A shortened surface electromyography recording is sufficient to facilitate home fasciculation assessment.

INTRODUCTION/AIMS: Fasciculations are an early clinical hallmark of amyotrophic lateral sclerosis (ALS), amenable to detection by high-density surface electromyography (HDSEMG). In conjunction with the Surface Potential Quantification Engine (SPiQE), HDSEMG offers improved spatial resolution for the analysis of fasciculations. This study aims to establish an optimal recording duration to enable longitudinal remote monitoring in the home. METHODS: Twenty patients with ALS and five patients with benign fasciculation syndrome (BFS) underwent serial 30 min HDSEMG recordings from biceps brachii and gastrocnemii. SPiQE was independently applied to abbreviated epochs within each 30-min recording (0-5, 0-10, 0-15, 0-20, and 0-25 min), outputting fasciculation frequency, amplitude median and amplitude interquartile range. Bland-Altman plots and intraclass correlation coefficients (ICC) were used to assess agreement with the validated 30-min recording. RESULTS: In total, 506 full recordings were included. The 5 min recordings demonstrated diverse and relatively poor agreement with the 30 min baselines across all parameters, muscles and patient groups (ICC = 0.32-0.86). The 15-min recordings provided more acceptable and stable agreement (ICC = 0.78-0.98), which did not substantially improve in longer recordings. DISCUSSION: For the detection and quantification of fasciculations in patients with ALS and BFS, HDSEMG recordings can be halved from 30 to 15 min without significantly compromising the primary outputs. Reliance on a shorter recording duration should lead to improved tolerability and repeatability among patients, facilitating longitudinal remote monitoring in patients' homes.

Fiber-Based Electrochemical Biosensors for Monitoring pH and Transient Neurometabolic Lactate.

Developing tools that are able to monitor transient neurochemical dynamics is important to decipher brain chemistry and function. Multifunctional polymer-based fibers have been recently applied to monitor and modulate neural activity. Here, we explore the potential of polymer fibers comprising six graphite-doped electrodes and two microfluidic channels within a flexible polycarbonate body as a platform for sensing pH and neurometabolic lactate. Electrodes were made into potentiometric sensors (responsive to pH) or amperometric sensors (lactate biosensors). The growth of an iridium oxide layer made the fiber electrodes responsive to pH in a physiologically relevant range. Lactate biosensors were fabricated via platinum black growth on the fiber electrode, followed by an enzyme layer, making them responsive to lactate concentration. Lactate fiber biosensors detected transient neurometabolic lactate changes in an in vivo mouse model. Lactate concentration changes were associated with spreading depolarizations, known to be detrimental to the injured brain. Induced waves were identified by a signature lactate concentration change profile and measured as having a speed of ∼2.7 mm/min (n = 4 waves). Our work highlights the potential applications of fiber-based biosensors for direct monitoring of brain metabolites in the context of injury.

Development and Evaluation of a Method for Automated Detection of Spreading Depolarizations in the Injured Human Brain.

BACKGROUND: Spreading depolarizations (SDs) occur in some 60% of patients receiving intensive care following severe traumatic brain injury and often occur at a higher incidence following serious subarachnoid hemorrhage and malignant hemisphere stroke (MHS); they are independently associated with worse clinical outcome. Detection of SDs to guide clinical management, as is now being advocated, currently requires continuous and skilled monitoring of the electrocorticogram (ECoG), frequently extending over many days. METHODS: We developed and evaluated in two clinical intensive care units (ICU) a software routine capable of detecting SDs both in real time at the bedside and retrospectively and also capable of displaying patterns of their occurrence with time. We tested this prototype software in 91 data files, each of approximately 24 h, from 18 patients, and the results were compared with those of manual assessment ("ground truth") by an experienced assessor blind to the software outputs. RESULTS: The software successfully detected SDs in real time at the bedside, including in patients with clusters of SDs. Counts of SDs by software (dependent variable) were compared with ground truth by the investigator (independent) using linear regression. The slope of the regression was 0.7855 (95% confidence interval 0.7149-0.8561); a slope value of 1.0 lies outside the 95% confidence interval of the slope, representing significant undersensitivity of 79%. R2 was 0.8415. CONCLUSIONS: Despite significant undersensitivity, there was no additional loss of sensitivity at high SD counts, thus ensuring that dense clusters of depolarizations of particular pathogenic potential can be detected by software and depicted to clinicians in real time and also be archived.

