A miniaturized wash-free microfluidic assay for electrical impedance-based assessment of red blood cell-mediated microvascular occlusion.

The production of HbS - an abnormal hemoglobin (Hb) - in sickle cell disease (SCD) results in poorly deformable red blood cells (RBCs) that are prone to microcapillary occlusion, causing tissue ischemia and organ damage. Novel treatments, including gene therapy, may reduce SCD morbidity, but methods to functionally evaluate RBCs remain limited. Previously, we presented the microfluidic impedance red cell assay (MIRCA) for rapid assessment of RBC deformability, employing electrical impedance-based readout to measure RBC occlusion of progressively narrowing micropillar openings. We describe herein the design, development, validation, and clinical utility of the next-generation MIRCA assay, featuring enhanced portability, rapidity, and usability. It incorporates a miniaturized impedance analyzer and features a simplified wash-free operation that yields an occlusion index (OI) within 15 min as a new metric for RBC occlusion. We show a correlation between OI and percent fetal hemoglobin (%HbF), other laboratory biomarkers of RBC hemolysis, and SCD severity. To demonstrate the assay's versatility, we tested RBC samples from treatment-naïve SCD patients in Uganda that yielded OI levels similar to those from hydroxyurea (HU)-treated patients in the U.S., highlighting the role of %HbF in protecting against microcapillary occlusion independent of other pharmacological effects. The MIRCA assay could also identify a subset of HU-treated patients with high occlusion risks, suggesting that they may require treatment adjustments including a second-line therapy to improve their outcomes. This work demonstrates the potential of the MIRCA assay for accelerated evaluation of RBC health, function, and therapeutic effect in an ex vivo model of the microcapillary networks.

Demographic Information Fusion Using Attentive Pooling In CNN-GRU Model For Systolic Blood Pressure Estimation.

Fusing demographic information into deep learning models has become of interest in recent end-to-end cuff-less blood pressure (BP) estimation studies in order to achieve improved performance. Conventionally, the demographic feature vector is concatenated with the pooled embedding vector. Here, using an attention-based convolutional neural network-gated recurrent unit (CNN-GRU), we present a new approach and fuse the demographic information into the attentive pooling module. Our results demonstrate that, under calibration-based testing protocol, the proposed approach provides improved systolic blood pressure (SBP) estimation accuracy (with R2=0.86 and mean absolute error (MAE)=4.90 mmHg) compared to both the baseline model with no demographic information fused, and the conventional approach of fusing demographic information. Our work showcases the feasibility of using attention-based methods to combine demographic features with deep learning models, and suggests new ways for fusing demographic information in deep learning models to achieve improved BP estimation accuracy.

A Multichannel Portable Platform With Embedded Thermal Management for Miniaturized Dielectric Blood Coagulometry.

This article presents a standalone, multichannel, miniaturized impedance analyzer (MIA) system for dielectric blood coagulometry measurements with a microfluidic sensor termed ClotChip. The system incorporates a front-end interface board for 4-channel impedance measurements at an excitation frequency of 1 MHz, an integrated resistive heater formed by a pair of printed-circuit board (PCB) traces to keep the blood sample near a physiologic temperature of 37 °C, a software-defined instrument module for signal generation and data acquisition, and a Raspberry Pi-based embedded computer with 7-inch touchscreen display for signal processing and user interface. When measuring fixed test impedances across all four channels, the MIA system exhibits an excellent agreement with a benchtop impedance analyzer, with rms errors of ≤0.30% over a capacitance range of 47-330 pF and ≤0.35% over a conductance range of 2.13-10 mS. Using in vitro-modified human whole blood samples, the two ClotChip output parameters, namely, the time to reach a permittivity peak (Tpeak) and maximum change in permittivity after the peak (Δϵr,max) are assessed by the MIA system and benchmarked against the corresponding parameters of a rotational thromboelastometry (ROTEM) assay. Tpeak exhibits a very strong positive correlation (r = 0.98, p < 10-6, n = 20) with the ROTEM clotting time (CT) parameter, while Δϵr,max exhibits a very strong positive correlation (r = 0.92, p < 10-6, n = 20) with the ROTEM maximum clot firmness (MCF) parameter. This work shows the potential of the MIA system as a standalone, multichannel, portable platform for comprehensive assessment of hemostasis at the point-of-care/point-of-injury (POC/POI).

