Exploring FPGA‐Based Lock‐In Techniques for Brain Monitoring Applications

Leonardo Mistretta, Giuseppe Costantino Giaconia, Giuseppe Greco, Raimondo Rizzo

Risultato della ricerca: Articlepeer review

14 Citazioni (Scopus)

Abstract

Functional near‐infrared spectroscopy (fNIRS) systems for e‐health applications usually suffer from poor signal detection, mainly due to a low end‐to‐end signal‐to‐noise ratio of the electronics chain. Lock‐in amplifiers (LIA) historically represent a powerful technique helping to improve performance in such circumstances. In this work a digital LIA system, based on a Zynq® field programmable gate array (FPGA) has been designed and implemented, in an attempt to explore if this technique might improve fNIRS system performance. More broadly, FPGA‐based solution flexibility has been investigated, with particular emphasis applied to digital filter parameters, needed in the digital LIA, and its impact on the final signal detection and noise rejection capability has been evaluated. The realized architecture was a mixed solution between VHDL hardware modules and software modules, running within a microprocessor. Experimental results have shown the goodness of the proposed solutions and comparative details among different implementations will be detailed. Finally a key aspect taken into account throughout the design was its modularity, allowing an easy increase of the input channels while avoiding the growth of the design cost of the electronics system.
Lingua originaleEnglish
Numero di pagine13
RivistaELECTRONICS
Volume6
Stato di pubblicazionePublished - 2017

All Science Journal Classification (ASJC) codes

  • ???subjectarea.asjc.2200.2207???
  • ???subjectarea.asjc.1700.1711???
  • ???subjectarea.asjc.1700.1708???
  • ???subjectarea.asjc.1700.1705???
  • ???subjectarea.asjc.2200.2208???

Fingerprint

Entra nei temi di ricerca di 'Exploring FPGA‐Based Lock‐In Techniques for Brain Monitoring Applications'. Insieme formano una fingerprint unica.

Cita questo