脑-机接口
运动表象
计算机科学
人工智能
卷积神经网络
脑电图
可用性
深度学习
接口(物质)
召回
模式识别(心理学)
机器学习
人机交互
精神科
最大气泡压力法
哲学
气泡
语言学
并行计算
心理学
作者
Cristian David Guerrero-Mendez,Cristian Felipe Blanco-Díaz,Andres F. Ruiz-Olaya,Alberto López-Delis,Sebastián Jaramillo-Isaza,Rafhael M. Andrade,Alberto F. De Souza,Denis Delisle-Rodriguez,Anselmo Frizera,Teodiano Bastos
出处
期刊:Biomedical Physics & Engineering Express
[IOP Publishing]
日期:2023-06-23
卷期号:9 (4): 045029-045029
标识
DOI:10.1088/2057-1976/acde82
摘要
Abstract Motor Imagery (MI)-Brain Computer-Interfaces (BCI) illiteracy defines that not all subjects can achieve a good performance in MI-BCI systems due to different factors related to the fatigue, substance consumption, concentration, and experience in the use. To reduce the effects of lack of experience in the use of BCI systems (naïve users), this paper presents the implementation of three Deep Learning (DL) methods with the hypothesis that the performance of BCI systems could be improved compared with baseline methods in the evaluation of naïve BCI users. The methods proposed here are based on Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM)/Bidirectional Long Short-Term Memory (BiLSTM), and a combination of CNN and LSTM used for upper limb MI signal discrimination on a dataset of 25 naïve BCI users. The results were compared with three widely used baseline methods based on the Common Spatial Pattern (CSP), Filter Bank Common Spatial Pattern (FBCSP), and Filter Bank Common Spatial-Spectral Pattern (FBCSSP), in different temporal window configurations. As results, the LSTM-BiLSTM-based approach presented the best performance, according to the evaluation metrics of Accuracy, F-score, Recall, Specificity, Precision, and ITR, with a mean performance of 80% (maximum 95%) and ITR of 10 bits/min using a temporal window of 1.5 s. The DL Methods represent a significant increase of 32% compared with the baseline methods ( p < 0.05). Thus, with the outcomes of this study, it is expected to increase the controllability, usability, and reliability of the use of robotic devices in naïve BCI users.
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