Real-time neurochemical measurement of dynamic metabolic events during cardiac arrest and resuscitation in a porcine model.

This work describes a fully-integrated portable microfluidic analysis system for real-time monitoring of dynamic changes in glucose and lactate occurring in the brain as a result of cardiac arrest and resuscitation. Brain metabolites are sampled using FDA-approved microdialysis probes and coupled to a high-temporal resolution 3D printed microfluidic chip housing glucose and lactate biosensors. The microfluidic biosensors are integrated with a wireless 2-channel potentiostat forming a compact analysis system that is ideal for use in a crowded operating theatre. Data are transmitted to a custom-written app running on a tablet for real-time visualisation of metabolic trends. In a proof-of-concept porcine model of cardiac arrest, the integrated analysis system proved reliable in a challenging environment resembling a clinical setting; noise levels were found to be comparable with those seen in the lab and were not affected by major clinical interventions such as defibrillation of the heart. Using this system, we were able, for the first time, to measure changes in brain glucose and lactate levels caused by cardiac arrest and resuscitation; the system was sensitive to clinical interventions such as infusion of adrenaline. Trends suggest that cardiopulmonary resuscitation alone does not meet the high energy demands of the brain as metabolite levels only return to their values preceding cardiac arrest upon return of spontaneous circulation.

What Should a Clinician Do When Spreading Depolarizations are Observed in a Patient?

The International Conference on Spreading Depolarizations (iCSD) held in Boca Raton, Florida, in the September of 2018 devoted a section to address the question, "What should a clinician do when spreading depolarizations are observed in a patient?" Discussants represented a wide range of expertise, including neurologists, neurointensivists, neuroradiologists, neurosurgeons, and pre-clinical neuroscientists, to provide both clinical and basic pathophysiology perspectives. A draft summary of viewpoints offered was then written by a multidisciplinary writing group of iCSD members, based on a transcript of the session. Feedback of all discussants was formally collated, reviewed, and incorporated into the final document which was subsequently approved by all authors.

Traumatic brain injury neuroelectrochemical monitoring: behind-the-ear micro-instrument and cloud application.

BACKGROUND: Traumatic Brain Injury (TBI) is a leading cause of fatality and disability worldwide, partly due to the occurrence of secondary injury and late interventions. Correct diagnosis and timely monitoring ensure effective medical intervention aimed at improving clinical outcome. However, due to the limitations in size and cost of current ambulatory bioinstruments, they cannot be used to monitor patients who may still be at risk of secondary injury outside the ICU. METHODS: We propose a complete system consisting of a wearable wireless bioinstrument and a cloud-based application for real-time TBI monitoring. The bioinstrument can simultaneously record up to ten channels including both ECoG biopotential and neurochemicals (e.g. potassium, glucose and lactate), and supports various electrochemical methods including potentiometry, amperometry and cyclic voltammetry. All channels support variable gain programming to automatically tune the input dynamic range and address biosensors' falling sensitivity. The instrument is flexible and can be folded to occupy a small space behind the ear. A Bluetooth Low-Energy (BLE) receiver is used to wirelessly connect the instrument to a cloud application where the recorded data is stored, processed and visualised in real-time. Bench testing has been used to validate device performance. RESULTS: The instrument successfully monitored spreading depolarisations (SDs) - reproduced using a signal generator - with an SNR of 29.07 dB and NF of 0.26 dB. The potentiostat generates a wide voltage range from -1.65V to +1.65V with a resolution of 0.8mV and the sensitivity of the amperometric AFE was verified by recording 5 pA currents. Different potassium, glucose and lactate concentrations prepared in lab were accurately measured and their respective working curves were constructed. Finally,the instrument achieved a maximum sampling rate of 1.25 ksps/channel with a throughput of 105 kbps. All measurements were successfully received at the cloud. CONCLUSION: The proposed instrument uniquely positions itself by presenting an aggressive optimisation of size and cost while maintaining high measurement accuracy. The system can effectively extend neuroelectrochemical monitoring to all TBI patients including those who are mobile and those who are outside the ICU. Finally, data recorded in the cloud application could be used to help diagnosis and guide rehabilitation.

