Novel stability approach using Routh-Hurwitz criterion for brain computer interface applications.

BACKGROUND: The stability criterion approach is very important for estimating precise behavior before or after fabricating brain computer interface system applications. OBJECTIVE: A novel approach using the Routh-Hurwitz standard criterion method is proposed to easily determine and analyze the stability of brain computer interface system applications. Using this developed approach, we were able to easily test the stability of technical issue using simple programmed codes before or after brain computer interfaces fabrication applications. METHODS: Using a MATLAB simulation program package, we are able to provide two different special case examples such as a first zero element and a row of zeros to verify the capability of our proposed Routh-Hurwitz method. RESULTS: The MATLAB simulation program provided efficient Routh-Hurwitz standard criterion results by differentiating the highest coefficients of the s and a. CONCLUSION: This technical paper explains how to use our proposed new Routh-Hurwitz standard condition to simply ascertain and determine the brain computer interface system stability without customized commercial simulation tools.

Design of Preamplifier for Ultrasound Transducers.

In diagnostic ultrasound imaging applications, preamplifiers are used as first-stage analog front-end amplifiers for ultrasound transducers because they can amplify weak acoustic signals generated directly by ultrasound transducers. For emerging diagnostic ultrasound imaging applications, different types of preamplifiers with specific design parameters and circuit topologies have been developed, depending on the types of the ultrasound transducer. In particular, the design parameters of the preamplifier, such as the gain, bandwidth, input- or output-referred noise components, and power consumption, have a tradeoff relationship. Guidelines on the detailed design concept, design parameters, and specific circuit design techniques of the preamplifier used for ultrasound transducers are outlined in this paper, aiming to help circuit designers and academic researchers optimize the performance of ultrasound transducers used in the diagnostic ultrasound imaging applications for research directions.

Power Amplifier Design for Ultrasound Applications.

A design analysis of the power amplifiers developed for ultrasound applications was conducted because ultrasound applications require different types of power amplifiers, which are one of the most critical electronic components in ultrasound systems. To generate acoustic signals using transducers, which are among the most important mechanical devices in ultrasound systems, an appropriate output voltage, current, or power signal must be produced by a power amplifier. Therefore, an appropriate design analysis of the power amplifier must be conducted to obtain the optimal performance from a transducer. In addition, because of new ultrasound research trends, such as ultrasound systems with other imaging modalities and wireless ultrasound systems, the selection of an appropriate power amplifier could improve the performance of an ultrasound system with other imaging and therapy modalities. This paper describes the design parameters of a power amplifier, including the gain, bandwidth, harmonic distortion, and efficiency. Each power amplifier has specific applications and limitations. Therefore, this review will assist design engineers and ultrasound researchers who need to develop or use power amplifiers in ultrasound applications.

Harmonic-Reduced Bias Circuit for Ultrasound Transducers.

The gain of class-C power amplifiers is generally lower than that of class-A power amplifiers. Thus, higher-amplitude input voltage signals for class-C power amplifiers are required. However, high-amplitude input signals generate unwanted harmonic signals. Therefore, a novel bias circuit was proposed to suppress the harmonic signals generated by class-C power amplifiers, which improves the output voltage amplitudes. To verify the proposed idea, the input harmonic signals when using a harmonic-reduced bias circuit (-61.31 dB, -89.092 dB, -90.53 dB, and -90.32 dB) were measured and were found to be much lower than those when using the voltage divider bias circuit (-57.19 dB, -73.49 dB, -70.97 dB, and -73.61 dB) at 25 MHz, 50 MHz, 75 MHz, and 100 MHz, respectively. To further validate the proposed idea, the pulse-echo measurements were compared using the bias circuits. The peak-to-peak echo amplitude and bandwidth of the piezoelectric transducer, measured when using a harmonic-reduced bias circuit (27.07 mV and 37.19%), were higher than those achieved with a voltage divider circuit (18.55 mV and 22.71%). Therefore, the proposed scheme may be useful for ultrasound instruments with low sensitivity.

Development of a robust eye exam diagnosis platform with a deep learning model.

BACKGROUND: Eye exam diagnosis is one of the early detection methods for eye diseases. However, such a method is dependent on expensive and unpredictable optical equipment. OBJECTIVE: The eye exam can be re-emerged through an optometric lens attached to a smartphone and come to read the diseases automatically. Therefore, this study aims to provide a stable and predictable model with a given dataset representing the target group domain and develop a new method to identify eye disease with accurate and stable performance. METHODS: The ResNet-18 models pre-trained on ImageNet data composed of 1,000 everyday objects were employed to learn the dataset's features and validate the test dataset separated from the training dataset. RESULTS: A proposed model showed high training and validation accuracy values of 99.1% and 96.9%, respectively. CONCLUSION: The designed model could produce a robust and stable eye disease discrimination performance.

