Analog Electrical Signal Research Articles

A sensory–neuromorphic interface capable of environmental perception, sensory coding, and biological stimuli

AbstractThe sensory–neuromorphic interface is key to the application of neuromorphic electronics. Artificial spiking neurons and artificial sensory nerves have been created, and a few studies showed a complete neuromorphic system through cointegration with synaptic electronics. However, artificial synaptic devices and systems often do not work in real environments, which limits their ability to provide realistic neural simulations and interface with biological nerves. We report a sensory–neuromorphic interface that uses a fiber synapse to emulate a biological afferent nerve. For the first time, a sensing–neuromorphic interface is connected to a living organism for peripheral nerve stimulation, allowing the organism to establish a connection with its surrounding environment. The interface converts perceived environmental information into analog electrical signals and then into frequency‐dependent pulse signals, which simplify the information interface between the sensor and the pulse‐data processing center. The frequency of the interface shows a sublinear dependence on strain amplitude at different stimulus intensities, and can deliver increased frequency spikes at potentially damaging stimulus intensities, similar to the response of biological afferent nerves. To verify the application of this interface, a system that monitors strain and provides an overstrain alarm was constructed based on this afferent neural circuit. The system has a response time of <2 ms, which is compatible with the response time in biological systems. The interface can be potentially extended to process signals from almost any type of sensors for other afferent senses, and these results demonstrate the potential for neuromorphic interfaces to be applied to bionic sensory interfaces.

Use of Arduino and flute in teaching waves in a high school class

This work aims to use music as a teaching tool and, alongside it, utilize Arduino as a device to verify the components to be studied. The theoretical framework to be used is based on the Potentially Meaningful Teaching Units, UEPS approach, allowing for the construction of meaningful learning for students through problem-solving situations. A didactic sequence was developed for the study of the theme of sound waves and their components at the high school level. This sequence was applied over a period of four weeks, including an initial presentation of topics related to waves, the construction of an electronic system using Arduino, and the verification of phenomena based on musical notes. The data collection instruments for this research included questionnaires to assess students' prior knowledge, mind maps, and exercise lists. The Arduino programming board, which allows for the digitization of analog and digital electrical signals, was used in conjunction with a microphone module, enabling the integration of electronic physics with wave physics. As a result of this research, there were indications of learning through the interdisciplinary relationship between music and physics, which was made effective through the use of Arduino and the recorder flute.

Scalable Photonic Digital-to-Analog Converters

This work introduces a novel architecture for implementing a parallel coherent photonic digital-to-analog converter (PDAC), designed to transform parallel digital electrical signals into corresponding analog optical output, convertible to analog electrical signals using photodiodes. The proposed architecture incorporates microring resonator-based modulators (MRMs), phase shifters, and symmetric multimode interference couplers. Efficient modulation is achieved by MRMs utilizing carrier depletion-induced refractive index changes, while metal heaters facilitate tuning of the ring resonator resonance wavelength. The proposed architecture is scalable to higher bit resolutions and exhibits a dynamic range limited by MRM’s sensitivity to applied bias and noise levels. Experimental results of the fabricated chip in the silicon-on-insulator (SOI) platform showcase the successful realization of a 4 GSample/sec conversion rate in a 2-bit resolution operation, along with a stationary conversion of four parallel DC digital signals into 16 analog intensity levels in a 4-bit PDAC configuration. The study encompasses a proof-of-concept experimental demonstration of 8 Gbps data conversion, along with a 50 Gbps data conversion rate using the optimized design in the simulation, affirming the accuracy and quality of the PDAC architecture. These findings contribute to the advancement of PDAC technology, providing insights into performance characteristics, limitations, and potential applications.

Direct wireless readout of fiber Bragg grating sensors using radio-over-fiber.