Portable Microfluidic Biosensing System for Real-Time Analysis of Microdialysate in Transplant Kidneys.

Currently, there is a severe shortage of donor kidneys that are fit for transplantation, due in part to a lack of adequate viability assessment tools for transplant organs. This work presents the integration of a novel wireless two-channel amperometric potentiostat with microneedle-based glucose and lactate biosensors housed in a 3D printed chip to create a microfluidic biosensing system that is genuinely portable. The wireless potentiostat transmits data via Bluetooth to an Android app running on a tablet. The whole miniaturized system is fully enclosed and can be integrated with microdialysis to allow continuous monitoring of tissue metabolite levels in real time. We have also developed a wireless portable automated calibration platform so that biosensors can be calibrated away from the laboratory and in transit. As a proof of concept, we have demonstrated the use of this portable analysis system to monitor porcine kidneys for the first time from organ retrieval, through warm ischemia, transportation on ice, right through to cold preservation and reperfusion. The portable system is robust and reliable in the challenging conditions of the abattoir and during kidney transportation and can detect clear physiological changes in the organ associated with clinical interventions.

A High-Performance Application Specific Integrated Circuit for Electrical and Neurochemical Traumatic Brain Injury Monitoring.

This paper presents the first application specific integrated chip (ASIC) for the monitoring of patients who have suffered a Traumatic Brain Injury (TBI). By monitoring the neurophysiological (ECoG) and neurochemical (glucose, lactate and potassium) signals of the injured human brain tissue, it is possible to detect spreading depolarisations, which have been shown to be associated with poor TBI patient outcome. This paper describes the testing of a new 7.5 mm2 ASIC fabricated in the commercially available AMS 0.35 µm CMOS technology. The ASIC has been designed to meet the demands of processing the injured brain tissue's ECoG signals, recorded by means of depth or brain surface electrodes, and neurochemical signals, recorded using microdialysis coupled to microfluidics-based electrochemical biosensors. The potentiostats use switchedcapacitor charge integration to record currents with 100 fA resolution, and allow automatic gain changing to track the falling sensitivity of a biosensor. This work supports the idea of a "behind the ear" wireless microplatform modality, which could enable the monitoring of currently non-monitored mobile TBI patients for the onset of secondary brain injury.

Comparison of synthetic aperture architectures for miniaturised ultrasound imaging front-ends.

BACKGROUND: Point of care ultrasonography has been the focus of extensive research over the past few decades. Miniaturised, wireless systems have been envisaged for new application areas, such as capsule endoscopy, implantable ultrasound and wearable ultrasound. The hardware constraints of such small-scale systems are severe, and tradeoffs between power consumption, size, data bandwidth and cost must be carefully balanced. METHODS: In this work, two receiver architectures are proposed and compared to address these challenges. Both architectures uniquely combine low-rate sampling with synthetic aperture beamforming to reduce the data bandwidth and system complexity. The first architecture involves the use of quadrature sampling to minimise the signal bandwidth and computational load. Synthetic aperture beamforming (SAB) is carried out using a single-channel, pipelined protocol suitable for implementation on an FPGA/ASIC. The second architecture employs compressive sensing within the finite rate of innovation framework to further reduce the bandwidth. Low-rate signals are transmitted to a computational back-end (computer), which sequentially reconstructs each signal and carries out beamforming. RESULTS: Both architectures were tested using a custom hardware front-end and synthetic aperture database to yield B-mode images. The normalised root-mean-squared-error between the quadrature SAB image and the RF reference image was [Formula: see text] while the compressive SAB error was [Formula: see text] for the same degree of spatial compounding. The sampling rate is reduced by a factor of 2 (quadrature SAB) and 4.7 (compressive SAB), compared to the RF sampling rate. The quadrature method is implemented on FPGA, with a total power consumption of [Formula: see text] mW, which is comparable to state-of-the-art hardware topologies, but with significantly reduced circuit area. CONCLUSIONS: Through a novel combination of SAB and low-rate sampling techniques, the proposed architectures achieve a significant reduction in data transmission rate, system complexity and digital/analogue circuit area. This allows for aggressive miniaturisation of the imaging front-end in portable imaging applications.

Real-time detection of carboplatin using a microfluidic system.

