Dynamic sub-array selection-based energy-efficient localization and tracking method to power implanted medical devices in scattering heterogenous media employing ultrasound.

Ultrasound (US) as a wireless power transfer methodology has drawn considerable attention from the implantable medical devices (IMD) research community. Beamforming (BF) using an external transducer array patch (ETAP) has been proposed as a robust localization scheme to find a mm-sized IMD inside the human body. However, for applications focusing on deep and shallow IMDs, optimum resource utilization at the ETAP is a major power efficiency concern for energy-constrained wearable patches.

A Fingertip-Mimicking 12×16 200μm-Resolution e-skin Taxel Readout Chip with per-Taxel Spiking Readout and Embedded Receptive Field Processing.

This paper presents an electronic skin (e-skin) taxel array readout chip in 0.18μm CMOS technology, achieving the highest reported spatial resolution of 200μm, comparable to human fingertips. A key innovation is the integration on chip of a 12×16 polyvinylidene fluoride (PVDF)-based piezoelectric sensor array with per-taxel signal conditioning frontend and spiking readout combined with local embedded neuromorphic first-order processing through Complex Receptive Fields (CRFs).

Brain Feature Extraction With an Artifact-Tolerant Multiplexed Time-Encoding Neural Frontend for True Real-Time Closed-Loop Neuromodulation.

Closed-loop neuromodulation is emerging as a more effective and targeted solution for the treatment of neurological symptoms compared to traditional open-loop stimulation. The majority of the present designs lack the ability to continuously record brain activity during electrical stimulation; hence they cannot fully monitor the treatment's effectiveness. This is due to the large stimulation artifacts that can saturate the sensitive readout circuits.

Improving the Accuracy of Spiking Neural Networks for Radar Gesture Recognition Through Preprocessing.

Event-based neural networks are currently being explored as efficient solutions for performing AI tasks at the extreme edge. To fully exploit their potential, event-based neural networks coupled to adequate preprocessing must be investigated. Within this context, we demonstrate a 4-b-weight spiking neural network (SNN) for radar gesture recognition, achieving a state-of-the-art 93% accuracy within only four processing time steps while using only one convolutional layer and two fully connected layers.

Power Efficiency Comparison of Event-Driven and Fixed-Rate Signal Conversion and Compression for Biomedical Applications.

Energy-constrained biomedical recording systems need power-efficient data converters and good signal compression in order to meet the stringent power consumption requirements of many applications. In literature today, typically a SAR ADC in combination with digital compression is used. Recently, alternative event-driven sampling techniques have been proposed that incorporate compression in the ADC, such as level-crossing A/D conversion.

An integrated multi-electrode-optrode array for in vitro optogenetics.

Modulation of a group of cells or tissue needs to be very precise in order to exercise effective control over the cell population under investigation. Optogenetic tools have already demonstrated to be of great value in the study of neuronal circuits and in neuromodulation. Ideally, they should permit very accurate resolution, preferably down to the single cell level.

Integral equations formulation of plasmonic transmission lines.

In this paper, a comprehensive integral equation formulation of plasmonic transmission lines is presented for the first time. Such lines are made up of a number of metallic strips with arbitrary shapes and dimensions immersed within a stack of planar dielectric or metallic layers. These lines support a number of propagating modes.

Carbon nanotube circuit integration up to sub-20 nm channel lengths.

Carbon nanotube (CNT) field-effect transistors (CNFETs) are a promising emerging technology projected to achieve over an order of magnitude improvement in energy-delay product, a metric of performance and energy efficiency, compared to silicon-based circuits. However, due to substantial imperfections inherent with CNTs, the promise of CNFETs has yet to be fully realized. Techniques to overcome these imperfections have yielded promising results, but thus far only at large technology nodes (1 μm device size).

Towards a noise prediction model for in vivo neural recording.

The signal-to-noise ratio of in vivo extracellular neural recordings with microelectrodes is influenced by many factors including the impedance of the electrode-tissue interface, the noise of the recording equipment and biological background noise from distant neurons. In this work we study the different noise sources affecting the quality of neural signals. We propose a simplified noise model as an analytical tool to predict the noise of an electrode given its geometrical dimensions and impedance characteristics.

Mixed-signal template-based reduction scheme for stimulus artifact removal in electrical stimulation.

Simultaneous electrical stimulation and recording are used to gain insights into the function of neuronal circuitry. However, artifacts produced by the electrical stimulation pulses prevent the recording of neural responses during, and a short period after, the stimulation duration. In this work, we describe a mixed-signal recording topology with template subtraction for removing the artifact during the stimulation pulse.

A multichannel integrated circuit for electrical recording of neural activity, with independent channel programmability.

Since a few decades, micro-fabricated neural probes are being used, together with microelectronic interfaces, to get more insight in the activity of neuronal networks. The need for higher temporal and spatial recording resolutions imposes new challenges on the design of integrated neural interfaces with respect to power consumption, data handling and versatility. In this paper, we present an integrated acquisition system for in vitro and in vivo recording of neural activity.

A third-order complementary metal-oxide-semiconductor sigma-delta modulator operating between 4.2 K and 300 K.

This paper presents a third-order switched-capacitor sigma-delta modulator implemented in a standard 0.35-μm CMOS process. It operates from 300 K down to 4.

Towards a closed-loop system for stimulation and recording: an in vitro approach with embryonic cardiomyocytes.

Closed loop systems, in which stimulation parameters are adjusted according to recorded signals would reduce the occurrence of side effects of stimulation and broaden current therapeutic options. As a step towards a closed-loop clinical system, we developed a single electrode stimulation / recording system for an in vitro microelectrode array. The system was used in vitro to simultaneously stimulate and record cardiac cells.

A cryogenic analog to digital converter operating from 300 K down to 4.4 K.

This paper presents a cryogenic successive approximation register (SAR) based analog to digital converter (ADC) implemented in a standard 0.35 microm complementary metal oxide semiconductor (CMOS) process. It operates from room temperature down to 4.