基于ADS8332的生理信号采集系统电路设计

本文介绍了医学生理信号的的特点,根据其特点设计出了针对医学生理信号进行采集的电路。该电路设计实现了基于16位的高精度A/D 转换芯片ADS8332 的医学生理信号采集系统,以基于Cortex-M3 内核的32 位微控制器STM32F103RD作为采集控制芯片,该系统电路可以实现对最多16 个通道的模拟医学生理信号进行采集。此电路设计充分利用了ADS8332 的高精度、低功耗、高采样速率的特点以及片上集成功能,并配合了信号调理电路和相应的抗干扰措施,因此保证了医学生理信号的采集精度和系统的稳定性。     

基于 ADS8332 的生理信号采集系统电路设计 *

摘要： 本文介绍了医学生理信号的的特点, 根据其特点设计出了针对医学生理信号进行采集的电路。该电路设计实现了基于 16 位的高精度 A/D 转换芯片 ADS8332 的医学生理信号采集系统,以基于 Cortex-M3 内核的 32 位微控制器 STM32F103RD 作为采 集控制芯片, 该系统电路可以实现对最多 16 个通道的模拟医学生理信号进行采集。此电路设计充分利用了 ADS8332 的高精度、 低功耗、 高采样速率的特点以及片上集成功能, 并配合了信号调理电路和相应的抗干扰措施,因此保证了医学生理信号的采集精 度和系统的稳定性。     

A circuit analog model for studying quantitative water relations of plant tissues

Using arrays of resistors and capacitors, a lumped circuit analog of plant tissue is developed. The circuit elements of the analog are identified in terms of physiological variables (hydraulic conductivities, water capacities, and cell dimensions) which can be measured in the laboratory. With the aid of a circuit simulation subroutine, the model was solved to predict water potential distributions as a function of position and time in plant tissues of three, six, and nine cells. Results presented for the six-cell case indicate that local equilibrium may or may not occur depending on the actual values of tissue hydraulic conductivities, water capacities, and the rate of change of water potential at the tissue boundaries. However, present measurements and estimates of tissue parameters suggest that local equilibrium is more the rule than the exception. Membrane resistance is an especially important parameter because it serves to isolate the vacuoles from the cell walls in addition to increasing the natural vacuole response time to changes in water potential.     

Nonlinear electronic circuit with neuron like bursting and spiking dynamics

It is difficult to design electronic nonlinear devices capable of reproducing complex oscillations because of the lack of general constructive rules, and because of stability problems related to the dynamical robustness of the circuits. This is particularly true for current analog electronic circuits that implement mathematical models of bursting and spiking neurons. Here we describe a novel, four-dimensional and dynamically robust nonlinear analog electronic circuit that is intrinsic excitable, and that displays frequency adaptation bursting and spiking oscillations. Despite differences from the classical Hodgkin–Huxley (HH) neuron model, its bifurcation sequences and dynamical properties are preserved, validating the circuit as a neuron model. The circuit's performance is based on a nonlinear interaction of fast–slow circuit blocks that can be clearly dissected, elucidating burst's starting, sustaining and stopping mechanisms, which may also operate in real neurons. Our analog circuit unit is easily linked and may be useful in building networks that perform in real-time.     

A low noise multichannel integrated circuit for recording neuronal signals using microelectrode arrays

This paper reports on the development of a fully integrated 32-channel integrated circuit (IC) for recording neuronal signals in neurophysiological experiments using microelectrode arrays. The IC consists of 32 channels of low-noise preamplifiers and bandpass filters, and an output analog multiplexer. The continuous-time RC active filters have a typical passband of 20-2000 Hz; the low and the high cut-off frequencies can be separately controlled by external reference currents. This chip provides a satisfactory signal-to-noise ratio for neuronal signals with amplitudes greater than 50 microV. For the nominal passband setting, an equivalent input noise of 3 microV rms has been achieved. A single channel occupies 0.35 mm(2) of silicon area and dissipates 1.7 mW of power. The chip was fabricated in a 0.7 microm CMOS process.     

