ArticleFrontiers in neuroscience2019
Time-Variant Linear Discriminant Analysis Improves Hand Gesture and Finger Movement Decoding for Invasive Brain-Computer Interfaces.
Article in Frontiers in neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- EEG Feature Extraction and Classification for Upper Limb Flexion and Extension Motor Imagery Based on Discriminative Filter Bank Common Spatial Pattern.Brain sciences · 2026Article
- Explainability in AI-enabled medical neurotechnology: a scoping review.Journal of neuroengineering and rehabilitation · 2026Article
- Signal properties and stability of a chronically implanted endovascular brain computer interface.medRxiv : the preprint server for health sciences · 2025Article
- Classification of Electroencephalography Motor Execution Signals Using a Hybrid Neural Network Based on Instantaneous Frequency and Amplitude Obtained via Empirical Wavelet Transform.Sensors (Basel, Switzerland) · 2025Article
- 5-year follow-up of a fully implanted brain-computer interface in a spinal cord injury patient.Journal of neural engineering · 2025Article
- Enhancing Hand Sensorimotor Function in Individuals with Cervical Spinal Cord Injury: A Novel Tactile Discrimination Feedback Approach Using a Multiple-Baseline Design.Brain sciences · 2025Article
- Decoding and geometry of ten finger movements in human posterior parietal cortex and motor cortex.Journal of neural engineering · 2023Article
- Hyper-parameter tuning and feature extraction for asynchronous action detection from sub-thalamic nucleus local field potentials.Frontiers in human neuroscience · 2023Article
- Characterization of High-Gamma Activity in Electrocorticographic Signals.Frontiers in neuroscience · 2023Article
- Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation.Experimental neurology · 2022Review
- Individual finger movement decoding using a novel ultra-high-density electroencephalography-based brain-computer interface system.Frontiers in neuroscience · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Invasive brain-computer interfaces yield remarkable performance in a multitude of applications. For classification experiments, high-gamma bandpower features and linear discriminant analysis (LDA) are commonly used due to simplicity and robustness. However, LDA is inherently static and not suited to account for transient information that is typically present in high-gamma features. To resolve this issue, we here present an extension of LDA to the time-variant feature space. We call this method
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Registered trials
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