An Inverse Class-E Power Amplifier for Ultrasound Transducer.

An inverse Class-E power amplifier was designed for an ultrasound transducer. The proposed inverse Class-E power amplifier can be useful because of the low series inductance values used in the output matching network that helps to reduce signal distortions. Therefore, a newly designed Class-E power amplifier can obtain a proper echo signal quality. The measured output voltage, voltage gain, voltage gain difference, and power efficiency were 50.1 V, 22.871 dB, 0.932 dB, and 55.342%, respectively. This low voltage difference and relatively high efficiency could verify the capability of the ultrasound transducer. The pulse-echo response experiment using an ultrasound transducer was performed to verify the capability of the proposed inverse Class-E power amplifier. The obtained echo signal amplitude and pulse width were 6.01 mVp-p and 0.81 µs, respectively. The -6 dB bandwidth and center frequencies of the echo signal were 27.25 and 9.82 MHz, respectively. Consequently, the designed Class-E power amplifier did not significantly alter the performance of the center frequency of the ultrasound transducer; therefore, it could be employed particularly in certain ultrasound applications that require high linearity and reasonable power efficiency.

Secured computed tomography scanner using a random bit.

BACKGROUND: Patient data in current computed tomography scanner machines are transferred through several communication channels, such as WiFi, to the mobile channel platform. Therefore, patient information is an important security concern. Medical imaging must be protected using various methods. OBJECTIVE: The current hardware-dependent method for generating random bits exhibits predictable or inconvenient physical characteristics. Therefore, a more flexible random-bit generation technique is to be devised. METHODS: We propose a deterministic random bit generation algorithm that uses a mathematical periodic function. RESULTS: After randomizing the image using the proposed random bit, the performance is analyzed and compared with that of the processed image. CONCLUSION: The random bit generation method using a mathematical algorithm shows higher entropy than the random bit generated by hardware.

A Doherty Power Amplifier for Ultrasound Instrumentation.

The ultrasound instrumentation uses linear power amplifiers with low power efficiency, generating unwanted heat and resulting in the deterioration of the echo signal quality of measured targets. Therefore, this study aims to develop a power amplifier scheme to increase power efficiency while maintaining appropriate echo signal quality. In communication systems, the Doherty power amplifier has shown relatively good power efficiency while producing high signal distortion. The same design scheme cannot be directly applied to ultrasound instrumentation. Therefore, the Doherty power amplifier needs to be re-designed. To verify the feasibility of the instrumentation, a Doherty power amplifier was designed to obtain high power efficiency. The measured gain, output 1-dB compression point, and power-added efficiency of the designed Doherty power amplifier were 33.71 dB, 35.71 dBm, and 57.24% at 25 MHz, respectively. In addition, the performance of the developed amplifier was measured and tested using the ultrasound transducer through the pulse-echo responses. The output power with 25 MHz, 5-cycle, and 43.06 dBm generated from the Doherty power amplifier was sent through the expander to the focused ultrasound transducer with 25 MHz and 0.5″ diameter. The detected signal was sent via a limiter. Afterwards, the signal was amplified by a 36.8 dB gain preamplifier, and then displayed in the oscilloscope. The measured peak-to-peak amplitude in the pulse-echo response with an ultrasound transducer was 0.9698 V. The data showed a comparable echo signal amplitude. Therefore, the designed Doherty power amplifier can improve the power efficiency used for medical ultrasound instrumentation.

Optical Light Sources and Wavelengths within the Visible and Near-Infrared Range Using Photoacoustic Effects for Biomedical Applications.

The photoacoustic (PA) effect occurs when sound waves are generated by light according to the thermodynamic and optical properties of the materials; they are absorption spectroscopic techniques that can be applied to characterize materials that absorb pulse or continuous wave (CW)-modulated electromagnetic radiation. In addition, the wavelengths and properties of the incident light significantly impact the signal-to-ratio and contrast with photoacoustic signals. In this paper, we reviewed how absorption spectroscopic research results have been used in applying actual photoacoustic effects, focusing on light sources of each wavelength. In addition, the characteristics and compositions of the light sources used for the applications were investigated and organized based on the absorption spectrum of the target materials. Therefore, we expect that this study will help researchers (who desire to study photoacoustic effects) to more efficiently approach the appropriate conditions or environments for selecting the target materials and light sources.