Analog VLSI implementation of resonate-and-fire neuron

We propose an analog integrated circuit that implements a resonate-and-fire neuron (RFN) model based on the Lotka-Volterra (LV) system. The RFN model is a spiking neuron model that has second-order membrane dynamics, and thus exhibits fast damped subthreshold oscillation, resulting in the coincidence detection, frequency preference, and post-inhibitory rebound. The RFN circuit has been derived from the LV system to mimic such dynamical behavior of the RFN model. Through circuit simulations, we demonstrate that the RFN circuit can act as a coincidence detector and a band-pass filter at circuit level even in the presence of additive white noise and background random activity. These results show that our circuit is expected to be useful for very large-scale integration (VLSI) implementation of functional spiking neural networks.     

Application of on-chip cell cultures for the detection of allergic response

In this report, the development of a microfluidic cell chip for monitoring allergic response is described. A rat basophilic leukemia cell line (RBL-2H3), a tumor analog of rat mucosal mast cells, has been used as a model to observe its allergic response upon antigen stimulus. The cells were cultivated on a poly(dimethylsiloxane) (PDMS) chip, the surface of which was modified by several methods. The PDMS chip, which comprised a cell cultivation chamber and microfluidic channels, was fabricated by conventional molding methods. In order to detect the allergic response, a fluorescent dye, quinacrine, was introduced inside the cell compartment that included histamine. The cells were stimulated with dinitrophenylated bovine serum albumin (DNP-BSA) after incubation with anti-DNP IgE. When exocytosis events occurred, the microfluidic system detected the fluorescent signal of quinacrine, which was released from RBL-2H3 cells by using a photomultiplier tube (PMT) fitted onto a microscope.     

A universal kinetic model for characterisation of the effect of chip thickness on kraft pulping

A kinetic model was developed to characterise the heterogeneous nature of kraft delignification kinetics, taking into account the effect of chip thickness. The final form of the model applied to kraft delignification can be represented by a first-order rate equation with a rate constant inversely proportional to a power function of chip thickness. Published laboratory results from kraft pulping of various lignocellulosic materials were used to validate the model. The outcomes confirm the significant effect of chip thickness on the delignification rate. The resultant model was used to predict the effect of chip thickness on the kappa distribution of kraft pulps.     

Modeling light-induced currents in the eye of Chlamydomonas reinhardtii

Rhodopsin-mediated electrical events in green algae have been recorded in the past from the eyes of numerous micro-algae like Haematococcus pluvialis, Chlamydomonas reinhardtii and Volvox carteri. However, the electrical data gathered by suction-pipette techniques could be interpreted in qualitative terms only. Here we present two models that allow a quantitative analysis of such results: First, an electrical analog circuit for the cell in suction pipette configuration is established. Applying this model to experimental data from unilluminated cells of C. reinhardtii yields a membrane conductance of about 3 Sm(-2). Furthermore, an analog circuit allows the determination of the photocurrent fraction that is recorded under experimental conditions. Second, a reaction scheme of a rhodopsin-type photocycle with an early Ca(2+) conductance and a later H(+) conductance is presented. The combination of both models provides good fits to light-induced currents recorded from C. reinhardtii. Finally, it allowed the calculation of the impact of each model parameter on the time courses of observable photocurrent and of inferred transmembrane voltage. The reduction of the flash-to-peak times at increasing light intensities are explained by superposition of two kinetically distinct rhodopsins and by assuming that the Ca(2+)-conducting state decays faster at more positive membrane voltages.     

Noise Expands the Response Range of the Bacillus subtilis Competence Circuit

Gene regulatory circuits must contend with intrinsic noise that arises due to finite numbers of proteins. While some circuits act to reduce this noise, others appear to exploit it. A striking example is the competence circuit in Bacillus subtilis, which exhibits much larger noise in the duration of its competence events than a synthetically constructed analog that performs the same function. Here, using stochastic modeling and fluorescence microscopy, we show that this larger noise allows cells to exit terminal phenotypic states, which expands the range of stress levels to which cells are responsive and leads to phenotypic heterogeneity at the population level. This is an important example of how noise confers a functional benefit in a genetic decision-making circuit.     

