Abernathymaxwell4050

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. In this paper, a very simple alternative time-to-digital demodulation method or 'time stamp' is proposed. It employs only three comparators to identify or stamp in the time domain, the crossing points of the excitation signal, and the measured signal. In a CMOS proof of concept design, the accuracy of impedance magnitude and phase is 97.06% and 98.81% respectively over a bandwidth of 10 kHz to 500 kHz. The effect of fractional-N synthesis is analysed for the counter-based zero crossing phase detector obtaining a finer phase resolution (0.51˚ at 500 kHz) using a counter clock frequency ( fclk = 12.5 MHz). Because of its circuit simplicity and ease of transmitting the time stamps, the method is very suited to implantable devices requiring low area and power consumption.

The purpose of this paper is to demonstrate the use of 2-D impedance spectroscopy to identify areas of biofilm growth on a CMOS biosensor microelectrode-array.

This paper presents the design and use of a novel multichannel impedance spectroscopy instrument to allow 2-D spatial and temporal evaluation of biofilm growth. The custom-designed circuits can provide a wide range of frequencies (1Hz-100kHz) to allow customization of impedance measurements, as the frequency of interest varies based on the type and state of biofilm under measurement. The device is capable of taking measurements as fast as once per second on the entire set of impedance sensors, allowing real-time observation. It also supports adjustable stimulus voltages. The distance between neighboring sensors is 220 micrometers which provides reasonable spatial resolution for biofilm study.