A Mathematically Generated Noise Technique for Ultrasound Systems.

Ultrasound systems have been widely used for consultation; however, they are susceptible to cyberattacks. Such ultrasound systems use random bits to protect patient information, which is vital to the stability of information-protecting systems used in ultrasound machines. The stability of the random bit must satisfy its unpredictability. To create a random bit, noise generated in hardware is typically used; however, extracting sufficient noise from systems is challenging when resources are limited. There are various methods for generating noises but most of these studies are based on hardware. Compared with hardware-based methods, software-based methods can be easily accessed by the software developer; therefore, we applied a mathematically generated noise function to generate random bits for ultrasound systems. Herein, we compared the performance of random bits using a newly proposed mathematical function and using the frequency of the central processing unit of the hardware. Random bits are generated using a raw bitmap image measuring 1000 × 663 bytes. The generated random bit analyzes the sampling data in generation time units as time-series data and then verifies the mean, median, and mode. To further apply the random bit in an ultrasound system, the image is randomized by applying exclusive mixing to a 1000 × 663 ultrasound phantom image; subsequently, the comparison and analysis of statistical data processing using hardware noise and the proposed algorithm were provided. The peak signal-to-noise ratio and mean square error of the images are compared to evaluate their quality. As a result of the test, the min entropy estimate (estimated value) was 7.156616/8 bit in the proposed study, which indicated a performance superior to that of GetSystemTime. These results show that the proposed algorithm outperforms the conventional method used in ultrasound systems.

Pre-Matching Circuit for High-Frequency Ultrasound Transducers.

High-frequency ultrasound transducers offer higher spatial resolution than low-frequency ultrasound transducers; however, their maximum sensitivity are lower. Matching circuits are commonly utilized to increase the amplitude of high-frequency ultrasound transducers because the size of the piezoelectric material decreases as the operating frequency of the transducer increases. Thus, it lowers the limit of the applied voltage to the piezoelectric materials. Additionally, the electrical impedances of ultrasound transducers generally differ at the resonant-, center-, and anti-resonant-frequencies. The currently developed most-matching circuits provide electrical matching at the center frequency ranges for ultrasound transmitters and transducers. In addition, matching circuits with transmitters are more difficult to use to control the echo signal quality of the transducers because it is harder to control the bandwidth and gain of an ultrasound transmitter working in high-voltage operation. Therefore, we provide a novel pre-matching circuit method to improve the amplitude and bandwidth of high-frequency ultrasound transducers at the resonant-, center-, and anti-resonant-frequency ranges, with an ultrasound receiver and transducer. To verify the pre-matching circuit, pulse-echo response tests were conducted on the ultrasound transducers. The results show that the designed pre-matching circuits provide higher amplitude (5.63- and 2.02-times) and wider bandwidth (175.55% and 62.01%) for the high-frequency ultrasound transducer compared to the original circuit without a pre-matching circuit, and the parallel capacitor with a series-inductor circuit, respectively; therefore, the proposed pre-matching circuit is an appropriate solution for improving the amplitudes and bandwidths of high-frequency ultrasound transducers over wide frequency ranges.

A Novel Quick-Response Eigenface Analysis Scheme for Brain-Computer Interfaces.

The brain-computer interface (BCI) is used to understand brain activities and external bodies with the help of the motor imagery (MI). As of today, the classification results for EEG 4 class BCI competition dataset have been improved to provide better classification accuracy of the brain computer interface systems (BCIs). Based on this observation, a novel quick-response eigenface analysis (QR-EFA) scheme for motor imagery is proposed to improve the classification accuracy for BCIs. Thus, we considered BCI signals in standardized and sharable quick response (QR) image domain; then, we systematically combined EFA and a convolution neural network (CNN) to classify the neuro images. To overcome a non-stationary BCI dataset available and non-ergodic characteristics, we utilized an effective neuro data augmentation in the training phase. For the ultimate improvements in classification performance, QR-EFA maximizes the similarities existing in the domain-, trial-, and subject-wise directions. To validate and verify the proposed scheme, we performed an experiment on the BCI dataset. Specifically, the scheme is intended to provide a higher classification output in classification accuracy performance for the BCI competition 4 dataset 2a (C4D2a_4C) and BCI competition 3 dataset 3a (C3D3a_4C). The experimental results confirm that the newly proposed QR-EFA method outperforms the previous the published results, specifically from 85.4% to 97.87% ± 0.75 for C4D2a_4C and 88.21% ± 6.02 for C3D3a_4C. Therefore, the proposed QR-EFA could be a highly reliable and constructive framework for one of the MI classification solutions for BCI applications.

