<?xml version="1.0" encoding="utf-8"?>
<journal>
<title>Basic and Clinical Neuroscience Journal</title>
<title_fa>مجله علوم اعصاب پایه و بالینی</title_fa>
<short_title>BCN</short_title>
<subject>Medical Sciences</subject>
<web_url>http://bcn.iums.ac.ir</web_url>
<journal_hbi_system_id>137</journal_hbi_system_id>
<journal_hbi_system_user>journal137</journal_hbi_system_user>
<journal_id_issn>2008-126X</journal_id_issn>
<journal_id_issn_online>2228-7442</journal_id_issn_online>
<journal_id_pii></journal_id_pii>
<journal_id_doi>10.32598/bcn</journal_id_doi>
<journal_id_iranmedex></journal_id_iranmedex>
<journal_id_magiran></journal_id_magiran>
<journal_id_sid></journal_id_sid>
<journal_id_nlai></journal_id_nlai>
<journal_id_science></journal_id_science>
<language>en</language>
<pubdate>
	<type>jalali</type>
	<year>1405</year>
	<month>2</month>
	<day>1</day>
</pubdate>
<pubdate>
	<type>gregorian</type>
	<year>2026</year>
	<month>5</month>
	<day>1</day>
</pubdate>
<volume>17</volume>
<number>2</number>
<publish_type>online</publish_type>
<publish_edition>1</publish_edition>
<article_type>fulltext</article_type>
<articleset>
	<article>


	<language>en</language>
	<article_id_doi></article_id_doi>
	<title_fa></title_fa>
	<title>A Comprehensive Review of Imagined Speech Decoding in Brain-Computer Interfaces: Utilizing EEG and fNIRS Technologies</title>
	<subject_fa>Cognitive Neuroscience</subject_fa>
	<subject>Cognitive Neuroscience</subject>
	<content_type_fa>Review</content_type_fa>
	<content_type>Review</content_type>
	<abstract_fa></abstract_fa>
	<abstract>&lt;div style=&quot;text-align: justify;&quot;&gt;&lt;span style=&quot;font-size:14px;&quot;&gt;&lt;span style=&quot;font-family:Tahoma;&quot;&gt;&lt;span style=&quot;line-height:2;&quot;&gt;&lt;span style=&quot;unicode-bidi:embed&quot;&gt;The use of brain&amp;ndash;computer interfaces (BCIs) to decode imagined speech has significant clinical and assistive potential. Twenty-six studies investigated covert speech decoding between 2009 and 2025 using EEG, fNIRS, or hybrid EEG&amp;ndash;fNIRS systems. Early research (2009&amp;ndash;2012) primarily focused on analyzing phonemes and syllables with EEG, achieving accuracy rates around 75%. From 2013 to 2017, CNN-based phoneme decoding produced highly variable results (40%&amp;ndash;83%), with more complex multiclass tasks occasionally performing poorly (as low as 26.7%). Since 2018, binary paradigms such as yes/no responses have reached 64%&amp;ndash;100% accuracy. CNN variants (about 83.4%), AlexNet (90.3%), and LSTM-RNNs (92.5%) demonstrated notable improvements, whereas architectures like EEGNet and SPDNet often underperformed (24.79%&amp;ndash;66.93%). In hybrid EEG&amp;ndash;fNIRS methods, convolutional neural networks (CNNs) achieved roughly 53% accuracy, while traditional classifiers like SVM and LDA performed better, reaching 78&amp;ndash;79%. These results indicate that although deep learning and multimodal systems have potential for enhancing imagined speech decoding, there are still major challenges related to generalization, variability, and robustness.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;</abstract>
	<keyword_fa></keyword_fa>
	<keyword>Brain-computer interface, imagined speech decoding, EEG, fNIRS, machine learning, multimodal fusion</keyword>
	<start_page>0</start_page>
	<end_page>0</end_page>
	<web_url>http://bcn.iums.ac.ir/browse.php?a_code=A-10-8254-1&amp;slc_lang=en&amp;sid=1</web_url>


<author_list>
	<author>
	<first_name>Monireh</first_name>
	<middle_name></middle_name>
	<last_name>Motaqi</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>Dr.motaqi@gmail.com</email>
	<code>13700319475328460057566</code>
	<orcid>13700319475328460057566</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Physiotherapy Research Center, School of Rehabilitation, Shahid Beheshti University of Medical Sciences, Tehran, Iran.</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Majid</first_name>
	<middle_name></middle_name>
	<last_name>Moallemi</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>mid.moallem@gmail.com</email>
	<code>13700319475328460057567</code>
	<orcid>13700319475328460057567</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Department of Biomedical Engineering, Faculty of Engineering, Islamic Azad University, Mashhad Branch, Mashhad, Razavi Khorasan, Iran.</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Abolfazl</first_name>
	<middle_name></middle_name>
	<last_name>Mirani</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>rsr.mirani@bmsu.ac.ir</email>
	<code>13700319475328460057568</code>
	<orcid>13700319475328460057568</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Biomedical Engineering Research Center, New Health Technologies, Baqiyatallah University of Medical Sciences, Tehran, Iran.	</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Yeganeh</first_name>
	<middle_name></middle_name>
	<last_name>Aboutorabi</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>yeganeaboutorabi@gmail.com</email>
	<code>13700319475328460057569</code>
	<orcid>13700319475328460057569</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Department of Microbiology, Faculty of Basic Sciences, Islamic Azad University, Mashhad Branch, Mashhad, Razavi Khorasan, Iran.	</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Boshra</first_name>
	<middle_name></middle_name>
	<last_name>Hatef</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>boshrahatef@yahoo.com</email>
	<code>13700319475328460057570</code>
	<orcid>13700319475328460057570</orcid>
	<coreauthor>Yes
</coreauthor>
	<affiliation>Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


</author_list>


	</article>
</articleset>
</journal>