A microfluidic sensor system based on a carbon nanotube-epoxy composite electrode was fabricated to allow detection of the presence of the anti-cancer drug carboplatin in healthy tissue in real time during chemotherapy. Detection of carboplatin was carried out by observing the effects of the drug on the differential pulse voltammetry of free purine bases using a novel carbon nanotube-epoxy composite electrode. In free solution these electrodes performed better than glassy carbon electrodes for oxidation of the free purine bases AMP and GMP, and than DNA-modified carbon nanotube-epoxy composite sensors for detection of carboplatin. On-line carboplatin detection was performed using a computer-controlled microfluidic platform. The methodology for on-line carboplatin detection was optimised in terms of the analysis time and to allow repeated carboplatin measurement using the same electrode. Microdialysis sampling and our microfluidic platform were combined to give a proof-of-concept system for real-time carboplatin detection with a limit of detection of 0.014 µM carboplatin in the sampled media. This paper is dedicated to Craig Lunte's pioneering work in analysis and microdialysis.

3D Printed Microfluidic Device with Integrated Biosensors for Online Analysis of Subcutaneous Human Microdialysate.

This work presents the design, fabrication, and characterization of a robust 3D printed microfluidic analysis system that integrates with FDA-approved clinical microdialysis probes for continuous monitoring of human tissue metabolite levels. The microfluidic device incorporates removable needle type integrated biosensors for glucose and lactate, which are optimized for high tissue concentrations, housed in novel 3D printed electrode holders. A soft compressible 3D printed elastomer at the base of the holder ensures a good seal with the microfluidic chip. Optimization of the channel size significantly improves the response time of the sensor. As a proof-of-concept study, our microfluidic device was coupled to lab-built wireless potentiostats and used to monitor real-time subcutaneous glucose and lactate levels in cyclists undergoing a training regime.

Detection of spreading depolarization with intraparenchymal electrodes in the injured human brain.

BACKGROUND: Spreading depolarization events following ischemic and traumatic brain injury are associated with poor patient outcome. Currently, monitoring these events is limited to patients in whom subdural electrodes can be placed at open craniotomy. This study examined whether these events can be detected using intra-cortical electrodes, opening the way for electrode insertion via burr hole. METHODS: Animal work was carried out on adult Sprague-Dawley rats in a laboratory setting to investigate the feasibility of recording depolarization events. Subsequently, 8 human patients requiring craniotomy for traumatic brain injury or aneurysmal subarachnoid hemorrhage were monitored for depolarization events in an intensive care setting with concurrent strip (subdural) and depth (intra-parenchymal) electrode recordings. RESULTS: (1) Depolarization events can be reliably detected from intra-cortically placed electrodes. (2) A reproducible slow potential change (SPC) waveform morphology was identified from intra-cortical electrodes on the depth array. (3) The depression of cortical activity known to follow depolarization events was identified consistently from both intra-cortical and sub-cortical electrodes on the depth array. CONCLUSIONS: Intra-parenchymally sited electrodes can be used to consistently identify depolarization events in humans. This technique greatly extends the capability of monitoring for spreading depolarization events in injured patients, as electrodes can be sited without the need for craniotomy. The method provides a new investigative tool for the evaluation of the contribution of these events to secondary brain injury in human patients.

Real-Time Non-Invasive Imaging and Detection of Spreading Depolarizations through EEG: An Ultra-Light Explainable Deep Learning Approach.

A core aim of neurocritical care is to prevent secondary brain injury. Spreading depolarizations (SDs) have been identified as an important independent cause of secondary brain injury. SDs are usually detected using invasive electrocorticography recorded at high sampling frequency. Recent pilot studies suggest a possible utility of scalp electrodes generated electroencephalogram (EEG) for non-invasive SD detection. However, noise and attenuation of EEG signals makes this detection task extremely challenging. Previous methods focus on detecting temporal power change of EEG over a fixed high-density map of scalp electrodes, which is not always clinically feasible. Having a specialized spectrogram as an input to the automatic SD detection model, this study is the first to transform SD identification problem from a detection task on a 1-D time-series wave to a task on a sequential 2-D rendered imaging. This study presented a novel ultra-light-weight multi-modal deep-learning network to fuse EEG spectrogram imaging and temporal power vectors to enhance SD identification accuracy over each single electrode, allowing flexible EEG map and paving the way for SD detection on ultra-low-density EEG with variable electrode positioning. Our proposed model has an ultra-fast processing speed (<0.3 sec). Compared to the conventional methods (2 hours), this is a huge advancement towards early SD detection and to facilitate instant brain injury prognosis. Seeing SDs with a new dimension - frequency on spectrograms, we demonstrated that such additional dimension could improve SD detection accuracy, providing preliminary evidence to support the hypothesis that SDs may show implicit features over the frequency profile.