Wireless readout of optical fiber sensors is of interest for a variety of applications. In the state of the art, the sensor data are digitized before the wireless transmission. We propose a wireless evaluation scheme for fiber Bragg gratings where the sensor signal is transmitted directly without any processing in a simplified sensor node. The underlying concept is explained in detail and validated experimentally. It is based on radio-over-fiber technology and evaluates not only the magnitude of the received analog electrical sensor signal but also the phase. Additionally, signal correction and signal processing schemes are discussed. A series of experimental measurements indicates not only advantages of the phase evaluation method over the magnitude evaluation method but also approves the general feasibility of the direct interrogation approach for wireless sensing applications. Future subjects of interest involve absolute accuracy considerations and maximum achievable sampling rates.

Readout IC Architectures and Strategies for Uncooled Micro-Bolometers Infrared Focal Plane Arrays: A Review.

InfraRed Focal Plane Arrays (IRFPAs) are crucial components in a wide range of applications, including night vision, thermal imaging and gas sensing. Among the various types of IRFPAs, micro-bolometer-based ones have gained significant attention due to their high sensitivity, low noise and low cost. However, their performance is heavily dependent on the readout interface, which converts the analog electrical signals provided by the micro-bolometers into digital signals for further processing and analysis. This paper briefly introduces these kinds of devices and their function, reporting and discussing a list of key parameters used to evaluate their performance; after that, the focus is shifted to the readout interface architecture with particular attention to the different strategies adopted, across the last two decades, in the design and development of the main blocks included in the readout chain.

Spectral sensitivity near exceptional points as a resource for hardware encryption

The spectral sensitivity near exceptional points (EPs) has been recently explored as an avenue for building sensors with enhanced sensitivity. However, to date, it is not clear whether this class of sensors does indeed outperform traditional sensors in terms of signal-to-noise ratio. In this work, we investigate the spectral sensitivity associated with EPs under a different lens and propose to utilize it as a resource for hardware security. In particular, we introduce a physically unclonable function (PUF) based on analogue electronic circuits that benefit from the drastic eigenvalues bifurcation near a divergent exceptional point to enhance the stochastic entropy caused by inherent parameter fluctuations in electronic components. This in turn results in a perfect entropy source for the generation of encryption keys encoded in analog electrical signals. This lightweight and robust analog-PUF structure may lead to a variety of unforeseen securities and anti-counterfeiting applications in radio-frequency fingerprinting and wireless communications.

Trainning profiles in motion sensor, facial expression, and mental commands for Emotiv Epoc+ in indicator LEDs interface

The study of the gyroscope method, facial expressions and mental commands using the Emotiv Epoc+ headset for driving indicator led is presented. The analog electrical signal provided by the inertial gyroscope located in the Emotiv headset, with the XY angular displacement and PITCH and JAW rotation, as well as the electrical pulses of cranial nerve VII associated with facial expressions and finally the extraction of the EEG signal acquired from the user's brain, are used to activate the output of indicator leds by developing a control program using Xavier Control Panel, Xavier Emokey and Visual Studio software. The electrical activation by means of the Emotiv Epoc+ headset favors several applications that can be explained with the leds and Arduino nano board interface.

Ultra-high-linearity integrated lithium niobate electro-optic modulators

Integrated lithium niobate (LN) photonics is a promising platform for future chip-scale microwave photonics systems owing to its unique electro-optic properties, low optical loss, and excellent scalability. A key enabler for such systems is a highly linear electro-optic modulator that could faithfully convert analog electrical signals into optical signals. In this work, we demonstrate a monolithic integrated LN modulator with an ultra-high spurious-free dynamic range (SFDR) of 120.04 dB · Hz 4 / 5 at 1 GHz, using a ring-assisted Mach–Zehnder interferometer configuration. The excellent synergy between the intrinsically linear electro-optic response of LN and an optimized linearization strategy allows us to fully suppress the cubic terms of third-order intermodulation distortions (IMD3) without active feedback controls, leading to ∼ 20 dB improvement over previous results in the thin-film LN platform. Our ultra-high-linearity LN modulators could become a core building block for future large-scale functional microwave photonic integrated circuits by further integration with other high-performance components like low-loss delay lines, tunable filters, and phase shifters available on the LN platform.