Bioelectronic Sensor Nodes for the Internet of Bodies.

Energy-efficient sensing with physically secure communication for biosensors on, around, and within the human body is a major area of research for the development of low-cost health care devices, enabling continuous monitoring and/or secure perpetual operation. When used as a network of nodes, these devices form the Internet of Bodies, which poses challenges including stringent resource constraints, simultaneous sensing and communication, and security vulnerabilities. Another major challenge is to find an efficient on-body energy-harvesting method to support the sensing, communication, and security submodules. Due to limitations in the amount of energy harvested, we require a reduction in energy consumed per unit information, making the use of in-sensor analytics and processing imperative. In this article, we review the challenges and opportunities of low-power sensing, processing, and communication with possible powering modalities for future biosensor nodes. Specifically, we analyze, compare, and contrast (a) different sensing mechanisms such as voltage/current domain versus time domain, (b) low-power, secure communication modalities including wireless techniques and human body communication, and (c) different powering techniques for wearable devices and implants.

Broad Therapeutic Time Window for Driving Motor Recovery After TBI Using Activity-Dependent Stimulation.

BACKGROUND: After an acquired injury to the motor cortex, the ability to generate skilled movements is impaired, leading to long-term motor impairment and disability. While rehabilitative therapy can improve outcomes in some individuals, there are no treatments currently available that are able to fully restore lost function. OBJECTIVE: We previously used activity-dependent stimulation (ADS), initiated immediately after an injury, to drive motor recovery. The objective of this study was to determine if delayed application of ADS would still lead to recovery and if the recovery would persist after treatment was stopped. METHODS: Rats received a controlled cortical impact over primary motor cortex, microelectrode arrays were implanted in ipsilesional premotor and somatosensory areas, and a custom brain-machine interface was attached to perform the ADS. Stimulation was initiated either 1, 2, or 3 weeks after injury and delivered constantly over a 4-week period. An additional group was monitored for 8 weeks after terminating ADS to assess persistence of effect. Results were compared to rats receiving no stimulation. RESULTS: ADS was delayed up to 3 weeks from injury onset and still resulted in significant motor recovery, with maximal recovery occurring in the 1-week delay group. The improvements in motor performance persisted for at least 8 weeks following the end of treatment. CONCLUSIONS: ADS is an effective method to treat motor impairments following acquired brain injury in rats. This study demonstrates the clinical relevance of this technique as it could be initiated in the post-acute period and could be explanted/ceased once recovery has occurred.

Design and Optimization of Capacitive Links for Wireless Power Transfer to Biomedical Implants.

This paper provides a comprehensive overview of capacitive wireless power transfer (C-WPT) links for biomedical implants, and proposes an algorithmic approach to optimize their design for a theoretically feasible desired power transmission efficiency (PTE). Two C-WPT links, one involving external inductors for parasitic capacitance cancellation, and another without external inductors are presented. An accurate electrical model has been presented for both cases considering the finite conductivity of the body tissue and fringe fields emanated from the metallic plates. Ex-vivo experiments were conducted with beef tissue to demonstrate the viability of the model and the optimization algorithm. The analytical and simulation results show good agreement with the measurement (with real tissue) for both types of links across a wide range of operating frequency, including one with the highest reported frequency (∼14.6 MHz) among tuned links.

The Effects of Filtering PPG Signal on Pulse Arrival Time-Systolic Blood Pressure Correlation.

