A Real-Time Vital-Sign Monitoring in the Physical Domain on a Mixed-Signal Reconfigurable Platform.

This work presents a mixed-signal physical-compu-tation-electronics for monitoring three vital signs; namely heart rate, blood pressure, and blood oxygen saturation; from electrocardiography, arterial blood pressure, and photoplethysmography signals in real-time. The computational circuits are implemented on a reconfigurable and programmable signal-processing platform, namely field-programmable analog array (FPAA). The design leverages the core enabling technology of FPAA, namely floating-gate CMOS devices, and an on-chip low-power microcontroller to achieve energy-efficiency while not compromising accuracy.

Corrigendum: Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain.

[This corrects the article DOI: 10.3389/fnins.2018.

Long-Term Results of Acetabular Reconstruction Using Ganz Acetabular Rings.

Background: Our study examines the long-term results of acetabular reconstruction using the Ganz acetabular reinforcement ring (GRR) in total hip arthroplasty.

Methods: Between 1998 and 2001, 135 hips (119 revision and 16 primary arthroplasties) were consecutively implanted with a GRR at our hospital. The average age was 65 years (range, 26-90).

Hodgkin-Huxley Neuron and FPAA Dynamics.

We present the experimental silicon results on the dynamics of a Hodgkin-Huxley neuron implemented on a reconfigurable platform. The circuit has been inspired by the similarity between biology and silicon, by modeling ion channels and their time constants. Another significant motivation behind this paper is to make the system available to circuit designers as well as users in the neuroscience community.

Reconfigurable analog classifier for knee-joint rehabilitation.

We present a System-On-Chip Field Programmable Analog Array (FPAA) for analyzing and processing the signals off an accelerometer for a wearable joint health assessment device. FPAAs have been shown to compute with an efficiency of 1000 times, as well as area efficiencies of 100 times, more than digital solutions. This work presents a low power signal processing system which allows us to extract features from the output of the accelerometer.

Optimal sparse approximation with integrate and fire neurons.

Sparse approximation is a hypothesized coding strategy where a population of sensory neurons (e.g. V1) encodes a stimulus using as few active neurons as possible.

Compiling probabilistic, bio-inspired circuits on a field programmable analog array.

A FIELD PROGRAMMABLE ANALOG ARRAY (FPAA) IS PRESENTED AS AN ENERGY AND COMPUTATIONAL EFFICIENCY ENGINE: a mixed mode processor for which functions can be compiled at significantly less energy costs using probabilistic computing circuits. More specifically, it will be shown that the core computation of any dynamical system can be computed on the FPAA at significantly less energy per operation than a digital implementation. A stochastic system that is dynamically controllable via voltage controlled amplifier and comparator thresholds is implemented, which computes Bernoulli random variables.

Capacitive micromachined ultrasonic transducer arrays as tunable acoustic metamaterials.

Capacitive Micromachined Ultrasonic Transducers (CMUTs) operating in immersion support dispersive evanescent waves due to the subwavelength periodic structure of electrostatically actuated membranes in the array. Evanescent wave characteristics also depend on the membrane resonance which is modified by the externally applied bias voltage, offering a mechanism to tune the CMUT array as an acoustic metamaterial. The dispersion and tunability characteristics are examined using a computationally efficient, mutual radiation impedance based approach to model a finite-size array and realistic parameters of variation.

Single-chip CMUT-on-CMOS front-end system for real-time volumetric IVUS and ICE imaging.

Intravascular ultrasound (IVUS) and intracardiac echography (ICE) catheters with real-time volumetric ultrasound imaging capability can provide unique benefits to many interventional procedures used in the diagnosis and treatment of coronary and structural heart diseases. Integration of capacitive micromachined ultrasonic transducer (CMUT) arrays with front-end electronics in single-chip configuration allows for implementation of such catheter probes with reduced interconnect complexity, miniaturization, and high mechanical flexibility. We implemented a single-chip forward-looking (FL) ultrasound imaging system by fabricating a 1.

Neuron array with plastic synapses and programmable dendrites.

We describe a novel neuromorphic chip architecture that models neurons for efficient computation. Traditional architectures of neuron array chips consist of large scale systems that are interfaced with AER for implementing intra- or inter-chip connectivity. We present a chip that uses AER for inter-chip communication but uses fast, reconfigurable FPGA-style routing with local memory for intra-chip connectivity.

Finding a roadmap to achieve large neuromorphic hardware systems.

Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techniques are reaching physical limits. These silicon systems mimic extremely energy efficient neural computing structures, potentially both for solving engineering applications as well as understanding neural computation. Toward this end, the authors provide a glimpse at what the technology evolution roadmap looks like for these systems so that Neuromorphic engineers may gain the same benefit of anticipation and foresight that IC designers gained from Moore's law many years ago.