Improved exploiting modification direction steganography for hexagonal image processing

Steganography has made significant advances in the Square-pixel-based Image Processing (SIP) domain, but to our knowledge, no work has yet been done in Hexel (Hexagonal Pixel)-based Image Processing (HIP). This paper presents a HIP-domain data hiding method that exploits and improves the SIP-domain Exploiting Modification Direction (EMD) embedding scheme. The proposed method, Hexagonal EMD (HexEMD), utilizes a HIP-domain cover image's hexagonal nature and infrastructure to embed the secret message. In standard digital imaging systems, the sensor portion that converts photonic energy into an analog electrical signal and all the subunits that digitize, process, and display this signal are based on square pixel logic, so there is currently no commercial equipment available to produce HIP-domain images. Thus, the image is first transformed into the HIP domain in software using the infrastructure developed in the project. Then the HIP-domain image is partitioned into non-overlapping heptads of the standard size, each containing seven hexels. Rather than embedding segments to the independent pixel pairs as done in SIP-domain EMD, we do the embedding iteratively in each heptad. Experimental results show that the HexEMD outperforms its SIP equivalent, EMD, by improving embedding capacity and achieving low visual quality distortion.

All-optical serrodyne frequency shifter.

We describe and demonstrate a method to induce a single-sideband serrodyne-like optical frequency shift in an all-fiber device. The time-varying phase-shift is generated by cross-phase modulation in a nonlinear fiber. Unlike electro-optic based serrodyne methods, which require a high-fidelity and high-bandwidth analog electrical ramp modulation signal, the proposed optical method uses a simple pulsed pump and can be made simultaneously both low-loss and polarization-independent. We demonstrate the technique by shifting a 1550 nm optical signal 150 MHz in a 1.5 dB insertion-loss polarization-independent frequency shifter and show a pathway to multi-GHz shifting frequencies.

Tunable electro-optic analog-to-digital converter using graphene nanoshells in photonic crystal ring resonators

In this paper, we propose a novel design of a tunable electro-optic analog-to-digital converter. The proposed structure consists of a tunable three-channel demultiplexer and an optical encoder. The first part provides sampling and quantization of the input electrical analog signal based on the applied potential to the graphene nanoshells (GNSs), while the second part converts the quantized levels into two-bit binary code. The electro-optic demultiplexer is realized using three GNS-based photonic crystal resonant cavities and can be tuned by applying different biasing of the gate voltage to the GNSs. For appropriate chemical potential values of GNS, each resonant cavity can drop the optical beam into its corresponding output port. This tunable ultrafast device supports a maximum sampling rate of up to 222 GS/s, whereas its compact footprint is about 692 µ m 2 . The proposed device opens a new window to the design and fabrication of tunable graphene-based photonic crystal circuits to develop electro-optic on-chip processing systems.

Real-Time Direction Judgment System of Sub-Nanometer Scale Grating Ruler

This paper presents the design of a real-time direction judgment system for a sub-nanometer scale grating ruler based on field-programmable gate array (FPGA) technology. On the basis of the working principle of the grating ruler reading head, the characteristics of the grating ruler phase signal are analyzed. In view of the frequency uncertainty and nonlinear error of grating scale phase signal laser, a preprocessing structure based on biorthogonal lock-in amplifier is designed. Aiming at the problem of low data update rate and insensitivity to direction switching in short stroke of traditional grating direction judgment method, a real-time direction judgment method is proposed. On the FPGA platform, the signal generator is used to simulate the actual photoelectric signal of grating ruler, and the calibration experimental platform of electrical analog signal is built to verify the effect of the real-time direction judgment system on the FPGA platform. The results show that compared with the traditional direction judgment system, the data update rate is improved by 256-fold. Moreover, a method for using the result of the direction judgment system to compensate the count value of the electronic subdivision when the object is moving backward is proposed.

