Deep-Framework: A Distributed, Scalable, and Edge-Oriented Framework for Real-Time Analysis of Video Streams.

Edge computing is the best approach for meeting the exponential demand and the real-time requirements of many video analytics applications. Since most of the recent advances regarding the extraction of information from images and video rely on computation heavy deep learning algorithms, there is a growing need for solutions that allow the deployment and use of new models on scalable and flexible edge architectures. In this work, we present Deep-Framework, a novel open source framework for developing edge-oriented real-time video analytics applications based on deep learning.

Local Chemical Stimulation of Neurons with the Fluidic Force Microscope (FluidFM).

Physiological communication between neurons is dependent on the exchange of neurotransmitters at the synapses. Although this chemical signal transmission targets specific receptors and allows for subtle adaptation of the action potential, in vitro neuroscience typically relies on electrical currents and potentials to stimulate neurons. The electric stimulus is unspecific and the confinement of the stimuli within the media is technically difficult to control and introduces large artifacts in electric recordings of the activity.

Pressure Mapping Mat for Tele-Home Care Applications.

Unlabelled: In this paper we present the development of a mat-like pressure mapping system based on a single layer textile sensor and intended to be used in home environments for monitoring the physical condition of persons with limited mobility. The sensor is fabricated by embroidering silver-coated yarns on a light cotton fabric and creating pressure-sensitive resistive elements by stamping the conductive polymer poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (

Pedot: PSS) at the crossing points of conductive stitches. A battery-operated mat prototype was developed and includes the scanning circuitry and a wireless communication module.

Evaluation of novel textile electrodes for ECG signals monitoring based on PEDOT:PSS-treated woven fabrics.

Unlabelled: Despite surface electrodes technology for biopotential recording is well established, different researches are aimed at overcoming the limitations exhibited by the available solutions. In this paper, a proposal for the low-cost development of textile electrodes based on woven fabrics treated with polymer poly-3,4-ethylenedioxythiophene doped with poly(styrene sulfonate) (

Pedot: PSS), is presented. Compared to other approaches, the proposed one can be exploited on any finished fabric.

Fully Textile, PEDOT:PSS Based Electrodes for Wearable ECG Monitoring Systems.

Goal: To evaluate a novel kind of textile electrodes based on woven fabrics treated with

Pedot: PSS, through an easy fabrication process, testing these electrodes for biopotential recordings.

Methods: Fabrication is based on raw fabric soaking in

Pedot: PSS using a second dopant, squeezing and annealing. The electrodes have been tested on human volunteers, in terms of both skin contact impedance and quality of the ECG signals recorded at rest and during physical activity (power spectral density, baseline wandering, QRS detectability, and broadband noise).

A new integrated system combining atomic force microscopy and micro-electrode array for measuring the mechanical properties of living cardiac myocytes.

In this paper we present a new experimental set-up which combines the surface characterization capabilities of atomic force microscopy at the sub-micrometer scale with non-invasive electrophysiological measurements obtained by using planar micro-electrode arrays. In order to show the potential of the combined measurements we studied the changes in cell topography and elastic properties of cardiac muscle cells as during the contraction-relaxation cycle. The onset of each beating cycle was precisely identified by the use of the extracellular potential signal, allowing us to combine nanomechanical measurements from multiple cardiomyocyte contractions in order to analyze the time-dependent variation of cell morphology and elasticity.