High-throughput data analysis challenges in laboratory automation and lab-on-a-chip devices´ applications are continuously increasing. In cell culture monitoring, specifically, the electrical cell-substrate impedance sensing technique (ECIS), has been extensively used for a wide variety of applications. One of the main drawbacks of ECIS is the need for implementing complex electrical models to decode the electrical performance of the full system composed by the electrodes, medium, and cells. In this work we present a new approach for the analysis of data and the prediction of a specific biological parameter, the fill-factor of a cell culture, based on a polynomial regression, data-analytic model. The method was successfully applied to a specific ECIS circuit and two different cell cultures, N2A (a mouse neuroblastoma cell line) and myoblasts. The data-analytic modeling approach can be used in the decoding of electrical impedance measurements of different cell lines, provided a representative volume of data from the cell culture growth is available, sorting out the difficulties traditionally found in the implementation of electrical models. This can be of particular importance for the design of control algorithms for cell cultures in tissue engineering protocols, and labs-on-a-chip and wearable devices applications.

Journal Paper - Sensors, vol. 19, no. 21, art. 4639, 2019 MDPI
DOI: 10.3390/s19214639    ISSN: 1424-8220    » doi

Neurophysiological observations are clarifying how astrocytes can actively participate in information processing and how they can encode information through frequency and amplitude modulation of intracellular Ca²⁺ signals. Consequently, hardware realization of astrocytes is important for developing the next generation of bio-inspired computing systems. In this paper, astrocytic calcium oscillations and neuronal firing dynamics are presented by De Pittà and IF (Integrated & Fire) models, respectively. Considering highly nonlinear equations of the astrocyte model, linear approximation and single constant multiplication (SCM) techniques are employed for efficient hardware execution while maintaining the dynamic of the original models. This low-cost hardware architecture for the astrocyte model is able to show the essential features of different types of Ca²⁺ modulation such as amplitude modulation (AM), frequency modulation (FM), or both modes (AFM). To show good agreement between the results of original models simulated in MATLAB and the proposed digital circuits executed on FPGA, quantitative, and qualitative analyses including phase plane are done. This new neuromorphic circuit of astrocyte is able to successfully demonstrate AM/FM/AFM calcium signaling in its real operation on FPGA and has applications in self-repairing systems. It also can be employed as a subsystem for linking biological cells to artificial neuronal networks using astrocytic calcium oscillations in future research.

Journal Paper - Frontiers in Neuroscience, vol. 13, article 998, 2019 FRONTIERS RESEARCH FOUNDATION
DOI: 10.3389/fnins.2019.00998    ISSN: 1662-4548    » doi

This paper describes a multichannel bidirectional front-end for true closed-loop neuromodulation. Stimulation artefacts are reduced via a 4-channel H-bridge current source sharing stimulators to minimize residual charge drops in the electrodes. The 4-channel sensing front-end is capable of multichannel sensing in the presence of artefacts as a result of its high total common-mode rejection ratio (TCMRR) that accounts for CMRR drop due to electrode mismatch. Experimental verification of a prototype fabricated in 180 nm process shows a stimulator front-end with 0.059% charge balance and 0.275 nA DC current error. The recording front-end consumes 3.24 μW, tolerates common-mode interference up to 1 Vpp and shows a TCMRR > 66 dB for 500 mVpp inputs.

Conference - IEEE Biomedical Circuits and Systems Conference BioCAS 2019

This paper describes a low-noise, low-power and high dynamic range analog front-end intended for sensing neural signals. In order to reduce interface area, a 32-channel multiplexer is implemented on circuit input. Furthermore, a spatial delta encoding is proposed to compress the signal range. A differential artifact compression algorithm is implemented to avoid saturation in the signal path, thus enabling reconstruct or suppressing artifacts in digital domain. The proposed design has been implemented using 0.18 μm TSMC technology. Experimental results shows a power consumption per channel of 1.0 μW, an input referred noise of 1.1 μVrms regarding the bandwidth of interest and a dynamic range of 91 dB.

Conference - IEEE Biomedical Circuits and Systems Conference BioCAS 2019

Photon detection at longer wavelengths is much desired for LiDAR applications. Silicon photodiodes with deeper junctions and larger multiplication regions are more sensitive to near-IR photons. This paper presents the complete electro-optical characterization of a P-well/Deep N-well single photon avalanche diode integrated in 110nm CIS technology. Devices with various sizes, shapes and guard ring widths have been fabricated and tested. The measured mean breakdown voltage is of 18V. The proposed structure has 0.4Hz/um2 dark count rate, 0.5% afterpulsing, 188ps FWHM (total) jitter and around 10% photon detection probability at 850nm wavelength. All figures have been measured at 3V excess voltage.

Conference - European Solid-State Device Research Conference ESSDERC 2019