ArticleBiomedical engineering letters2020
Multiclass covert speech classification using extreme learning machine.
Article in Biomedical engineering letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of EEG-Based Imagined Speech Classification Methods.Sensors (Basel, Switzerland) · 2024Pooled it
- Sentence-Level Silent Speech Recognition Using a Wearable EMG/EEG Sensor System with AI-Driven Sensor Fusion and Language Model.Sensors (Basel, Switzerland) · 2025Article
- Acquisition Of Balinese Imagined Spelling using Electroencephalogram (BISE) Dataset.Data in brief · 2025Article
- Adaptive LDA Classifier Enhances Real-Time Control of an EEG Brain-Computer Interface for Decoding Imagined Syllables.Brain sciences · 2024Article
- Ethical considerations for integrating multimodal computer perception and neurotechnology.Frontiers in human neuroscience · 2024Article
- Imagined Speech Classification Using EEG and Deep Learning.Bioengineering (Basel, Switzerland) · 2023Article
- Multiclass classification of imagined speech EEG using noise-assisted multivariate empirical mode decomposition and multireceptive field convolutional neural network.Frontiers in human neuroscience · 2023Article
- The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review.Sensors (Basel, Switzerland) · 2022Article
- [Key technology of brain-computer interaction based on speech imagery].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2022Article
- A State-of-the-Art Review of EEG-Based Imagined Speech Decoding.Frontiers in human neuroscience · 2022Review
- Silent EEG-Speech Recognition Using Convolutional and Recurrent Neural Network with 85% Accuracy of 9 Words Classification.Sensors (Basel, Switzerland) · 2021Article
- Article
- Decoding Covert Speech From EEG-A Comprehensive Review.Frontiers in neuroscience · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
The objective of the proposed research is to classify electroencephalography (EEG) data of covert speech words. Six subjects were asked to perform covert speech tasks i.e mental repetition of four different words i.e 'left', 'right', 'up' and 'down'. Fifty trials for each word recorded for every subject. Kernel-based Extreme Learning Machine (kernel ELM) was used for multiclass and binary classification of EEG signals of covert speech words. We achieved a maximum multiclass and binary classification accuracy of (49.77%) and (85.57%) respectively. The kernel ELM achieves significantly higher accuracy compared to some of the most commonly used classification algorithms in Brain-Computer Interfaces (BCIs). Our findings suggested that covert speech EEG signals could be successfully classified using kernel ELM. This research involving the classification of covert speech words potentially leading to real-time silent speech BCI research.
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