[HTML][HTML] Pre-trial EEG-based single-trial motor performance prediction to enhance neuroergonomics for a hand force task
We propose a framework for building electrophysiological predictors of single-trial motor
performance variations, exemplified for SVIPT, a sequential isometric force control task …
performance variations, exemplified for SVIPT, a sequential isometric force control task …
Characterizing regularization techniques for spatial filter optimization in oscillatory eeg regression problems: Guidelines derived from simulation and real-world data
We report on novel supervised algorithms for single-trial brain state decoding. Their
reliability and robustness are essential to efficiently perform neurotechnological applications …
reliability and robustness are essential to efficiently perform neurotechnological applications …
[HTML][HTML] Post-hoc Labeling of Arbitrary M/EEG Recordings for Data-Efficient Evaluation of Neural Decoding Methods
S Castaño-Candamil, A Meinel… - Frontiers in …, 2019 - frontiersin.org
Many cognitive, sensory and motor processes have correlates in oscillatory neural source
activity, which is embedded as a subspace in the recorded brain signals. Decoding such …
activity, which is embedded as a subspace in the recorded brain signals. Decoding such …
[PDF][PDF] Commonalities of Motor Performance Metrics are Revealed by Predictive Oscillatory EEG Components.
The power of oscillatory components of the electroencephalogram (EEG) can be predictive
for the single-trial performance score of an upcoming task. State-of-the-art machine learning …
for the single-trial performance score of an upcoming task. State-of-the-art machine learning …
Mining within-trial oscillatory brain dynamics to address the variability of optimized spatial filters
A Meinel, H Kolkhorst… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Data-driven spatial filtering algorithms optimize scores, such as the contrast between two
conditions to extract oscillatory brain signal components. Most machine learning …
conditions to extract oscillatory brain signal components. Most machine learning …
[PDF][PDF] Informative Oscillatory EEG Components and their Persistence in Time and Frequency
M Tangermann, A Meinel - 2017 - scitepress.org
Oscillatory brain activity measured by the electroencephalogram, local field potentials or
magnetoencephalogram can reflect cognitive processes. It can be used to run brain …
magnetoencephalogram can reflect cognitive processes. It can be used to run brain …
[引用][C] Machine learning methods for motor performance decoding in adaptive deep brain stimulation
S Castaño-Candamil - 2020 - Dissertation, Universität Freiburg …