Search research articles
Contact Us
Filters
Showing results (1-10 of 12) with videos related to
Page
of 2
Sort By:
Frontiers in Human Neuroscience
|
July 11, 2022
Error-Related Potentials in Reinforcement Learning-Based Brain-Machine Interfaces
Aline Xavier Fidêncio, Christian Klaes, Ioannis Iossifidis
Scientific Data
|
July 24, 2025
Hand Motion Catalog of Human Center-Out Transport Trajectories Measured Redundantly in 3D Task-Space
Tim Sziburis, Susanne Blex, Tobias Glasmachers, et al.
Scientific Reports
|
January 6, 2026
Insights into motor control: predict muscle activity from upper limb kinematics with LSTM networks
Marie D Schmidt, Tobias Glasmachers, Ioannis Iossifidis
Frontiers in Human Neuroscience
|
August 1, 2024
A generic error-related potential classifier based on simulated subjects
Aline Xavier Fidêncio, Christian Klaes, Ioannis Iossifidis
Biomedical Engineering Online
|
June 24, 2023
The concepts of muscle activity generation driven by upper limb kinematics
Marie D Schmidt, Tobias Glasmachers, Ioannis Iossifidis
Frontiers in Human Neuroscience
|
June 19, 2025
Hybrid brain-computer interface using error-related potential and reinforcement learning
Aline Xavier Fidêncio, Felix Grün, Christian Klaes, et al.
Journal of Neural Engineering
|
October 7, 2022
Deep transfer learning compared to subject-specific models for sEMG decoders
Stephan Johann Lehmler, Muhammad Saif-Ur-Rehman, Glasmachers Tobias, et al.
Computers in Biology and Medicine
|
November 19, 2023
ConTraNet: A hybrid network for improving the classification of EEG and EMG signals with limited training data
Omair Ali, Muhammad Saif-Ur-Rehman, Tobias Glasmachers, et al.
Scientific Reports
|
March 11, 2022
Enhancing the decoding accuracy of EEG signals by the introduction of anchored-STFT and adversarial data augmentation method
Omair Ali, Muhammad Saif-Ur-Rehman, Susanne Dyck, et al.
Frontiers in Neurorobotics
|
October 9, 2024
Human in the collaborative loop: a strategy for integrating human activity recognition and non-invasive brain-machine interfaces to control collaborative robots
Artur Pilacinski, Lukas Christ, Marius Boshoff, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 12) with videos related to
Sort By:
Page
of 2
Frontiers in Human Neuroscience
|
July 11, 2022
Error-Related Potentials in Reinforcement Learning-Based Brain-Machine Interfaces
Aline Xavier Fidêncio, Christian Klaes, Ioannis Iossifidis
Scientific Data
|
July 24, 2025
Hand Motion Catalog of Human Center-Out Transport Trajectories Measured Redundantly in 3D Task-Space
Tim Sziburis, Susanne Blex, Tobias Glasmachers, et al.
Scientific Reports
|
January 6, 2026
Insights into motor control: predict muscle activity from upper limb kinematics with LSTM networks
Marie D Schmidt, Tobias Glasmachers, Ioannis Iossifidis
Frontiers in Human Neuroscience
|
August 1, 2024
A generic error-related potential classifier based on simulated subjects
Aline Xavier Fidêncio, Christian Klaes, Ioannis Iossifidis
Biomedical Engineering Online
|
June 24, 2023
The concepts of muscle activity generation driven by upper limb kinematics
Marie D Schmidt, Tobias Glasmachers, Ioannis Iossifidis
Frontiers in Human Neuroscience
|
June 19, 2025
Hybrid brain-computer interface using error-related potential and reinforcement learning
Aline Xavier Fidêncio, Felix Grün, Christian Klaes, et al.
Journal of Neural Engineering
|
October 7, 2022
Deep transfer learning compared to subject-specific models for sEMG decoders
Stephan Johann Lehmler, Muhammad Saif-Ur-Rehman, Glasmachers Tobias, et al.
Computers in Biology and Medicine
|
November 19, 2023
ConTraNet: A hybrid network for improving the classification of EEG and EMG signals with limited training data
Omair Ali, Muhammad Saif-Ur-Rehman, Tobias Glasmachers, et al.
Scientific Reports
|
March 11, 2022
Enhancing the decoding accuracy of EEG signals by the introduction of anchored-STFT and adversarial data augmentation method
Omair Ali, Muhammad Saif-Ur-Rehman, Susanne Dyck, et al.
Frontiers in Neurorobotics
|
October 9, 2024
Human in the collaborative loop: a strategy for integrating human activity recognition and non-invasive brain-machine interfaces to control collaborative robots
Artur Pilacinski, Lukas Christ, Marius Boshoff, et al.
Page
of 2