Biofilm was grown on the surface of the chip, occupancy was measured using the new tool, and the results were validated optically using fluorescent stainingbiofilms.To improve the SpO 2 sensing system performance for hypoperfusion (low perfusion index) applications, this paper proposes a low-noise light-to-frequency converter scheme from two aspects. First, a low-noise photocurrent buffer is proposed by reducing the amplifier noise floor with a transconductance-boost ( gm-boost) circuit structure. Second, a digital processing unit of pulse-frequency-duty-cycle modulation is proposed to minimize the quantization noise in the following timer by limiting the maximum output frequency. The proposed light-to-frequency sensor chip is designed and fabricated with a 0.35- μm CMOS process. The overall chip area is 1 × 0.9 mm 2 and the typical total current consumption is about 1.8 mA from a 3.3-V power supply at room temperature. The measurement results prove the proposed functionality of output pulse duty cycle modulation, while the SNR of a typical 10-kHz output frequency is 59 dB with about 9-dB improvement when compared with the previous design. Among them, 2-3 dB SNR improvement stems from the gm-boosting and the rest comes from the layout design. In-system experimental results show that the minimum measurable PI using the proposed blood SpO 2 sensor could be as low as 0.06% with 2-percentage-point error of SpO 2. The proposed chip is suitable for portable low-power high-performance blood oximeter devices especially for hypoperfusion applications.This paper presents a novel approach to design compact wearable antennas based on metasurfaces. The behavior of compact metasurfaces is modeled with a composite right-left handed transmission line (CRLH TL). By controlling the dispersion curve, the resonant modes of the compact metasurface can be tuned efficiently. A printed coplanar waveguide (CPW) monopole antenna is used as the feed structure to excite the compact metasurface, which will result in a low profile antenna with low backward radiation. Following this approach, two compact antennas are designed for wearable applications. The first antenna is designed to operate at its first negative mode (-1 mode), which can realize miniaturization, but maintain the broadside radiation as for a normal microstrip antenna. The proposed prototype resonates around 2.65 GHz, with a matching bandwidth of 300 MHz. The total dimensions of the antenna are 39.4 × 33.4 mm2 (0.1 λ02), and its maximum gain is 2.99 dBi. The second antenna targets dual-band operation at 2.45 and 3.65 GHz. Selleckchem Degrasyn A pair of symmetric modes (±1 modes) are used to generate similar radiation patterns in these two bands. The size of the antenna is 55.79 × 52.25 mm2 (0.2 λ02), and the maximum gains are 4.25 and 7.35 dBi in the two bands, respectively. Furthermore, the performance of the antennas is analyzed on the human body. The results show that the proposed antennas are promising candidates for Wireless Body Area Networks (WBAN).Electrochemical micro-sensors made of nano-graphitic (NG) carbon materials could offer high sensitivity and support voltammetry measurements at vastly different temporal resolutions. Here, we implement a configurable CMOS biochip for measuring low concentrations of bio-analytes by leveraging these advantageous features of NG micro-sensors. In particular, the core of the biochip is a discrete-time ∆Σ modulator, which can be configured for optimal power consumption according to the temporal resolution requirements of the sensing experiments while providing a required precision of ≈ 13 effective number of bits. We achieve this new functionality by developing a design methodology using the physical models of transistors, which allows the operating region of the modulator to be switched on-demand between weak and strong inversion. We show the application of this configurable biochip through in-vitro measurements of dopamine with concentrations as low as 50 nM and 200 nM at temporal resolutions of 100 ms and 10 s, respectively.We have developed a 5-electrode recording system that combines an implantable electromyography (EMG) device package with transcutaneous inductive power transmission, near-infrared (NIR) transcutaneous data telemetry and 3 Mbps Wi-Fi data acquisition for chronic EMG recording in vivo. This system comprises a hermetically-sealed single-chip, 5-electrode Implantable EMG Acquisition Device (IEAD), a custom external powering and Implant Telemetry Module (ITM), and a custom Wi-Fi-based Raspberry Pi-based Data Acquisition (RaspDAQ) and relay device. The external unit (ITM and RaspDAQ) is powered entirely by a single battery to achieve the objective of untethered EMG recording, for the convenience of clinicians and animal researchers. The IEAD acquires intramuscular EMG signals at 17.85 ksps/electrode while being powered transcutaneously by the ITM using 22 MHz near-field inductive coupling. The acquired EMG data is transmitted transcutaneously via NIR telemetry to the ITM, which in turn, transfers the data to the RaspDAQ for relaying to a laptop computer for display and storage. We have also validated the complete system by acquiring EMG signals from rodents for up to two months. Following the explantation of the devices, we have also conducted failure and histological analysis on the devices and the surrounding tissue, respectively.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. This paper describes the power efficiency analysis of such level-crossing ADC (LCADC) and the traditional fixed-rate SAR ADC with simple compression. A model for the power consumption of the LCADC is derived, which is then compared to the power consumption of the SAR ADC with zero-order hold (ZOH) compression for multiple biosignals (ECG, EMG, EEG, and EAP). The LCADC is more power efficient than the SAR ADC up to a cross-over point in quantizer resolution (for example 8 bits for an EEG signal). This cross-over point decreases with the ratio of the maximum to average slope in the signal of the application. It also changes with the technology and design techniques used. The LCADC is thus suited for low to medium resolution applications. In addition, the event-driven operation of an LCADC results in fewer data to be transmitted in a system application. The event-driven LCADC without timer and with single-bit quantizer achieves a reduction in power consumption at system level of two orders of magnitude, an order of magnitude better than the SAR ADC with ZOH compression. At system level, the LCADC thus offers a big advantage over the SAR ADC.In this article, a novel method for measuring the volume of the urinary bladder non-invasively is presented that relies on the principles dictated by Electrical Impedance Tomography (EIT). The electronic prototype responsible for injecting innocuous electrical currents to the lower abdominal region and measuring the developed voltage levels is fully described, as well as the computational models for resolution of the so-called Forward and Inverse Problems in Imaging. The simultaneous multi-tone injection of current provided by a high performance Field Programmable Gate Array (FPGA), combined with impedance estimation by the Discrete Fourier Transform (DFT) constitutes a novelty in Urodynamics with potential to monitor continuously the intravesical volume of patients in a much faster and comfortable way than traditional transurethral catheterization methods. The resolution of the Inverse Problem is performed by the Gauss-Newton method with Laplacian regularization, allowing to obtain a sectional representation of the volume of urine encompassed by the bladder and surrounding body tissues. Experimentation has been carried out with synthetic phantoms and human subjects with results showing a good correlation between the levels of abdominal admittivity acquired by the EIT system and the volume of ingested water.Chronic neurological disorders (CND's) are lifelong diseases and cannot be eradicated, but their severe effects can be alleviated by early preemptive measures. CND's, such as Alzheimer's, Autism Spectrum Disorder (ASD), and Amyotrophic Lateral Sclerosis (ALS), are the chronic ailment of the central nervous system that causes the degradation of emotional and cognitive abilities. Long term continuous monitoring with neuro-feedback of human emotions for patients with CND's is crucial in mitigating its harmful effect. This paper presents hardware efficient and dedicated human emotion classification processor for CND's. Scalp EEG is used for the emotion's classification using the valence and arousal scales. A linear support vector machine classifier is used with power spectral density, logarithmic interhemispheric power spectral ratio, and the interhemispheric power spectral difference of eight EEG channel locations suitable for a wearable non-invasive classification system. A look-up-table based logarithmic division unit (LDU) is to represent the division features in machine learning (ML) applications.