Pulse arrival time (PAT), evaluated from electro-cardiogram (ECG) and photoplethysmogram (PPG) signals, has been widely used for cuff-less blood pressure (BP) estimation due to its high correlation with BP. However, the question of whether filtering the PPG signal impacts the extracted PAT values and consequently, the correlation between PAT and BP, has not been investigated before. In this paper, using data from 18 subjects, changes in the PAT values, and in the subject-specific PAT-systolic BP (SBP) correlation caused by filtering the PPG signal with variable cutoff frequencies in the range of 2 to 15 Hz are studied. For PAT extraction, three PPG characteristic points (foot, maximum slope and systolic peak) are considered. Results show that differences in the cutoff frequency can shift the PAT values and introduce a worst-case error of over 8.2 mmHg for SBP estimation, indicating that PPG signal filter settings can impact PAT-based BP estimations. Our study suggests that extracting the PAT from the maximum slope point of PPG signal filtered at 10 Hz provides the most stable correlation with SBP.

Assessment of fibrinolytic status in whole blood using a dielectric coagulometry microsensor.

Rapid assessment of the fibrinolytic status in whole blood at the point-of-care/point-of-injury (POC/POI) is clinically important to guide timely management of uncontrolled bleeding in patients suffering from hyperfibrinolysis after a traumatic injury. In this work, we present a three-dimensional, parallel-plate, capacitive sensor - termed ClotChip - that measures the temporal variation in the real part of blood dielectric permittivity at 1 MHz as the sample undergoes coagulation within a microfluidic channel with <10 µL of total volume. The ClotChip sensor features two distinct readout parameters, namely, lysis time (LT) and maximum lysis rate (MLR) that are shown to be sensitive to the fibrinolytic status in whole blood. Specifically, LT identifies the time that it takes from the onset of coagulation for the fibrin clot to mostly dissolve in the blood sample during fibrinolysis, whereas MLR captures the rate of fibrin clot lysis. Our findings are validated through correlative measurements with a rotational thromboelastometry (ROTEM) assay of clot viscoelasticity, qualitative/quantitative assessments of clot stability, and scanning electron microscope imaging of clot ultrastructural changes, all in a tissue plasminogen activator (tPA)-induced fibrinolytic environment. Moreover, we demonstrate the ClotChip sensor ability to detect the hemostatic rescue that occurs when the tPA-induced upregulated fibrinolysis is inhibited by addition of tranexamic acid (TXA) - a potent antifibrinolytic drug. This work demonstrates the potential of ClotChip as a diagnostic platform for rapid POC/POI assessment of fibrinolysis-related hemostatic abnormalities in whole blood to guide therapy.

PulseDB: A large, cleaned dataset based on MIMIC-III and VitalDB for benchmarking cuff-less blood pressure estimation methods.

There has been a growing interest in developing cuff-less blood pressure (BP) estimation methods to enable continuous BP monitoring from electrocardiogram (ECG) and/or photoplethysmogram (PPG) signals. The majority of these methods have been evaluated using publicly-available datasets, however, there exist significant discrepancies across studies with respect to the size, the number of subjects, and the applied pre-processing steps for the data that is eventually used for training and testing the models. Such differences make conducting performance comparison across models largely unfair, and mask the generalization capability of various BP estimation methods. To fill this important gap, this paper presents "PulseDB," the largest cleaned dataset to date, for benchmarking BP estimation models that also fulfills the requirements of standardized testing protocols. PulseDB contains 1) 5,245,454 high-quality 10 -s segments of ECG, PPG, and arterial BP (ABP) waveforms from 5,361 subjects retrieved from the MIMIC-III waveform database matched subset and the VitalDB database; 2) subjects' identification and demographic information, that can be utilized as additional input features to improve the performance of BP estimation models, or to evaluate the generalizability of the models to data from unseen subjects; and 3) positions of the characteristic points of the ECG/PPG signals, making PulseDB directly usable for training deep learning models with minimal data pre-processing. Additionally, using this dataset, we conduct the first study to provide insights about the performance gap between calibration-based and calibration-free testing approaches for evaluating generalizability of the BP estimation models. We expect PulseDB, as a user-friendly, large, comprehensive and multi-functional dataset, to be used as a reliable source for the evaluation of cuff-less BP estimation methods.

