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.

Low-power EEG monitor based on compressed sensing with compressed domain noise rejection / Bertoni, Nicola; Senevirathna, Bathiya; Pareschi, Fabio; Mangia, Mauro; Rovatti, Riccardo; Abshire, Pamela; Simon, Jonathan Z.; Setti, Gianluca. - STAMPA. - 2016-:(2016), pp. 7527292.522-7527292.525. (Intervento presentato al convegno 2016 IEEE International Symposium on Circuits and Systems, ISCAS 2016 tenutosi a Montreal's Sheraton Centre, can nel 2016) [10.1109/ISCAS.2016.7527292].

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

MANGIA, MAURO;ROVATTI, RICCARDO;
2016

Abstract

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.
2016
Proceedings - IEEE International Symposium on Circuits and Systems
522
525
Low-power EEG monitor based on compressed sensing with compressed domain noise rejection / Bertoni, Nicola; Senevirathna, Bathiya; Pareschi, Fabio; Mangia, Mauro; Rovatti, Riccardo; Abshire, Pamela; Simon, Jonathan Z.; Setti, Gianluca. - STAMPA. - 2016-:(2016), pp. 7527292.522-7527292.525. (Intervento presentato al convegno 2016 IEEE International Symposium on Circuits and Systems, ISCAS 2016 tenutosi a Montreal's Sheraton Centre, can nel 2016) [10.1109/ISCAS.2016.7527292].
Bertoni, Nicola; Senevirathna, Bathiya; Pareschi, Fabio; Mangia, Mauro; Rovatti, Riccardo; Abshire, Pamela; Simon, Jonathan Z.; Setti, Gianluca
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/562411
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 9
  • ???jsp.display-item.citation.isi??? 9
social impact