Low-power EEG monitor based on compressed sensing with compressed domain noise rejection

Nicola Bertoni, Bathiya Senevirathna, Fabio Pareschi, Mauro Mangia, Riccardo Rovatti, Pamela Abshire, Jonathan Z. Simon, Gianluca Setti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations


Wireless sensor nodes capable of acquiring and transmitting biosignals are increasingly important to address future needs in healthcare monitoring. One of the main issues in designing these systems is the unavoidable energy constraint due to the limited battery lifetime, which strictly limits the amount of data that may be transmitted. Compressed Sensing (CS) is an emerging technique for introducing low-power, real-time compression of the acquired signals before transmission. The recently developed rakeness approach is capable of further increasing CS performance. In this paper we apply the rakeness-CS technique to enhance compression capabilities for electroencephalographic (EEG) signals, and particularly for Evoked Potentials (EP), which are recordings of the neural activity evoked by the presentation of a stimulus. Simulation results demonstrate that EPs are correctly reconstructed using rakeness-CS with a compression factor of 16. Additionally, some interesting denoising capabilities are identified: the high-frequency noise components are rejected and the 60 Hz power line noise is decreased by more than 20 dB with respect to the state-of-the-art filtering when rakeness-CS techniques are applied to the EEG data stream.
Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Symposium on Circuits and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Print)9781479953400
StatePublished - Jul 29 2016
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15


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