Cuff-Less Blood Pressure Estimation From Photoplethysmography via Visibility Graph and Transfer Learning.

This paper presents a new solution that enables the use of transfer learning for cuff-less blood pressure (BP) monitoring via short duration of photoplethysmogram (PPG). The proposed method estimates BP with low computational budget by 1) creating images from segments of PPG via visibility graph (VG), hence, preserving the temporal information of the PPG waveform, 2) using pre-trained deep convolutional neural network (CNN) to extract feature vectors from VG images, and 3) solving for the weights and bias between the feature vectors and the reference BPs with ridge regression. Using the University of California Irvine (UCI) database consisting of 348 records, the proposed method achieves a best error performance of 0.00±8.46 mmHg for systolic blood pressure (SBP), and -0.04±5.36 mmHg for diastolic blood pressure (DBP), respectively, in terms of the mean error (ME) and the standard deviation (SD) of error, ranking grade B for SBP and grade A for DBP under the British Hypertension Society (BHS) protocol. Our novel data-driven method offers a computationally-efficient end-to-end solution for rapid and user-friendly cuff-less PPG-based BP estimation.

Cuff-Less Blood Pressure Estimation via Small Convolutional Neural Networks.

Deep learning-based cuff-less blood pressure (BP) estimation methods have recently gained increased attention as they can provide accurate BP estimation with only one physiological signal as input. In this paper, we present a simple and effective method for cuff-less BP estimation by training a small-scale convolutional neural network (CNN), modified from LeNet-5, with images created from short segments of the photoplethysmogram (PPG) signal via visibility graph (VG). Results show that the trained modified LeNet-5 model achieves an error performance of 0.184±7.457 mmHg for the systolic BP (SBP), and 0.343±4.065 mmHg for the diastolic BP (DBP) in terms of the mean error (ME) and the standard deviation (SD) of error between the estimated and reference BP. Both the SBP and the DBP accuracy rank grade A under the British Hypertension Society (BHS) protocol, demonstrating that our proposed method is an accurate way for cuff-less BP estimation.

PulseLab: An Integrated and Expandable Toolbox for Pulse Wave Velocity-based Blood Pressure Estimation.

In this paper, we introduce PulseLab, a comprehensive MATLAB toolbox that enables estimating the blood pressure (BP) from electrocardiogram (ECG) and photoplethysmogram (PPG) signals using pulse wave velocity (PWV)-based models. This universal framework consists of 6 sequential modules, covering end-to-end procedures that are needed for estimating BP from raw PPG/ECG data. These modules are "dataset formation", "signal pre-processing", "segmentation", "characteristic-points detection", "pulse transit time (PTT)/ pulse arrival time (PAT) calculation", and "model validation". The toolbox is expandable and its application programming interface (API) is built such that newly-derived PWV-BP models can be easily included. The toolbox also includes a user-friendly graphical user interface (GUI) offering visualization for step-by-step processing of physiological signals, position of characteristic points, PAT/PTT values, and the BP regression results. To the best of our knowledge, PulseLab is the first comprehensive toolbox that enables users to optimize their model by considering several factors along the process for obtaining the most accurate model for cuff-less BP estimation.

On the Non-idealities of a Capacitive Link for Wireless Power Transfer to Biomedical Implants.

