ArticleClinical neurophysiology practice2026
An open-source JavaScript clinical neurophysiology library for education and clinical research.
Article in Clinical neurophysiology practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Objective: We present 'Epicurrents', an open-source JavaScript library for processing and displaying neurophysiological signal data in a web browser. Methods: The library follows a modular architecture to enable support for multiple clinical neurophysiology modalities. It supports open standards such as the European Data Format (EDF) and Digital Imaging and Communications in Medicine (DICOM), with optional Python and Open Neural Network Exchange (ONNX) integrations for scientific signal processing. The application presented in this article is platform agnostic, requires no installation, and is usable both online and offline as a progressive web application. Results: The library has been tested in real-world educational and research projects and is used by the European Academy of Neurology for hands-on EEG-education in their congresses. While JavaScript's memory management poses limitations for processing large recordings, architectural workarounds such as shared memory buffers and asynchronous processing have resulted in improved performance. Conclusions: The application presented here is not intended nor certified for clinical diagnostics, but its accessibility and extensibility make it a promising tool for neurophysiology education and research. Significance: Epicurrents is the first modular JavaScript library for clinical neurophysiology education and illustrates how web technologies can also enhance collaborative scientific research in the field of clinical neurophysiology.
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