An open-source JavaScript clinical neurophysiology library for education and clinical research.
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| Titel: | An open-source JavaScript clinical neurophysiology library for education and clinical research. |
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| Autoren: | Lohi S; Department of Clinical Neurophysiology, North Karelia Central Hospital, Joensuu, Finland.; Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland.; Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland., Julkunen P; Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland.; Department of Technical Physics, University of Eastern Finland, Kuopio, Finland., Kälviäinen R; Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.; Epilepsy Center, Kuopio University Hospital, Kuopio, Finland., Mervaala E; Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland.; Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland. |
| Quelle: | Clinical neurophysiology practice [Clin Neurophysiol Pract] 2026 Feb 06; Vol. 11, pp. 115-125. Date of Electronic Publication: 2026 Feb 06 (Print Publication: 2026). |
| Publikationsart: | Journal Article |
| Sprache: | English |
| Info zur Zeitschrift: | Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101684308 Publication Model: eCollection Cited Medium: Internet ISSN: 2467-981X (Electronic) Linking ISSN: 2467981X NLM ISO Abbreviation: Clin Neurophysiol Pract Subsets: PubMed not MEDLINE |
| Imprint Name(s): | Original Publication: Amsterdam : Elsevier, [2016]- |
| 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. (© 2026 The Author(s).) |
| Competing Interests: | The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Contributed Indexing: | Keywords: Clinical neurophysiology; Electroencephalography; Electromyography; Nerve conduction studies; Open source; Web application |
| Entry Date(s): | Date Created: 20260220 Date Completed: 20260220 Latest Revision: 20260220 |
| Update Code: | 20260220 |
| PubMed Central ID: | PMC12914546 |
| DOI: | 10.1016/j.cnp.2026.02.001 |
| PMID: | 41717536 |
| Datenbank: | MEDLINE |
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Nájsť tento článok vo Web of Science | Abstract: | Objective: We present 'Epicurrents', an open-source JavaScript library for processing and displaying neurophysiological signal data in a web browser.<br />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.<br />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.<br />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.<br />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.<br /> (© 2026 The Author(s).) |
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| ISSN: | 2467-981X |
| DOI: | 10.1016/j.cnp.2026.02.001 |