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Found 7 papers, 1 papers with code
Latent Alignment with Deep Set EEG Decoders
We delineate a trade-off relationship between increased classification accuracy when alignment is performed at later modeling stages, and susceptibility to class-imbalance in the set of trials that the statistics are computed on.
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets
Task 2 is centred on Brain-Computer Interfacing (BCI), addressing motor imagery decoding across both subjects and data sets.
Team Cogitat at NeurIPS 2021: Benchmarks for EEG Transfer Learning Competition
The second task required to transfer models trained on the subjects of one or more source motor imagery datasets to perform inference on two target datasets, providing a small set of personalized calibration data for multiple test subjects.
EEGminer: Discovering Interpretable Features of Brain Activity with Learnable Filters
Patterns of brain activity are associated with different brain processes and can be used to identify different brain states and make behavioral predictions.
A Tutorial on Graph Theory for Brain Signal Analysis
Finally, the notion of signals residing on a given graph is introduced and elements from the emerging field of graph signal processing (GSP) are provided.
Towards the bio-personalization of music recommendation systems: A single-sensor EEG biomarker of subjective music preference
During a stage of exploratory analysis, and using the signals from a suitably designed experiment, we established the biomarker, which acts on brain activations recorded over the left prefrontal cortex and focuses on the functional coupling between high-beta and low-gamma oscillations.
A Consumer BCI for Automated Music Evaluation Within a Popular On-Demand Music Streaming Service - Taking Listener's Brainwaves to Extremes
We investigated the possibility of using a machine-learning scheme in conjunction with commercial wearable EEG-devices for translating listener's subjective experience of music into scores that can be used for the automated annotation of music in popular on-demand streaming services.
