Neurocomputing
NeuronLab: BCI framework for the study of biosignals
Brain–Computer Interfaces (BCIs) allow the acquisition of brain activity using non-invasive techniques such as Electroencephalography (EEG). Since BCI devices do not commonly interpret the acquired EEG signals, external...
Quick facts
- Year
- 2024
- Venue
- Neurocomputing
- Identifier
- lopezbernal2024neuronlab
Suggested citation
Sergio López Bernal, Juan Antonio Martínez López, Enrique Tomás Martínez Beltrán, Mario Quiles Pérez, Gregorio Martínez Pérez, Alberto Huertas Celdrán (2024). NeuronLab: BCI framework for the study of biosignals. Neurocomputing.
Abstract
Brain–Computer Interfaces (BCIs) allow the acquisition of brain activity using non-invasive techniques such as Electroencephalography (EEG). Since BCI devices do not commonly interpret the acquired EEG signals, external software applications play a critical role in the BCI lifecycle. Despite the literature offering a great variety of platforms and frameworks, they present several limitations, such as implementing old software architectures or needing more functionality to cover all phases of the BCI lifecycle. Based on these limitations, this work proposes the design and implementation of NeuronLab, a secure, multi-platform, standalone, multi-paradigm, and web-based framework that defines all BCI lifecycle phases and provides novel functionality compared to current open-source BCI software, such as sharing experiments between researchers and storing data on the cloud. This framework has been validated in two experiments common in BCI literature: P300 identification and limb movements detection. This verification has been performed based on performance metrics, such as CPU and RAM consumption, highlighting that NeuronLab is a promising solution for BCI scenarios requiring a distributed and collaborative platform for researchers and practitioners.
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