This paper studies the performance of a resonant capacitive wireless power transfer (C-WPT) link for biomedical implants in the presence of non-idealities. The study emphasizes on finding an accurate electrical model of a practical C-WPT link, which can be used to investigate the performance of the link under different practical/non-ideal scenarios. A sound knowledge about these non-idealities is crucial for device optimization. For the first time, a circuit model has been presented and analyzed, which is applicable to a practical C-WPT link undergoing plate mismatch, flexion, tissue contraction, and stretching. Our model considers the finite conductivity of the body tissue and fringe fields formed by capacitor plates. Analytical and HFSSTM simulation results have been presented for different non-idealities, and are in good agreement. Additionally, we show a procedure to interpolate non-ideal case results. The study shows that plate misalignment (causing reduction in parallel plate overlap area) and skin tissue contraction (while muscle grows) are the most detrimental individual factors to the link performance. We recorded ∼32% and ∼14% power transfer efficiency decrease due to these two worst-case scenarios, respectively for a C-WPT link comprising of two pairs of 400 mm2 parallel plates (12 cm edge-to-edge separation) coated with 63.5 µm thick Kapton layer and aligned around a 3 mm tissue at 20 MHz.

Microfluidic electrical impedance assessment of red blood cell-mediated microvascular occlusion.

Alterations in the deformability of red blood cells (RBCs), occurring in hemolytic blood disorders such as sickle cell disease (SCD), contribute to vaso-occlusion and disease pathophysiology. There are few functional in vitro assays for standardized assessment of RBC-mediated microvascular occlusion. Here, we present the design, fabrication, and clinical testing of the Microfluidic Impedance Red Cell Assay (MIRCA) with embedded capillary network-based micropillar arrays and integrated electrical impedance measurement electrodes to address this need. The micropillar arrays consist of microcapillaries ranging from 12 µm to 3 µm, with each array paired with two sputtered gold electrodes to measure the impedance change of the array before and after sample perfusion through the microfluidic device. We define RBC occlusion index (ROI) and RBC electrical impedance index (REI), which represent the cumulative percentage occlusion and cumulative percentage impedance change, respectively. We demonstrate the promise of MIRCA in two common red cell disorders, SCD and hereditary spherocytosis. We show that the electrical impedance measurement reflects the microvascular occlusion, where REI significantly correlates with ROI that is obtained via high-resolution microscopy imaging of the microcapillary arrays. Further, we show that RBC-mediated microvascular occlusion, represented by ROI and REI, associates with clinical treatment outcomes and correlates with in vivo hemolytic biomarkers, lactate dehydrogenase (LDH) level and absolute reticulocyte count (ARC) in SCD. Impedance measurement obviates the need for high-resolution imaging, enabling future translation of this technology for widespread access, portable and point-of-care use. Our findings suggest that the presented microfluidic design and the integrated electrical impedance measurement provide a reproducible functional test for standardized assessment of RBC-mediated microvascular occlusion. MIRCA and the newly defined REI may serve as an in vitro therapeutic efficacy benchmark for assessing the clinical outcome of emerging RBC-modifying targeted and curative therapies.

Monitoring DOACs with a Novel Dielectric Microsensor: A Clinical Study.

BACKGROUND: There are acute settings where assessing the anticoagulant effect of direct oral anticoagulants (DOACs) can be useful. Due to variability among routine coagulation tests, there is an unmet need for an assay that detects DOAC effects within minutes in the laboratory or at the point of care. METHODS: We developed a novel dielectric microsensor, termed ClotChip, and previously showed that the time to reach peak permittivity (T peak) is a sensitive parameter of coagulation function. We conducted a prospective, single-center, pilot study to determine its clinical utility at detecting DOAC anticoagulant effects in whole blood. RESULTS: We accrued 154 individuals: 50 healthy volunteers, 49 rivaroxaban patients, 47 apixaban, and 8 dabigatran patients. Blood samples underwent ClotChip measurements and plasma coagulation tests. Control mean T peak was 428 seconds (95% confidence interval [CI]: 401-455 seconds). For rivaroxaban, mean T peak was 592 seconds (95% CI: 550-634 seconds). A receiver operating characteristic curve showed that the area under the curve (AUC) predicting rivaroxaban using T peak was 0.83 (95% CI: 0.75-0.91, p < 0.01). For apixaban, mean T peak was 594 seconds (95% CI: 548-639 seconds); AUC was 0.82 (95% CI: 0.73-0.91, p < 0.01). For dabigatran, mean T peak was 894 seconds (95% CI: 701-1,086 seconds); AUC was 1 (p < 0.01). Specificity for all DOACs was 88%; sensitivity ranged from 72 to 100%. CONCLUSION: This diagnostic study using samples from "real-world" DOAC patients supports that ClotChip exhibits high sensitivity at detecting DOAC anticoagulant effects in a disposable portable platform, using a miniscule amount of whole blood (<10 µL).

