Work

Impact of Data Quality on EEG-Based Biomedical Systems

Year: 2025

Type: conference-paper

Abstract: With the growing use of biomedical signal acquisition systems such as EEG, ensuring high-quality data acquisition in resource-constrained environments remains a critical challenge. This study evaluates how data quality-specifically noise, error, and loss-affects the performance of a CNN-based epileptic seizure detection system in terms of accuracy, execution time, and power consumption. We simulate different corruption scenarios and propose strategies for tolerance assessment and lightweight compensation. The results provide insights for building adaptive EEG-based biomedical systems.

Source: International Conference on Bio-engineering for Smart Technologies (BioSMART)

DOI: 10.1109/biosmart66413.2025.11046065

Authors: Xia Han, Frédéric Amiel, Cong Wang, Wenjun Hu, Zefeng Wang, Xun Zhang

Institutions: Institut Supérieur d'Électronique de Paris, Huzhou Normal University

Language: English

Topic: EEG and Brain-Computer Interfaces

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

Funder: China Scholarship Council

Award: G303048776