ArticleSensors (Basel, Switzerland)2020
Enhancing Classification Performance of fNIRS-BCI by Identifying Cortically Active Channels Using the z-Score Method.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- AI-Driven Hemodynamic Detection of Self-Induced Daydreaming With EMG-Based Physiological Triggers During Pre- and Post-Prandial States Using fNIRS and EGG.CNS neuroscience & therapeutics · 2026Article
- Exploring Imagined Movement for Brain-Computer Interface Control: An fNIRS and EEG Review.Brain sciences · 2025Review
- A specific model of resting-state functional brain network in MRI-negative temporal lobe epilepsy.Heliyon · 2025Article
- Improved performance of fNIRS-BCI by stacking of deep learning-derived frequency domain features.PloS one · 2025Article
- Functional near-infrared spectroscopy for the assessment and treatment of patients with disorders of consciousness.Frontiers in neurology · 2025Review
- Open-access fNIRS dataset for motor imagery of lower-limb knee and ankle joint tasks.Frontiers in robotics and AI · 2025Article
- Enhancing Classification Accuracy with Integrated Contextual Gate Network: Deep Learning Approach for Functional Near-Infrared Spectroscopy Brain-Computer Interface Application.Sensors (Basel, Switzerland) · 2024Article
- Metaheuristic Optimization-Based Feature Selection for Imagery and Arithmetic Tasks: An fNIRS Study.Sensors (Basel, Switzerland) · 2023Article
- Driving drowsiness detection using spectral signatures of EEG-based neurophysiology.Frontiers in physiology · 2023Article
- LASSO Homotopy-Based Sparse Representation Classification for fNIRS-BCI.Sensors (Basel, Switzerland) · 2022Article
- Analyzing Classification Performance of fNIRS-BCI for Gait Rehabilitation Using Deep Neural Networks.Sensors (Basel, Switzerland) · 2022Article
- Data Processing in Functional Near-Infrared Spectroscopy (fNIRS) Motor Control Research.Brain sciences · 2021Review
- Vector Phase Analysis Approach for Sleep Stage Classification: A Functional Near-Infrared Spectroscopy-Based Passive Brain-Computer Interface.Frontiers in human neuroscience · 2021Article
- Brain cortex activity of patients with disorders of consciousness under familiar and unfamiliar voice of subject's own name: an fNIRS-based study.Frontiers in neurologyArticle
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7 authors.
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Abstract
A state-of-the-art brain-computer interface (BCI) system includes brain signal acquisition, noise removal, channel selection, feature extraction, classification, and an application interface. In functional near-infrared spectroscopy-based BCI (fNIRS-BCI) channel selection may enhance classification performance by identifying suitable brain regions that contain brain activity. In this study, the z-score method for channel selection is proposed to improve fNIRS-BCI performance. The proposed method uses cross-correlation to match the similarity between desired and recorded brain activity signals, followed by forming a vector of each channel's correlation coefficients' maximum values. After that, the z-score is calculated for each value of that vector. A channel is selected based on a positive z-score value. The proposed method is applied to an open-access dataset containing mental arithmetic (MA) and motor imagery (MI) tasks for twenty-nine subjects. The proposed method is compared with the conventional
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