activity
20232025
most citedHierarchical Event Descriptor library schema for EEG data annotation

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2025

Quantifying Data Requirements for EEG Independent Component Analysis Using AMICA

Gwenevere Frank, Seyed Yahya Shirazi, Jason Palmer +3

Independent Component Analysis (ICA) is an important step in EEG processing for a wide-ranging set of applications. However, ICA requires well-designed studies and data collection…

eess.SP2025

EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding

Bruno Aristimunha, Dung Truong, Pierre Guetschel +16

Current electroencephalogram (EEG) decoding models are typically trained on small numbers of subjects performing a single task. Here, we introduce a large-scale, code-submission-ba…

q-bio.QM2024★ 1 cited

UNISEP: A Unified Sensor Placement Framework for Human Motion Capture and Wearables

Julius Welzel, Sein Jeung, Lara Godbersen +1

The proliferation of wearable sensors and monitoring technologies has created a need for standardized sensor placement protocols. While existing standards like the Surface Electrom…

eess.SP2023

An Exploration of Optimal Parameters for Efficient Blind Source Separation of EEG Recordings Using AMICA

Gwenevere Frank, Seyed Yahya Shirazi, Jason Palmer +3

EEG continues to find a multitude of uses in both neuroscience research and medical practice, and independent component analysis (ICA) continues to be an important tool for analyzi…

q-bio.NC2023★ 2 cited

Hierarchical Event Descriptor library schema for EEG data annotation

Dora Hermes, Tal Pal Attia, Sándor Beniczky +11

Standardizing terminology to annotate electrophysiological events can improve both computational research and clinical care. Sharing data enriched with standard terms can facilitat…