A 280 µW, 108 dB DR PPG-Readout IC With Reconfigurable, 2nd-Order, Incremental ΔΣM Front-End for Direct Light-to-Digital Conversion.

This paper reports on a low-power readout IC (ROIC) for high-fidelity recording of the photoplethysmogram (PPG) signal. The system comprises a highly reconfigurable, continuous-time, second-order, incremental delta-sigma modulator (I-ΔΣM) as a light-to-digital converter (LDC), a 2-channel 10b light-emitting diode (LED) driver, and an integrated digital signal processing (DSP) unit. The LDC operation in intermittent conversion phases coupled with digital assistance by the DSP unit allow signal-aware, on-the-fly cancellation of the dc and ambient light-induced components of the photodiode current for more efficient use of the full-scale input range for recording of the small-amplitude, ac, PPG signal. Fabricated in TSMC 0.18 µm 1P/6M CMOS, the PPG ROIC exhibits a high dynamic range of 108.2 dB and dissipates on average 15.7 µW from 1.5 V in the LDC and 264 µW from 2.5 V in one LED (and its driver), while operating at a pulse repetition frequency of 250 Hz and 3.2% duty cycling. The overall functionality of the ROIC is also demonstrated by high-fidelity recording of the PPG signal from a human subject fingertip in the presence of both natural light and indoor light sources of 60 Hz.

A Dual-Output Single-Stage Regulating Rectifier With PWM and Dual-Mode PFM Control for Wireless Powering of Biomedical Implants.

This paper presents a reconfigurable, dual-output, regulating rectifier featuring pulse width modulation (PWM) and dual-mode pulse frequency modulation (PFM) control schemes for single-stage ac-to-dc conversion to provide two independently regulated supply voltages (each in 1.5-3 V) from an input ac voltage. The dual-mode PFM controllers feature event-driven regulation as well as frequency division. The former incorporates stable, fast, digital feedback loops to adaptively adjust the driving frequency of four power transistors, MP1∼4, based on the desired output power level to perform voltage regulation and deliver fast, transient, load currents. The latter sets the driving frequency of MP1∼4 to a user-defined fraction (1/1 âˆ¼ 1/32) of the input frequency (1-10 MHz). The PWM controllers incorporate stable, analog, feedback loops to accurately adjust the conduction duration of MP1∼4 for voltage regulation and can be combined with PFM frequency division for an extended operation dynamic range. Fabricated in 0.18 µm 1P/6M CMOS, the regulating rectifier features power conversion efficiency (PCE) of >83.8% at 2 and 5 MHz, with the first output channel delivering ∼1 mW from VDD of 1.5 V and the second output channel delivering variable power from VDDH of 2.5 V to a load in the range of 0.1 to 1 kΩ. Peak PCE values of 90.75% (2 MHz, 100 Ω) and 90.7% (5 MHz, 200 Ω) are also measured. The regulating rectifier is suitable for the emerging modality of capacitive wireless power transfer to biomedical implants.

A novel, point-of-care, whole-blood assay utilizing dielectric spectroscopy is sensitive to coagulation factor replacement therapy in haemophilia A patients.

