Deep learning-based spike sorting: a survey.

Deep learning is increasingly permeating neuroscience, leading to a rise in signal-processing applications for extracellular recordings. These signals capture the activity of small neuronal populations, necessitating 'spike sorting' to assign action potentials (spikes) to their underlying neurons. With the rise in publications delving into new methodologies and techniques for deep learning-based spike sorting, it is crucial to synthesise these findings critically.

Risk factors for older people re-presenting to the emergency department with falls: A case-control analysis.

Objective: Falls are a leading cause for ED presentations among older adults. Existing secondary falls prevention interventions have not been shown to decrease fall-related ED re-presentation, indicating a need to better understand contributing factors. Our aim was to evaluate risk factors for fall re-presentations among the older patient population presenting to the ED.

Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review.

Interfaces with peripheral nerves have been widely developed to enable bioelectronic control of neural activity. Peripheral nerve neuromodulation shows great potential in addressing motor dysfunctions, neurological disorders, and psychiatric conditions. The integration of high-density neural electrodes with stimulation and recording circuits poses a challenge in the design of neural interfaces.

A multi-channel stimulator with an active electrode array implant for vagal-cardiac neuromodulation studies.

Background: Implantable vagus nerve stimulation is a promising approach for restoring autonomic cardiovascular functions after heart transplantation. For successful treatment a system should have multiple electrodes to deliver precise stimulation and complex neuromodulation patterns.

Methods: This paper presents an implantable multi-channel stimulation system for vagal-cardiac neuromodulation studies in swine species.

An optogenetic cell therapy to restore control of target muscles in an aggressive mouse model of amyotrophic lateral sclerosis.

Breakdown of neuromuscular junctions (NMJs) is an early pathological hallmark of amyotrophic lateral sclerosis (ALS) that blocks neuromuscular transmission, leading to muscle weakness, paralysis and, ultimately, premature death. Currently, no therapies exist that can prevent progressive motor neuron degeneration, muscle denervation, or paralysis in ALS. Here, we report important advances in the development of an optogenetic, neural replacement strategy that can effectively restore innervation of severely affected skeletal muscles in the aggressive SOD1 mouse model of ALS, thus providing an interface to selectively control the function of targeted muscles using optical stimulation.

Neural Stimulation Hardware for the Selective Intrafascicular Modulation of the Vagus Nerve.

The neural stimulation of the vagus nerve is able to modulate various functions of the parasympathetic response in different organs. The stimulation of the vagus nerve is a promising approach to treating inflammatory diseases, obesity, diabetes, heart failure, and hypertension. The complexity of the vagus nerve requires highly selective stimulation, allowing the modulation of target-specific organs without side effects.

Efficient Approximation of Action Potentials with High-Order Shape Preservation in Unsupervised Spike Sorting.

This paper presents a novel approximation unit added to the conventional spike processing chain which provides an appreciable reduction of complexity of the high-hardware cost feature extractors. The use of the Taylor polynomial is proposed and modelled employing its cascaded derivatives to non-uniformly capture the essential samples in each spike for reliable feature extraction and sorting. Inclusion of the approximation unit can provide 3X compression (i.

Multimodal Diagnosis for Pulmonary Embolism from EHR Data and CT Images.

Pulmonary Embolism (PE) is a severe medical condition that can pose a significant risk to life. Traditional deep learning methods for PE diagnosis are based on Computed Tomography (CT) images and do not consider the patient's clinical context. To make full use of patient's clinical information, this article presents a multimodal fusion model ingesting Electronic Health Record (EHR) data and CT images for PE diagnosis.

Development of a Biosensor for fast point-of-care Blood Analysis of Troponin.

We present the development of novel tetrapolar EIS biosensor for the detect of troponin. Troponin has considerable diagnostic power and provide invaluable prognostic information for risk stratification. of acute coronary syndromes.

High Frame Rate Electrical Impedance Tomography System for Monitoring of Regional Lung Ventilation.

This paper describes the development of a compact high frame rate passive electrical impedance tomography system. The injected current amplitude and frequency can be adjusted to fit any EIT application. Measured results show that the system is capable of high frame rate of 89 fps and has power consumption of 1.

A Fully Implantable Opto-Electro Closed-Loop Neural Interface for Motor Neuron Disease Studies.

This paper presents a fully implantable closed-loop device for use in freely moving rodents to investigate new treatments for motor neuron disease. The 0.18 μm CMOS integrated circuit comprises 4 stimulators, each featuring 16 channels for optical and electrical stimulation using arbitrary current waveforms at frequencies from 1.

Insertion Guidance Based on Impedance Measurements of a Cochlear Electrode Array.

The cochlear implantable neuromodulator provides substantial auditory perception to those with severe or profound impaired hearing. Correct electrode array positioning in the cochlea is one of the important factors for quality hearing, and misplacement may lead to additional injury to the cochlea. Visual inspection of the progress of electrode insertion is limited and mainly relies on the surgeon's tactile skills, and there is a need to detect in real-time the electrode array position in the cochlea during insertion.

Cross-sectional chest circumference and shape development in infants.

Objective: This study investigates the development of the thoracic cross-section at the nipple line level during the early stages of life. Unlike the descriptive awareness regarding chest development course, there exist no quantitative references concerning shape, circumference and possible dependencies to age, gender or body weight. The proposed mathematical relations are expected to help create guidelines for more realistic modelling and potential detection of abnormalities.

A Multi-Channel Stimulator With High-Resolution Time-to-Current Conversion for Vagal-Cardiac Neuromodulation.

