title: Wearable EEG via lossless compression.
abstract: This work presents a wearable multi-channel EEG recording system featuring a lossless compression algorithm. The algorithm, based in a previously reported algorithm by the authors, exploits the existing temporal correlation between samples at different sampling times, and the spatial correlation between different electrodes across the scalp. The low-power platform is able to compress, by a factor between 2.3 and 3.6, up to 300sps from 64 channels with a power consumption of 176μW/ch. The performance of the algorithm compares favorably with the best compression rates reported up to date in the literature.
authors.forename: Guillermo
authors.initials: G
authors.lastname: Dufort
authors.forename: Federico
authors.initials: F
authors.lastname: Favaro
authors.forename: Federico
authors.initials: F
authors.lastname: Lecumberry
authors.forename: Alvaro
authors.initials: A
authors.lastname: Martin
authors.forename: Juan P
authors.initials: JP
authors.lastname: Oliver
authors.forename: Julian
authors.initials: J
authors.lastname: Oreggioni
authors.forename: Ignacio
authors.initials: I
authors.lastname: Ramirez
authors.forename: Gadiel
authors.initials: G
authors.lastname: Seroussi
authors.forename: Leonardo
authors.initials: L
authors.lastname: Steinfeld
mesh_terms: D000465:Algorithms; D044962:Data Compression; D004566:Electrodes; D004569:Electroencephalography / Q000295:instrumentation*; D006801:Humans