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Low-Power Lossless Data Compression for Wireless Brain Electrophysiology

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Low-Power Lossless Data Compression for Wireless Brain Electrophysiology

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dc.contributor.author Cuevas-López, Aarón es_ES
dc.contributor.author Pérez-Montoyo, Elena es_ES
dc.contributor.author López-Madrona, Víctor J. es_ES
dc.contributor.author Canals, Santiago es_ES
dc.contributor.author Moratal, David es_ES
dc.date.accessioned 2023-04-20T18:00:37Z
dc.date.available 2023-04-20T18:00:37Z
dc.date.issued 2022-05 es_ES
dc.identifier.uri http://hdl.handle.net/10251/192888
dc.description.abstract [EN] Wireless electrophysiology opens important possibilities for neuroscience, especially for recording brain activity in more natural contexts, where exploration and interaction are not restricted by the usual tethered devices. The limiting factor is transmission power and, by extension, battery life required for acquiring large amounts of neural electrophysiological data. We present a digital compression algorithm capable of reducing electrophysiological data to less than 65.5% of its original size without distorting the signals, which we tested in vivo in experimental animals. The algorithm is based on a combination of delta compression and Huffman codes with optimizations for neural signals, which allow it to run in small, low-power Field-Programmable Gate Arrays (FPGAs), requiring few hardware resources. With this algorithm, a hardware prototype was created for wireless data transmission using commercially available devices. The power required by the algorithm itself was less than 3 mW, negligible compared to the power saved by reducing the transmission bandwidth requirements. The compression algorithm and its implementation were designed to be device-agnostic. These developments can be used to create a variety of wired and wireless neural electrophysiology acquisition systems with low power and space requirements without the need for complex or expensive specialized hardware. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Sensors es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Low power es_ES
dc.subject Data compression es_ES
dc.subject Wireless es_ES
dc.subject Brain es_ES
dc.subject Electrophysiology es_ES
dc.subject FPGA es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Low-Power Lossless Data Compression for Wireless Brain Electrophysiology es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/s22103676 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Cuevas-López, A.; Pérez-Montoyo, E.; López-Madrona, VJ.; Canals, S.; Moratal, D. (2022). Low-Power Lossless Data Compression for Wireless Brain Electrophysiology. Sensors. 22(10):1-19. https://doi.org/10.3390/s22103676 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/s22103676 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 19 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 22 es_ES
dc.description.issue 10 es_ES
dc.identifier.eissn 1424-8220 es_ES
dc.identifier.pmid 35632085 es_ES
dc.identifier.pmcid PMC9147146 es_ES
dc.relation.pasarela S\483884 es_ES
dc.subject.ods 03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades es_ES
upv.costeAPC 2360 es_ES


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