Whitening Technique Based on Gram-Schmidt Orthogonalization for Motor Imagery Classification of Brain-Computer Interface Applications.

A novel whitening technique for motor imagery (MI) classification is proposed to reduce the accuracy variance of brain-computer interfaces (BCIs). This method is intended to improve the electroencephalogram eigenface analysis performance for the MI classification of BCIs. In BCI classification, the variance of the accuracy among subjects is sensitive to the accuracy itself for superior classification results. Hence, with the help of Gram-Schmidt orthogonalization, we propose a BCI channel whitening (BCICW) scheme to minimize the variance among subjects. The newly proposed BCICW method improved the variance of the MI classification in real data. To validate and verify the proposed scheme, we performed an experiment on the BCI competition 3 dataset IIIa (D3D3a) and the BCI competition 4 dataset IIa (D4D2a) using the MATLAB simulation tool. The variance data when using the proposed BCICW method based on Gram-Schmidt orthogonalization was much lower (11.21) than that when using the EFA method (58.33) for D3D3a and decreased from (17.48) to (9.38) for D4D2a. Therefore, the proposed method could be effective for MI classification of BCI applications.

Hexagonal Stimulation Digital Controller Design and Verification for Wireless Subretinal Implant Device.

Significant progress has been made in the field of micro/nano-retinal implant technologies. However, the high pixel range, power leakage, reliability, and lifespan of retinal implants are still questionable. Active implantable devices are safe, cost-effective, and reliable. Although a device that can meet basic safety requirements set by the Food and Drug Administration and the European Union is reliable for long-term use and provides control on current and voltage parameters, it will be expensive and cannot be commercially successful. This study proposes an economical, fully controllable, and configurable wireless communication system based on field-programmable gated arrays (FPGAs) that were designed with the ability to cope with the issues that arise in retinal implantation. This system incorporates hexagonal biphasic stimulation pulses generated by a digital controller that can be fully controlled using an external transmitter. The integration of two separate domain analog systems and a digital controller based on FPGAs is proposed in this study. The system was also implemented on a microchip and verified using in vitro results.

Fully Customized Photoacoustic System Using Doubly Q-Switched Nd:YAG Laser and Multiple Axes Stages for Laboratory Applications.

We developed a customized doubly Q-switched laser that can control the pulse width to easily find weak acoustic signals for photoacoustic (PA) systems. As the laser was constructed using an acousto-optic Q-switcher, in contrast to the existing commercial laser system, it is easier to control the pulse repetition rate and pulse width. The laser has the following control ranges: 10 Hz-10 kHz for the pulse repetition rate, 40-150 ns for the pulse width, and 50-500 µJ for the pulse energy. Additionally, a custom-made modularized sample stage was used to develop a fully customized PA system. The modularized sample stage has a nine-axis control unit design for the PA system, allowing the sample target and transducer to be freely adjusted. This makes the system suitable for capturing weak PA signals. Images were acquired and processed for widely used sample targets (hair and insulating tape) with the developed fully customized PA system. The customized doubly Q-switched laser-based PA imaging system presented in this paper can be modified for diverse conditions, including the wavelength, frequency, pulse width, and sample target; therefore, we expect that the proposed technique will be helpful in conducting fundamental and applied research for PA imaging system applications.

Low-Area Four-Channel Controlled Dielectric Breakdown System Design for Point-of-Care Applications.

In this study, we propose a low-area multi-channel controlled dielectric breakdown (CDB) system that simultaneously produces several nanopore sensors. Conventionally, solid-state nanopores are prepared by etching or drilling openings in a silicon nitride (SiNx) substrate, which is expensive and requires a long processing time. To address these challenges, a CDB technique was introduced and used to fabricate nanopore channels in SiNx membranes. However, the nanopore sensors produced by the CDB result in a severe pore-to-pore diameter variation as a result of different fabrication conditions and processing times. Accordingly, it is indispensable to simultaneously fabricate nanopore sensors in the same environment to reduce the deleterious effects of pore-to-pore variation. In this study, we propose a four-channel CDB system that comprises an amplifier that boosts the command voltage, a 1-to-4 multiplexer, a level shifter, a low-noise transimpedance amplifier and a data acquisition device. To prove our design concept, we used the CDB system to fabricate four nanopore sensors with diameters of <10 nm, and its in vitro performance was verified using λ-DNA samples.