Wideband LTE Power Amplifier with Integrated Novel Analog Pre-Distorter Linearizer for Mobile Wireless Communications

For the first time, a new circuit to extend the linear operation bandwidth of a LTE (Long Term Evolution) power amplifier, while delivering a high efficiency is implemented in less than 1 mm² chip area. The 950 µm × 900 µm monolithic microwave integrated circuit (MMIC) power amplifier (PA) is fabricated in a 2 µm InGaP/GaAs process. An on-chip analog pre-distorter (APD) is designed to improve the linearity of the PA, up to 20 MHz channel bandwidth. Intended for 1.95 GHz Band 1 LTE application, the PA satisfies adjacent channel leakage ratio (ACLR) and error vector magnitude (EVM) specifications for a wide LTE channel bandwidth of 20 MHz at a linear output power of 28 dBm with corresponding power added efficiency (PAE) of 52.3%. With a respective input and output return loss of 30 dB and 14 dB, the PA’s power gain is measured to be 32.5 dB while exhibiting an unconditional stability characteristic from DC up to 5 GHz. The proposed APD technique serves to be a good solution to improve linearity of a PA without sacrificing other critical performance metrics.     

Distinct rhythmic locomotor patterns can be generated by a simple adaptive neural circuit: Biology,simulation, and VLSI implementation

Rhythmic motor patterns can be induced in leg motor neurons of isolated locust thoracic ganglia by bath application of pilocarpine. We observed that the relative phases of levators and depressors differed in the three thoracic ganglia. Assuming that the central pattern generating circuits underlying these three segmental rhythms are probably very similar, we developed a simple model circuit that can produce any one of the three activity patterns and characteristic phase relationships by modifying a single synaptic weight. We show results of a computer simulation of this circuit using the neuronal simulator NeuraLOG/Spike. We built and tested an analog VLSI circuit implementation of this model circuit that exhibits the same range of behaviors as the computer simulation. This multidisciplinary strategy will be useful to explore the dynamics of central pattern generating networks coupled to physical actuators, and ultimately should allow the design of biologically realistic walking robots.     

Sensing without touching: psychophysical performance based on cortical microstimulation

Unequivocal proof that the activity of a localized cortical neuronal population provides sufficient basis for a specific cognitive function has rarely been obtained. We looked for such proof in monkeys trained to discriminate between two mechanical flutter stimuli applied sequentially to the fingertips. Microelectrodes were inserted into clusters of quickly adapting (QA) neurons of the primary somatosensory cortex (S1), and the first or both stimuli were then substituted with trains of current pulses during the discrimination task. Psychophysical performance with artificial stimulus frequencies was almost identical to that measured with the natural stimulus frequencies. Our results indicate that microstimulation can be used to elicit a memorizable and discriminable analog range of percepts, and shows that activation of the QA circuit of S1 is sufficient to initiate all subsequent neural processes associated with flutter discrimination.     

An electronic analog of synthetic genetic networks

An electronic analog of a synthetic genetic network known as the repressilator is proposed. The repressilator is a synthetic biological clock consisting of a cyclic inhibitory network of three negative regulatory genes which produces oscillations in the expressed protein concentrations. Compared to previous circuit analogs of the repressilator, the circuit here takes into account more accurately the kinetics of gene expression, inhibition, and protein degradation. A good agreement between circuit measurements and numerical prediction is observed. The circuit allows for easy control of the kinetic parameters thereby aiding investigations of large varieties of potential dynamics.     

Watching neurotransmission in vitro

A new chip with a capability to read genomes uses arrays of tiny pH sensors on an integrated circuit to sequence DNA without the need for optics.     

