEEDINGS, 2002, :156-163
[6]   A P300-based Brain-Computer Interface with Stimuli on Moving Objects: Four-Session Single-Trial and Triple-Trial Tests with a Game-Like Task Design [J].
Ganin, Ilya P. ;
Shishkin, Sergei L. ;
Kaplan, Alexander Y. .
PLOS ONE, 2013, 8 (10)
[7]  
Hamid NHA, 2015, 2015 IEEE 6TH CONTROL AND SYSTEM GRADUATE RESEARCH COLLOQUIUM (ICSGRC), P135, DOI 10.1109/ICSGRC.2015.7412480
[8]   A brain-computer interface for single-trial detection of gait initiation from movement related cortical potentials [J].
Jiang, Ning ;
Gizzi, Leonardo ;
Mrachacz-Kersting, Natalie ;
Dremstrup, Kim ;
Farina, Dario .
CLINICAL NEUROPHYSIOLOGY, 2015, 126 (01) :154-159
[9]  
Joachims T., 2013, LEARNING CLASSIFY TE, P35
[10]   Detection and classification of movement-related cortical potentials associated with task force and speed [J].
Jochumsen, Mads ;
Niazi, Imran Khan ;
Mrachacz-Kersting, Natalie ;
Farina, Dario ;
Dremstrup, Kim .
JOURNAL OF NEURAL ENGINEERING, 2013, 10 (05)