BACKGROUND: Reliable monitoring of coagulation factor replacement therapy in patients with severe haemophilia, especially those with inhibitors, is an unmet clinical need. While useful, global assays, eg thromboelastography (TEG), rotational thromboelastometry (ROTEM) and thrombin generation assay (TGA), are cumbersome to use and not widely available. OBJECTIVE: To assess the utility of a novel, point-of-care, dielectric microsensor - ClotChip - to monitor coagulation factor replacement therapy in patients with haemophilia A, with and without inhibitors. METHODS: The ClotChip Tpeak parameter was assessed using whole-blood samples from children with severe haemophilia A, with (n = 6) and without (n = 12) inhibitors, collected pre- and postcoagulation factor replacement therapy. ROTEM, TGA and chromogenic FVIII assays were also performed. Healthy children (n = 50) served as controls. RESULTS: ClotChip Tpeak values exhibited a significant decrease for samples collected postcoagulation factor replacement therapy as compared to baseline (pretherapy) samples in patients with and without inhibitors. A difference in Tpeak values was also noted at baseline among severe haemophilia A patients with inhibitors as compared to those without inhibitors. ClotChip Tpeak parameter exhibited a very strong correlation with clotting time (CT) of ROTEM, endogenous thrombin potential (ETP) and peak thrombin of TGA, and FVIII clotting activity. CONCLUSIONS: ClotChip is sensitive to coagulation factor replacement therapy in patients with severe haemophilia A, with and without inhibitors. ClotChip Tpeak values correlate very well with ROTEM, TGA and FVIII assays, opening up possibilities for its use in personalized coagulation factor replacement therapy in haemophilia.

Modeling and Characterization of Capacitive Elements With Tissue as Dielectric Material for Wireless Powering of Neural Implants.

This paper reports on the modeling and characterization of capacitive elements with tissue as the dielectric material, representing the core building block of a capacitive link for wireless power transfer to neural implants. Each capacitive element consists of two parallel plates that are aligned around the tissue layer and incorporate a grounded, guarded, capacitive pad to mitigate the adverse effect of stray capacitances and shield the plates from external interfering electric fields. The plates are also coated with a biocompatible, insulating, coating layer on the inner side of each plate in contact with the tissue. A comprehensive circuit model is presented that accounts for the effect of the coating layers and is validated by measurements of the equivalent capacitance as well as impedance magnitude/phase of the parallel plates over a wide frequency range of 1 kHz-10 MHz. Using insulating coating layers of Parylene-C at a thickness of and Parylene-N at a thickness of deposited on two sets of parallel plates with different sizes and shapes of the guarded pad, our modeling and characterization results accurately capture the effect of the thickness and electrical properties of the coating layers on the behavior of the capacitive elements over frequency and with different tissues.

C-FSCV: Compressive Fast-Scan Cyclic Voltammetry for Brain Dopamine Recording.

This paper presents a novel compressive sensing framework for recording brain dopamine levels with fast-scan cyclic voltammetry (FSCV) at a carbon-fiber microelectrode. Termed compressive FSCV (C-FSCV), this approach compressively samples the measured total current in each FSCV scan and performs basic FSCV processing steps, e.g., background current averaging and subtraction, directly with compressed measurements. The resulting background-subtracted faradaic currents, which are shown to have a block-sparse representation in the discrete cosine transform domain, are next reconstructed from their compressively sampled counterparts with the block sparse Bayesian learning algorithm. Using a previously recorded dopamine dataset, consisting of electrically evoked signals recorded in the dorsal striatum of an anesthetized rat, the C-FSCV framework is shown to be efficacious in compressing and reconstructing brain dopamine dynamics and associated voltammograms with high fidelity (correlation coefficient, ), while achieving compression ratio, CR, values as high as ~ 5. Moreover, using another set of dopamine data recorded 5 minutes after administration of amphetamine (AMPH) to an ambulatory rat, C-FSCV once again compresses (CR = 5) and reconstructs the temporal pattern of dopamine release with high fidelity ( ), leading to a true-positive rate of 96.4% in detecting AMPH-induced dopamine transients.