Gesture Recognition Through sEMG with Wearable Device Based on Deep Learning

It is conducive to the application of sEMG signals in helping disabled people through combining wearable devices with deep learning. Therefore, design of sEMG gesture recognition system using deep learning based on wearable device is proposed in this paper. The system is mainly consisted of wearable sEMG acquisition device and sEMG gesture recognition method based on deep learning. In the wearable sEMG acquisition device, the sEMG signal sensor is mainly used to convert the human bioelectrical signal into an analog electrical signal. Then it can be acquired using an analog to digital converter. We also use 2.4 GHz wireless communication for data transmission, and use the micro-controller as the core of system control and data processing. In the sEMG gesture recognition method, we designed a model of sEMG signal gesture classification based on convolutional neural network (CNN). It can avoid omission of important feature information and improve accuracy of recognition, effectively. In the experimental part, we collected the sEMG signals of three different gestures using our own wearable sEMG acquisition device. Then, we trained and evaluated on the designed sEMG gesture recognition model using these data. A recognition accuracy of about 79.43% can be achieved in three gestures. Finally, we trained and tested the sEMG gesture recognition model on the Ninapro DB5 dataset and can reach about 74.51% accuracy on 52 gestures. In the case that there are more types of gestures recognized, our accuracy is still 5.02%, 6.61%, and 2.58% higher than Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and Long Short Term Memory-CNN (LCNN), respectively. Also, the accuracy rate is 5.47% higher than SVM and Random Forests.

Optical Transmission of an Analog TV-Signal Coded at 2.24 GHz and Its Distribution by Using a Radiating Cable

In this work, an alternative technology to extend wireless coverage beyond the conventional methods of providing radio propagation coverage is presented. The use of a radiating cable is proposed for difficult-to-reach areas. In this regard, an indoor radiating cable is successfully employed for the distribution of an analog electric signal in a fiber-radio scheme using a microwave photonic filter. A filtered microwave band-pass window located at 2.24 GHz is used as an electrical carrier to transmit an analog TV-signal of 67.25 MHz over an optical link of 25.28 km. Measurements are carried out in an indoor environment. Experimental results demonstrate that the recovered signal is of good quality in each measurement location, exhibiting on average a signal-to-noise-ratio (SNR) of around 31.60 dB.

Field-Programmable Gate Array-Based Hardware Design of Optical Fiber Transducer Integrated Platform

This study focuses on the hardware architecture of a Raman scattering distributed optical fiber transducer platform, the principles of Raman scattering are analyzed, and the output 2 analog electrical signals are converted to digital signals at a 16-bit sampling rate by an Analog-to-Digital Converter (ADC). The system is implemented based on the FPGA. The integrated circuit is responsible for controlling the data acquisition process. The differential amplifier circuit, FPGA peripheral circuit, and CPU subsystem circuit, which takes ARM as the core, are separately designed. The composition of software includes a DDR2 (Double Data Rate 2) driver and central control logic. In this study, the optical fiber transducer platform has been tested. The CPU DDR2 is read/written by the test program respectively. According to the results, the program passes the read/write test. The NAND FLASH is tested. The results show that this program returns all operations successfully. The timing tests of the DDR2 interface and data latching are conducted. The results show that the read/write operations ensure that the clock and data curves are aligned. Therefore, the optical fiber transducer integrated platform designed in this study is effective.

Production of a Strain-Measuring Device with an Improved 3D Printer.

A traditional strain measurement sensor needs to be electrified and is susceptible to electromagnetic interference. In order to solve the fluctuations in the analog electrical signal in a traditional strain gauge operation, a new strain measurement method is presented here. It uses a photographic technique to display the strain change by amplifying the change of the pointer displacement of the mechanism. A visual polydimethylsiloxane (PDMS) lens with a focal length of 7.16 mm was added to a smartphone camera to generate a lens group acting as a microscope to capture images. It had an equivalent focal length of 5.74 mm. Acrylonitrile butadiene styrene (ABS) and nylon amplifiers were used to test the influence of different materials on the sensor performance. The production of the amplifiers and PDMS lens is based on improved 3D printing technology. The data obtained were compared with the results from finite element analysis (FEA) to verify their validity. The sensitivity of the ABS amplifier was 36.03 ± 1.34 µε/µm, and the sensitivity of the nylon amplifier was 36.55 ± 0.53 µε/µm.