Ultrasensitive detection of dopamine using a carbon nanotube network microfluidic flow electrode.

The electrochemical measurement of dopamine (DA), in phosphate buffer solution (pH 7.4), with a limit of detection (LOD) of ∼5 pM in 50 µL (∼ 250 attomol) is achieved using a band electrode comprised of a sparse network of pristine single-walled carbon nanotubes (SWNTs), which covers <1% of the insulating substrate. The SWNT electrodes are deployed as amperometric (anodic) detectors in microfluidic cells, produced by microstereolithography, designed specifically for flow injection analysis (FIA). The flow cells, have a channel (duct) geometry, with cell height of 25 µm, and are shown to be hydrodynamically well-defined, with laminar Poiseuille flow. In the arrangement where solution continuously flows over the electrode but the electrode is only exposed to the analyte for short periods of time, the SWNT electrodes do not foul and can be used repeatedly for many months. The LOD for dopamine (DA), reported herein, is significantly lower than previous reports using FIA-electrochemical detection. Furthermore, the SWNT electrodes can be used as grown, i.e., they do not require chemical modification or cleanup. The extremely low background signals of the SWNT electrodes, as a consequence of the sparse surface coverage and the low intrinsic capacitance of the SWNTs, means that no signal processing is required to measure the low currents for DA oxidation at trace levels. DA detection in artificial cerebral fluid is also possible with a LOD of ∼50 pM in 50 µL (∼2.5 fmol).

Dexamethasone-Enhanced Continuous Online Microdialysis for Neuromonitoring of O2 after Brain Injury.

Traumatic brain injury (TBI) is a major public health crisis in many regions of the world. Severe TBI may cause a primary brain lesion with a surrounding penumbra of tissue that is vulnerable to secondary injury. Secondary injury presents as progressive expansion of the lesion, possibly leading to severe disability, a persistent vegetive state, or death. Real time neuromonitoring to detect and monitor secondary injury is urgently needed. Dexamethasone-enhanced continuous online microdialysis (Dex-enhanced coMD) is an emerging paradigm for chronic neuromonitoring after brain injury. The present study employed Dex-enhanced coMD to monitor brain K+ and O2 during manually induced spreading depolarization in the cortex of anesthetized rats and after controlled cortical impact, a widely used rodent model of TBI, in behaving rats. Consistent with prior reports on glucose, O2 exhibited a variety of responses to spreading depolarization and a prolonged, essentially permanent decline in the days after controlled cortical impact. These findings confirm that Dex-enhanced coMD delivers valuable information regarding the impact of spreading depolarization and controlled cortical impact on O2 levels in the rat cortex.

Optimisation of a microfluidic analysis chamber for the placement of microelectrodes.

The behaviour of droplets entering a microfluidic chamber designed to house microelectrode detectors for real time analysis of clinical microdialysate is described. We have designed an analysis chamber to collect the droplets produced by multiphase flows of oil and artificial cerebral spinal fluid. The coalescence chamber creates a constant aqueous environment ideal for the placement of microelectrodes avoiding the contamination of the microelectrode surface by oil. A stream of alternating light and dark coloured droplets were filmed as they passed through the chamber using a high speed camera. Image analysis of these videos shows the colour change evolution at each point along the chamber length. The flow in the chamber was simulated using the general solution for Poiseuille flow in a rectangular chamber. It is shown that on the centre line the velocity profile is very close to parabolic, and an expression is presented for the ratio between this centre line velocity and the mean flow velocity as a function of channel aspect ratio. If this aspect ratio of width/height is 2, the ratio of flow velocities closely matches that of Poiseuille flow in a circular tube, with implications for connections between microfluidic channels and connection tubing. The droplets are well mixed as the surface tension at the interface with the oil dominates the viscous forces. However once the droplet coalesces with the solution held in the chamber, the no-slip condition at the walls allows Poiseuille flow to take over. The meniscus at the back of the droplet continues to mix the droplet and acts as a piston until the meniscus stops moving. We have found that the no-slip conditions at the walls of the chamber, create a banding effect which records the history of previous drops. The optimal position for sensors is to be placed at the plane of droplet coalescence ideally at the centre of the channel, where there is an abrupt concentration change leading to a response time ≪16 ms, the compressed frame rate of the video. Further away from this point the response time and sensitivity decrease due to convective dispersion.