This paper presents a low power integrated multi-channel stimulator for a cardiac neuroprosthesis designed to restore the parasympathetic control after heart transplantation. The proposed stimulator is based on time-to-current conversion. It replaces the conventional current mode digital-to-analog converter (DAC) that uses tens of microamps for biasing, with a novel capacitor time-based DAC (CT-DAC) offering about 10-bit current amplitude resolution with a bias current of only 250 nA.

Generation of Anatomically Inspired Human Airway Tree Using Electrical Impedance Tomography: A Method to Estimate Regional Lung Filling Characteristics.

The purpose of lung recruitment is to improve and optimize the air exchange flow in the lungs by adjusting the respiratory settings during mechanical ventilation. Electrical impedance tomography (EIT) is a monitoring tool that permits measurement of regional pulmonary filling characteristics or filling index (FI) during ventilation. The conventional EIT system has limitations which compromise the accuracy of the FI.

Integrated Circuits for Medical Ultrasound Applications: Imaging and Beyond.

Medical ultrasound has become a crucial part of modern society and continues to play a vital role in the diagnosis and treatment of illnesses. Over the past decades, the development of medical ultrasound has seen extraordinary progress as a result of the tremendous research advances in microelectronics, transducer technology and signal processing algorithms. However, medical ultrasound still faces many challenges including power-efficient driving of transducers, low-noise recording of ultrasound echoes, effective beamforming in a non-linear, high-attenuation medium (human tissues) and reduced overall form factor.

Development of an in-line magnetometer for flow chemistry and its demonstration for magnetic nanoparticle synthesis.

Despite the wide usage of magnetic nanoparticles, it remains challenging to synthesise particles with properties that exploit each application's full potential. Time consuming experimental procedures and particle analysis hinder process development, which is commonly constrained to a handful of experiments without considering particle formation kinetics, reproducibility and scalability. Flow reactors are known for their potential of large-scale production and high-throughput screening of process parameters.

A Versatile Hermetically Sealed Microelectronic Implant for Peripheral Nerve Stimulation Applications.

This article presents a versatile neurostimulation platform featuring a fully implantable multi-channel neural stimulator for chronic experimental studies with freely moving large animal models involving peripheral nerves. The implant is hermetically sealed in a ceramic enclosure and encapsulated in medical grade silicone rubber, and then underwent active tests at accelerated aging conditions at 100°C for 15 consecutive days. The stimulator microelectronics are implemented in a 0.

Locating Functionalized Gold Nanoparticles Using Electrical Impedance Tomography.

Objective: An imaging device to locate functionalised nanoparticles, whereby therapeutic agents are transported from the site of administration specifically to diseased tissues, remains a challenge for pharmaceutical research. Here, we show a new method based on electrical impedance tomography (EIT) to provide images of the location of gold nanoparticles (GNPs) and the excitation of GNPs with radio frequencies (RF) to change impedance permitting an estimation of their location in cell models Methods: We have created an imaging system using quantum cluster GNPs as contrast agent, activated with RF fields to heat the functionalized GNPs, which causes a change in impedance in the surrounding region. This change is then identified with EIT.

An Imaged Based Method for Universal Performance Evaluation of Electrical Impedance Tomography Systems.

This paper describes a simple and reproducible method for universal evaluation of the performance of electrical impedance tomography (EIT) systems using reconstructed images. To address the issues where common electrical parameters are not directly related to the quality of EIT images, based on objective full reference (FR) image quality assessment, the method provides a visually distinguishable hot colormap and two new FR metrics, the global and the more specific 'region of interest'. A passive 16 electrode EIT system using an application specific integrated circuit front-end was used to evaluate the proposed method.

Thoracic shape changes in newborns due to their position.

The highly compliant nature of the neonatal chest wall is known to clinicians. However, its morphological changes have never been characterized and are especially important for a customised monitoring of respiratory diseases. Here, we show that a device applied on newborns can trace their chest boundary without the use of radiation.

Model Selection Based Algorithm in Neonatal Chest EIT.

This paper presents a new method for selecting a patient specific forward model to compensate for anatomical variations in electrical impedance tomography (EIT) monitoring of neonates. The method uses a combination of shape sensors and absolute reconstruction. It takes advantage of a probabilistic approach which automatically selects the best estimated forward model fit from pre-stored library models.

Dictionary selection for compressed sensing of EEG signals using sparse binary matrix and spatiotemporal sparse Bayesian learning.

Online monitoring of electroencephalogram (EEG) signals is challenging due to the high volume of data and power requirements. Compressed sensing (CS) may be employed to address these issues. Compressed sensing using a sparse binary matrix, owing to its low power features, and reconstruction/decompression using spatiotemporal sparse Bayesian learning have been shown to constitute a robust framework for fast, energy efficient and accurate multichannel bio-signal monitoring.

Time Stamp - A Novel Time-to-Digital Demodulation Method for Bioimpedance Implant Applications.

Bioimpedance analysis is a noninvasive and inexpensive technology used to investigate the electrical properties of biological tissues. The analysis requires demodulation to extract the real and imaginary parts of the impedance. Conventional systems use complex architectures such as I-Q demodulation.

A Framework for Adapting Deep Brain Stimulation Using Parkinsonian State Estimates.

The mechanisms underlying the beneficial effects of deep brain stimulation (DBS) for Parkinson's disease (PD) remain poorly understood and are still under debate. This has hindered the development of adaptive DBS (aDBS). For further progress in aDBS, more insight into the dynamics of PD is needed, which can be obtained using machine learning models.