Advances in brain-computer interface for decoding speech imagery from EEG signals: a systematic review

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES Cognitive Neurodynamics Pub Date : 2024-09-04 DOI:10.1007/s11571-024-10167-0
Nimra Rahman, Danish Mahmood Khan, Komal Masroor, Mehak Arshad, Amna Rafiq, Syeda Maham Fahim
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Abstract

Numerous individuals encounter challenges in verbal communication due to various factors, including physical disabilities, neurological disorders, and strokes. In response to this pressing need, technology has actively pursued solutions to bridge the communication gap, recognizing the inherent difficulties faced in verbal communication, particularly in contexts where traditional methods may be inadequate. Electroencephalogram (EEG) has emerged as a primary non-invasive method for measuring brain activity, offering valuable insights from a cognitive neurodevelopmental perspective. It forms the basis for Brain-Computer Interfaces (BCIs) that provide a communication channel for individuals with neurological impairments, thereby empowering them to express themselves effectively. EEG-based BCIs, especially those adapted to decode imagined speech from EEG signals, represent a significant advancement in enabling individuals with speech disabilities to communicate through text or synthesized speech. By utilizing cognitive neurodevelopmental insights, researchers have been able to develop innovative approaches for interpreting EEG signals and translating them into meaningful communication outputs. To aid researchers in effectively addressing this complex challenge, this review article synthesizes key findings from state-of-the-art significant studies. It investigates into the methodologies employed by various researchers, including preprocessing techniques, feature extraction methods, and classification algorithms utilizing Deep Learning and Machine Learning approaches and their integration. Furthermore, the review outlines the potential avenues for future research, with the goal of advancing the practical implementation of EEG-based BCI systems for decoding imagined speech from a cognitive neurodevelopmental perspective.

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从脑电图信号解码语音图像的脑机接口研究进展:系统综述
由于身体残疾、神经系统疾病和中风等各种因素,许多人在语言交流方面遇到困难。为了满足这一迫切需求,科技界认识到语言交流所面临的固有困难,尤其是在传统方法可能无法满足的情况下,因此积极寻求缩小交流差距的解决方案。脑电图(EEG)已成为测量大脑活动的主要非侵入性方法,从认知神经发育的角度提供了宝贵的见解。脑电图是脑-计算机接口(BCI)的基础,它为有神经障碍的人提供了一个交流渠道,从而使他们能够有效地表达自己。基于脑电图的 BCI(脑机接口),尤其是那些能够解码脑电信号中的想象语音的 BCI,在帮助有语言障碍的人通过文本或合成语音进行交流方面取得了重大进展。研究人员利用对认知神经发育的深入了解,开发出创新的方法来解读脑电信号并将其转化为有意义的交流输出。为了帮助研究人员有效应对这一复杂的挑战,这篇综述文章综合了最新重要研究的主要发现。文章研究了不同研究人员采用的方法,包括预处理技术、特征提取方法、利用深度学习和机器学习方法的分类算法及其整合。此外,综述还概述了未来研究的潜在途径,目的是推动基于脑电图的 BCI 系统的实际应用,从认知神经发育的角度解码想象中的语音。
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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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