Fisheye lens design for solar-powered mobile ultrasound devices.

BACKGROUND: Compared to benchtop ultrasound machines, mobile ultrasound machines require portable batteries when acquiring information regarding human tissues during outdoor activities. OBJECTIVE: A novel fisheye lens type was designed to address the charging issue where it is difficult to constantly track the sun. This method does not require the use of a mechanical motor that constantly tracks the sun to charge the portable batteries. METHODS: To obtain an optical solar power system, the numerical aperture (NA) and field angle must be increased. Therefore, we use the fisheye lens with the largest field angle. RESULTS: The NA of the designed fisheye lens system reaches 0.75, allowing light collection of approximately ± 48∘. Additionally, the efficiency ratio of the central and surrounding areas also satisfies more than 80% at a field angle of 85∘ and more than 70% at field angles of 85∘ to 90∘, respectively. CONCLUSIONS: We designed a novel fisheye lens for solar-powered mobile ultrasound machines used outdoors.

Novel dual-resistor-diode limiter circuit structures for high-voltage reliable ultrasound receiver systems.

BACKGROUND: The limiters have been used to protect the ultrasound receivers because of the inherent characteristic of the transducers which are required to use the high voltage excitation to obtain the reasonable echo signal amplitudes. OBJECTIVE: Among the variety of the limiters, the performances of discharge voltage degradation from the limiters gradually deteriorate the whole ultrasound systems according to the applied voltages of the ultrasonic transducers. This could cause the ultrasound systems to be unreliable for the long-term operations, resulting in possibly breaking the receiver systems. METHODS: Designed limiters were evaluated with insertion loss, total harmonic distortion, and pulse-echo responses with the ultrasound transducer devices. RESULTS: Designed new dual-resistor-diode limiters exhibited greater and faster suppression of the pulse width (1.15 V and 6.1 µs) for high-voltage signals. CONCLUSIONS: Our proposed dual-resistor-diode limiter could be one of the potential candidates for reliable ultrasound receiver system.

Ambient Light Rejection Integrated Circuit for Autonomous Adaptation on a Sub-Retinal Prosthetic System.

This paper introduces an ambient light rejection (ALR) circuit for the autonomous adaptation of a subretinal implant system. The sub-retinal implants, located beneath a bipolar cell layer, are known to have a significant advantage in spatial resolution by integrating more than a thousand pixels, compared to epi-retinal implants. However, challenges remain regarding current dispersion in high-density retinal implants, and ambient light induces pixel saturation. Thus, the technical issues of ambient light associated with a conventional image processing technique, which lead to high power consumption and area occupation, are still unresolved. Thus, it is necessary to develop a novel image-processing unit to handle ambient light, considering constraints related to power and area. In this paper, we present an ALR circuit as an image-processing unit for sub-retinal implants. We first introduced an ALR algorithm to reduce the ambient light in conventional retinal implants; next, we implemented the ALR algorithm as an application-specific integrated chip (ASIC). The ALR circuit was fabricated using a standard 0.35-µm CMOS process along with an image-sensor-based stimulator, a sensor pixel, and digital blocks. As experimental results, the ALR circuit occupies an area of 190 µm2, consumes a power of 3.2 mW and shows a maximum response time of 1.6 s at a light intensity of 20,000 lux. The proposed ALR circuit also has a pixel loss rate of 0.3%. The experimental results show that the ALR circuit leads to a sensor pixel (SP) being autonomously adjusted, depending on the light intensity.

Printed Circuit Board Defect Detection Using Deep Learning via A Skip-Connected Convolutional Autoencoder.

As technology evolves, more components are integrated into printed circuit boards (PCBs) and the PCB layout increases. Because small defects on signal trace can cause significant damage to the system, PCB surface inspection is one of the most important quality control processes. Owing to the limitations of manual inspection, significant efforts have been made to automate the inspection by utilizing high resolution CCD or CMOS sensors. Despite the advanced sensor technology, setting the pass/fail criteria based on small failure samples has always been challenging in traditional machine vision approaches. To overcome these problems, we propose an advanced PCB inspection system based on a skip-connected convolutional autoencoder. The deep autoencoder model was trained to decode the original non-defect images from the defect images. The decoded images were then compared with the input image to identify the defect location. To overcome the small and imbalanced dataset in the early manufacturing stage, we applied appropriate image augmentation to improve the model training performance. The experimental results reveal that a simple unsupervised autoencoder model delivers promising performance, with a detection rate of up to 98% and a false pass rate below 1.7% for the test data, containing 3900 defect and non-defect images.