Validation of Dexamethasone-Enhanced Continuous-Online Microdialysis for Monitoring Glucose for 10 Days after Brain Injury.

Traumatic brain injury (TBI) induces a pathophysiologic state that can be worsened by secondary injury. Monitoring brain metabolism with intracranial microdialysis can provide clinical insights to limit secondary injury in the days following TBI. Recent enhancements to microdialysis include the implementation of continuously operating electrochemical biosensors for monitoring the dialysate sample stream in real time and dexamethasone retrodialysis to mitigate the tissue response to probe insertion. Dexamethasone-enhanced continuous-online microdialysis (Dex-enhanced coMD) records long-lasting declines of glucose after controlled cortical impact in rats and TBI in patients. The present study employed retrodialysis and fluorescence microscopy to investigate the mechanism responsible for the decline of dialysate glucose after injury of the rat cortex. Findings confirm the long-term functionality of Dex-enhanced coMD for monitoring brain glucose after injury, demonstrate that intracranial glucose microdialysis is coupled to glucose utilization in the tissues surrounding the probes, and validate the conclusion that aberrant glucose utilization drives the postinjury glucose decline.

The rise and fall of fasciculations in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis is a devastating neurodegenerative disease with a median survival of 3 years from symptom onset. Accessible and reliable biomarkers of motor neuron decline are urgently needed to quicken the pace of drug discovery. Fasciculations represent an early pathophysiological hallmark of amyotrophic lateral sclerosis and can be reliably detected by high-density surface electromyography. We set out to quantify fasciculation potentials prospectively over 14 months, seeking comparisons with established markers of disease progression. Twenty patients with amyotrophic lateral sclerosis and five patients with benign fasciculation syndrome underwent up to seven assessments each. At each assessment, we performed the amyotrophic lateral sclerosis-functional rating scale, sum power score, slow vital capacity, 30-min high-density surface electromyography recordings from biceps and gastrocnemius and the motor unit number index. We employed the Surface Potential Quantification Engine, which is an automated analytical tool to detect and characterize fasciculations. Linear mixed-effect models were employed to account for the pseudoreplication of serial measurements. The amyotrophic lateral sclerosis-functional rating scale declined by 0.65 points per month (P < 0.0001), 35% slower than average. A total of 526 recordings were analysed. Compared with benign fasciculation syndrome, biceps fasciculation frequency in amyotrophic lateral sclerosis was 10 times greater in strong muscles and 40 times greater in weak muscles. This was coupled with a decline in fasciculation frequency among weak muscles of -7.6/min per month (P = 0.003), demonstrating the rise and fall of fasciculation frequency in biceps muscles. Gastrocnemius behaved differently, whereby strong muscles in amyotrophic lateral sclerosis had fasciculation frequencies five times greater than patients with benign fasciculation syndrome while weak muscles were increased by only 1.5 times. Gastrocnemius demonstrated a significant decline in fasciculation frequency in strong muscles (2.4/min per month, P < 0.0001), which levelled off in weak muscles. Fasciculation amplitude, an easily quantifiable surrogate of the reinnervation process, was highest in the biceps muscles that transitioned from strong to weak during the study. Pooled analysis of >900 000 fasciculations revealed inter-fasciculation intervals <100 ms in the biceps of patients with amyotrophic lateral sclerosis, particularly in strong muscles, consistent with the occurrence of doublets. We hereby present the most comprehensive longitudinal quantification of fasciculation parameters in amyotrophic lateral sclerosis, proposing a unifying model of the interactions between motor unit loss, muscle power and fasciculation frequency. The latter showed promise as a disease biomarker with linear rates of decline in strong gastrocnemius and weak biceps muscles, reflecting the motor unit loss that drives clinical progression.