Portable neuroimaging technologies can be employed for long-term monitoring of neurophysiological and neuropathological states. Functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are highly suited for such a purpose. Their multimodal integration allows the evaluation of hemodynamic and electrical brain activity together with neurovascular coupling. An innovative fNIRS-EEG system is here presented. The system integrated a novel continuous-wave fNIRS component and a modified commercial EEG device. fNIRS probing relied on fiberless technology based on light emitting diodes and silicon photomultipliers (SiPMs). SiPMs are sensitive semiconductor detectors, whose large detection area maximizes photon harvesting from the scalp and overcomes limitations of fiberless technology. To optimize the signal-to-noise ratio and avoid fNIRS-EEG interference, a digital lock-in was implemented for fNIRS signal acquisition. A benchtop characterization of the fNIRS component showed its high performances with a noise equivalent power below 1 pW. Moreover, the fNIRS-EEG device was tested in vivo during tasks stimulating visual, motor and pre-frontal cortices. Finally, the capabilities to perform ecological recordings were assessed in clinical settings on one Alzheimer’s Disease patient during long-lasting cognitive tests. The system can pave the way to portable technologies for accurate evaluation of multimodal brain activity, allowing their extensive employment in ecological environments and clinical practice.

In this paper, we present an innovative way to measure some physiological parameters (such as the pre-ejection period, the pulse transit time, the blood pressure) in a cardiac cycle. A combo PPG-ECG system has been employed to extract both the ECG signal from chest and simultaneously the photoplethysmography signal from the wrist and the forearm, to\ud calculate the pre-ejection period. This system represents an easy and non-invasive technique to determine these biomedical parameters without using expensive impedance cardiography equipment (ICG)

Functional Near Infrared Spectroscopy (fNIRS) systems for e-health applications usually suffer of 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 performances in such circumstances. In this work it has been designed and implemented a digital LIA system, based on a Zynq® Field Programmable Gate Array (FPGA), trying to explore if this technique might improve fNIRS system performances. More broadly, FPGA based solution flexibility has been investigated, with particular emphasis applied to digital filter parameters, needed in the digital LIA, and it has been evaluated its impact on the final signal detection and noise rejection capability. The realized architecture was a mixed solution between VHDL hardware modules and software ones, running within a softcore microprocessor. Experimental results have shown the goodness of the proposed solutions and comparative details among different implementation will be detailed. Finally a key aspect taken into account throughout the design was its modularity, allowing an ease increase of the input channels while avoiding the growth of the design cost of the electronics system.

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.

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