Equivalent Data Information of Sensory and Motor Signals in the Human Body

In this paper, the amount of information collected by sensory and motor organs is analyzed. Humans use their senses to recognize the information around them and to perform appropriate actions. To perform these processes, information is exchanged between organs via analog electrical signals. Analog electrical signals convey information transmitted from human sensory organs to the cerebrum or commands sent from the cerebrum to the appropriate motor organs. This paper analyzes the amount of analog signal information generated inside the human body and converts this information into equivalent digital data. This process is carried out in an effort to build a human-like humanoid based on the equivalent digital data. The analog information generated in the human body is investigated based on the medical publications to date. These analyses result in the bit rate and delay requirements of nervous systems that are built with digital networks. It is shown in this paper that both artificial eyes equivalently generate approximately 14 Gigabits from a one-time look when a humanoid performs at a human-like level. In addition, it is realized that the human body is more sensitive to pressure than to temperature since the pressure sensation generates, on average, more information than the temperature sensation.

Research on the technology of abnormal discharge detection device for metal fittings based on optical fiber signal transmission

This paper aims to develop an abnormal discharge detection device based on optical fiber signal transmission, and realize the reliable detection of abnormal discharge between fittings of high voltage electrical equipment. The detector and visible light detector developed in the arc light detection part can realize the efficient detection of ultraviolet light and visible light in the arc light. By optical fiber far - range signal transmission structure, this design developed multifunctional optical signal collector, which can be converted into analog electric signal, state quantity signal, digital quantity signal and other forms while collecting arc light efficiently.

Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks

We introduce an electro-optic hardware platform for nonlinear activation functions in optical neural networks. The optical-to-optical nonlinearity operates by converting a small portion of the input optical signal into an analog electric signal, which is used to intensity-modulate the original optical signal with no reduction in processing speed. Our scheme allows for complete nonlinear on-off contrast in transmission at relatively low optical power thresholds and eliminates the requirement of having additional optical sources between each layer of the network. Moreover, the activation function is reconfigurable via electrical bias, allowing it to be programmed or trained to synthesize a variety of nonlinear responses. Using numerical simulations, we demonstrate that this activation function significantly improves the expressiveness of optical neural networks, allowing them to perform well on two benchmark machine learning tasks: learning a multi-input exclusive-OR (XOR) logic function and classification of images of handwritten numbers from the MNIST dataset. The addition of the nonlinear activation function improves test accuracy on the MNIST task from 85% to 94%.

MODELING OF STATIC CHARACTERISTICS OF PNEUMATIC STRAIN GAUGE TRANSDUCER

Measuring instruments that implement the pneumatic principle of measurement, have a number of significant advantages: small dimensions of the measuring equipment, allowing to produce multiparameter control in a limited size of the working area, insensitivity to vibration, simplicity of design and reliability. The disadvantage of pneumatic converters is a discrete output electrical signal, which does not allow the processing of measurement results. In this regard, it seems appropriate to investigate the pneumatic-electric Converter, which includes a jet pneumatic and differential strain gauges, which allows to obtain an analog electrical signal at the output. The article describes the design and principle of operation pneumoenteritis Converter to control the diameter of the part. Pneumotensometric Converter converts the change in the diameter of the part in the movement of the nozzle, which causes a change in the force of the air jet on the beam, its deformation and, accordingly, a change in the resistance of he strain gauge. An expression describing the stoic characteristic of the transducer and allowing to determine the force of the air jet impact on the load cell from the gap between the nozzle and the beam, the air pressure and the nozzle diameter is given. The results of modeling the static characteristics of the Converter at different combinations of design parameters are given, the values of straight sections of characteristics and sensitivity are determined, their comparative evaluation is given.