Back-Propagation Operation for Analog Neural Network Hardware with Synapse Components Having Hysteresis Characteristics

To realize an analog artificial neural network hardware, the circuit element for synapse function is important because the number of synapse elements is much larger than that of neuron elements. One of the candidates for this synapse element is a ferroelectric memristor. This device functions as a voltage controllable variable resistor, which can be applied to a synapse weight. However, its conductance shows hysteresis characteristics and dispersion to the input voltage. Therefore, the conductance values vary according to the history of the height and the width of the applied pulse voltage. Due to the difficulty of controlling the accurate conductance, it is not easy to apply the back-propagation learning algorithm to the neural network hardware having memristor synapses. To solve this problem, we proposed and simulated a learning operation procedure as follows. Employing a weight perturbation technique, we derived the error change. When the error reduced, the next pulse voltage was updated according to the back-propagation learning algorithm. If the error increased the amplitude of the next voltage pulse was set in such way as to cause similar memristor conductance but in the opposite voltage scanning direction. By this operation, we could eliminate the hysteresis and confirmed that the simulation of the learning operation converged. We also adopted conductance dispersion numerically in the simulation. We examined the probability that the error decreased to a designated value within a predetermined loop number. The ferroelectric has the characteristics that the magnitude of polarization does not become smaller when voltages having the same polarity are applied. These characteristics greatly improved the probability even if the learning rate was small, if the magnitude of the dispersion is adequate. Because the dispersion of analog circuit elements is inevitable, this learning operation procedure is useful for analog neural network hardware.     

Expression of regulatory nif genes in Rhodobacter capsulatus.

Translational fusions of the Escherichia coli lacZ gene to Rhodobacter capsulatus nif genes were constructed in order to determine the regulatory circuit of nif gene expression in R. capsulatus, a free-living photosynthetic diazotroph. The expression of nifH, nifA (copies I and II), and nifR4 was measured in different regulatory mutant strains under different physiological conditions. The expression of nifH and nifR4 (the analog of ntrA in Klebsiella pneumoniae) depends on the NIFR1/R2 system (the analog of the ntr system in K. pneumoniae), on NIFA, and on NIFR4. The expression of both copies of nifA is regulated by the NIFR1/R2 system and is modulated by the N source of the medium under anaerobic photosynthetic growth conditions. In the presence of ammonia or oxygen, moderate expression of nifA was detectable, whereas nifH and nifR4 were not expressed under these conditions. The implications for the regulatory circuit of nif gene expression in R. capsulatus are discussed and compared with the situation in K. pneumoniae, another free-living diazotroph.     

Automatic bio-sampling chips integrated with micro-pumps and micro-valves for disease detection

The present study reports a microfluidic system using the concept of membrane-movement to design and fabricate micro-pneumatic valves and pumps to form a bio-sensing diagnostic chip. The automatic bio-sampling system includes a micro-diagnostic chip fabricated by using MEMS (micro-electro-mechanical systems) technology and an automatic platform comprising of a control circuit, a compressed air source and several electromagnetic valve switches. The control circuit is used to regulate the electromagnetic valve switches, causing thin PDMS membranes to deflect pneumatically by the compressed air and generate valving and pumping effects. The micro-diagnostic chip allows for the quick detection of diseases. Compared to large-scale systems, the new microfluidic system uses smaller amounts of samples and reagents and performs fast diagnosis in an automated format. Instead of using traditional pneumatic micro-pumps, the current study adopts a new design called "spider-web" micro-pumps to increase the pumping rate, and more importantly, improve the uniformity of flow rates inside multiple micro-channels. Experimental data show that for disease diagnosis, the bio-sensing chips integrated with the micro-pneumatic valves and the peristaltic micro-pumps could successfully perform diagnosis tests. Small amounts of samples and reagents could be injected into the diagnosis chips using the micro-pumps and the micro-pneumatic valves could effectively control the movement of the samples and reagents. In order to demonstrate the functionality of the developed device, detection of hepatitis C virus (HCV) and syphilis has been performed using the bio-sampling chips. Experimental data show that fluorescence signals from the microfluidic system were comparable to the ones using conventional testing methods. The developed chip could be easily extended for multiple disease detection. The automatic bio-sensing chips could provide a useful tool for fast disease detection and be crucial for a micro-total-analysis system.