Optimizing Image Enhancement: Feature Engineering for Improved Classification in AI-Assisted Artificial Retinas.

Artificial retinas have revolutionized the lives of many blind people by enabling their ability to perceive vision via an implanted chip. Despite significant advancements, there are some limitations that cannot be ignored. Presenting all objects captured in a scene makes their identification difficult. Addressing this limitation is necessary because the artificial retina can utilize a very limited number of pixels to represent vision information. This problem in a multi-object scenario can be mitigated by enhancing images such that only the major objects are considered to be shown in vision. Although simple techniques like edge detection are used, they fall short in representing identifiable objects in complex scenarios, suggesting the idea of integrating primary object edges. To support this idea, the proposed classification model aims at identifying the primary objects based on a suggested set of selective features. The proposed classification model can then be equipped into the artificial retina system for filtering multiple primary objects to enhance vision. The suitability of handling multi-objects enables the system to cope with real-world complex scenarios. The proposed classification model is based on a multi-label deep neural network, specifically designed to leverage from the selective feature set. Initially, the enhanced images proposed in this research are compared with the ones that utilize an edge detection technique for single, dual, and multi-object images. These enhancements are also verified through an intensity profile analysis. Subsequently, the proposed classification model's performance is evaluated to show the significance of utilizing the suggested features. This includes evaluating the model's ability to correctly classify the top five, four, three, two, and one object(s), with respective accuracies of up to 84.8%, 85.2%, 86.8%, 91.8%, and 96.4%. Several comparisons such as training/validation loss and accuracies, precision, recall, specificity, and area under a curve indicate reliable results. Based on the overall evaluation of this study, it is concluded that using the suggested set of selective features not only improves the classification model's performance, but aligns with the specific problem to address the challenge of correctly identifying objects in multi-object scenarios. Therefore, the proposed classification model designed on the basis of selective features is considered to be a very useful tool in supporting the idea of optimizing image enhancement.

Enhancing Human Activity Recognition through Integrated Multimodal Analysis: A Focus on RGB Imaging, Skeletal Tracking, and Pose Estimation.

Human activity recognition (HAR) is pivotal in advancing applications ranging from healthcare monitoring to interactive gaming. Traditional HAR systems, primarily relying on single data sources, face limitations in capturing the full spectrum of human activities. This study introduces a comprehensive approach to HAR by integrating two critical modalities: RGB imaging and advanced pose estimation features. Our methodology leverages the strengths of each modality to overcome the drawbacks of unimodal systems, providing a richer and more accurate representation of activities. We propose a two-stream network that processes skeletal and RGB data in parallel, enhanced by pose estimation techniques for refined feature extraction. The integration of these modalities is facilitated through advanced fusion algorithms, significantly improving recognition accuracy. Extensive experiments conducted on the UTD multimodal human action dataset (UTD MHAD) demonstrate that the proposed approach exceeds the performance of existing state-of-the-art algorithms, yielding improved outcomes. This study not only sets a new benchmark for HAR systems but also highlights the importance of feature engineering in capturing the complexity of human movements and the integration of optimal features. Our findings pave the way for more sophisticated, reliable, and applicable HAR systems in real-world scenarios.

Sensors, Circuits, and Systems for Biomedical Applications.

Sensor technologies (including electrodes) have been widely utilized in many applications, especially in fields such as smart factories, automation, clinics, laboratories, and more [...].

Integrated Low-Voltage Compliance and Wide-Dynamic Stimulator Design for Neural Implantable Devices.

In this study, a pulse frequency modulation (PFM)-based stimulator is proposed for use in biomedical implantable devices. Conventionally, functional electrical stimulation (FES) techniques have been used to reinforce damaged nerves, such as retina tissue and brain tissue, by injecting a certain amount of charge into tissues. Although several design methods are present for implementing FES devices, an FES stimulator for retinal implants is difficult to realize because of the chip area, which needs to be inserted in a fovea, sized 5 mm x 5 mm, and power limitations to prevent the heat generation that causes tissue damage. In this work, we propose a novel stimulation structure to reduce the compliance voltage during stimulation, which can result in high-speed and low-voltage operation. A new stimulator that is composed of a modified high-speed PFM, a 4-bit counter, a serializer, a digital controller, and a current driver is designed and verified using a DB HiTek standard 0.18 µm process. This proposed stimulator can generate a charge up to 130 nC, consumes an average power of 375 µW during a stimulation period, and occupies a total area of 700 µm × 68 µm.

Integrated High-Temporal-Resolution and High-Density Subretinal Prosthesis Using a Correlated Double-Sampling Technique.

This paper presents a 1600-pixel integrated neural stimulator with a correlated double-sampling readout (DSR) circuit for a subretinal prosthesis. The retinal stimulation chip inserted beneath the photoreceptor layer comprises an array of an active pixel sensor (APS) and biphasic pulse shaper. The DSR circuit achieves a high signal-to-noise ratio (SNR) of the APS with a short integration time to simultaneously improve the temporal and spatial resolutions of restored vision. This DSR circuit is adopted along with a 5 × 5-pixel tile, which reduces pixel size and improves the SNR by increasing the area occupied by storage capacitors. Moreover, a low-mismatch reference generator enables a low standard deviation between individual pulse shapers. The 1600-pixel retinal chip, fabricated using the 0.18 µm 1P6M CMOS process, occupies a total area of 4.3 mm × 3.3 mm and dissipates an average power of 3.4 mW; this was demonstrated by determining the stimulus current patterns corresponding to the illuminations of an LCD projector. Experimental results show that the proposed high-density stimulation array chip can achieve a high temporal resolution owing to its short integration time.

Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs.

Dynamic consent management allows a data subject to dynamically govern her consent to access her data. Clearly, security and privacy guarantees are vital for the adoption of dynamic consent management systems. In particular, specific data protection guarantees can be required to comply with rules and laws (e.g., the General Data Protection Regulation (GDPR)). Since the primary instantiation of the dynamic consent management systems in the existing literature is towards developing sustainable e-healthcare services, in this paper, we study data protection issues in dynamic consent management systems, identifying crucial security and privacy properties and discussing severe limitations of systems described in the state of the art. We have presented the precise definitions of security and privacy properties that are essential to confirm the robustness of the dynamic consent management systems against diverse adversaries. Finally, under those precise formal definitions of security and privacy, we have proposed the implications of state-of-the-art tools and technologies such as differential privacy, blockchain technologies, zero-knowledge proofs, and cryptographic procedures that can be used to build dynamic consent management systems that are secure and private by design.

Data Provenance in Healthcare: Approaches, Challenges, and Future Directions.

Data provenance means recording data origins and the history of data generation and processing. In healthcare, data provenance is one of the essential processes that make it possible to track the sources and reasons behind any problem with a user's data. With the emergence of the General Data Protection Regulation (GDPR), data provenance in healthcare systems should be implemented to give users more control over data. This SLR studies the impacts of data provenance in healthcare and GDPR-compliance-based data provenance through a systematic review of peer-reviewed articles. The SLR discusses the technologies used to achieve data provenance and various methodologies to achieve data provenance. We then explore different technologies that are applied in the healthcare domain and how they achieve data provenance. In the end, we have identified key research gaps followed by future research directions.

Psychometric properties of the Barriers Self-Efficacy Scale for Physical Activity-Korean.

This study examined the psychometric properties of the Barriers Self-Efficacy Scale-Physical Activity for Korean-speaking adults with osteoarthritis at risk for metabolic syndrome (N = 150). Factor analysis identified three dimensions of the Korean Barriers scale, explaining 65.9 % of the total variance. Confirmatory factor analysis indicated that the structural validity adequately fits the data. Construct validity confirmed significant associations between the amount of physical activity and psychological variables. The test-retest reliability was 0.87; the alpha was 0.90. The standardized response mean (0.497) indicated responsiveness to medium-magnitude change. The Korean Barriers scale can assess self-efficacy to engage in regular physical activity in clinical settings.

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.

Real-Time Sound Source Localization for Low-Power IoT Devices Based on Multi-Stream CNN.

Voice-activated artificial intelligence (AI) technology has advanced rapidly and is being adopted in various devices such as smart speakers and display products, which enable users to multitask without touching the devices. However, most devices equipped with cameras and displays lack mobility; therefore, users cannot avoid touching them for face-to-face interactions, which contradicts the voice-activated AI philosophy. In this paper, we propose a deep neural network-based real-time sound source localization (SSL) model for low-power internet of things (IoT) devices based on microphone arrays and present a prototype implemented on actual IoT devices. The proposed SSL model delivers multi-channel acoustic data to parallel convolutional neural network layers in the form of multiple streams to capture the unique delay patterns for the low-, mid-, and high-frequency ranges, and estimates the fine and coarse location of voices. The model adapted in this study achieved an accuracy of 91.41% on fine location estimation and a direction of arrival error of 7.43° on noisy data. It achieved a processing time of 7.811 ms per 40 ms samples on the Raspberry Pi 4B. The proposed model can be applied to a camera-based humanoid robot that mimics the manner in which humans react to trigger voices in crowded environments.

Two-Way Communication Digital Power Controllers for Wireless Retinal Prosthesis Systems.

Power-efficient digital controllers are proposed for wireless retinal prosthetic systems. Power management plays an important role in reducing the power consumption and avoiding malfunctions in implantable medical devices. In the case of implantable devices with only one-way communication, the received power level is uncertain because there is no feedback on the power status. Accordingly, system breakdown due to inefficient power management should be avoided to prevent harm to patients. In this study, digital power controllers were developed for achieving two-way communication. Three controllers-a forward and back telemetry control unit, a power control unit, and a preamble control unit-operated simultaneously to control the class-E amplifier input power, provided command data to stimulators, monitored the power levels of the implanted devices, and generated back telemetry data. For performance verification, we implemented a digital power control system using a field-programmable gate array and then demonstrated it by employing a wireless telemetry system.

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.

Comparable clinical and radiological outcomes between anatomical and high femoral tunnels in posterior cruciate ligament reconstruction.

PURPOSE: To compare clinical and radiological outcomes and failure rates between anatomical and high femoral tunnels in remnant-preserving single-bundle posterior cruciate ligament (PCL) reconstruction. METHODS: 63 patients who underwent remnant-preserving single-bundle PCL reconstruction between 2011 and 2018 with a minimum 2-year follow-up were retrospectively reviewed. Patients were divided into two groups according to the femoral tunnel position: group A (33 patients with anatomical femoral tunnel) and group H (30 patients with high femoral tunnels). The femoral tunnel was positioned at the center (group A) or upper margin (group H) of the remnant anterolateral bundle. The position of the femoral tunnel was evaluated using the grid method on three-dimensional computed tomography. Clinical and radiological outcomes and failure rates were compared between the groups at the 2-year follow-up. RESULTS: The position of the femoral tunnel was significantly high in group H than in group A (87.4% ± 4.2% versus 76.1% ± 3.7%, p < 0.001). Clinical outcomes were not significantly different between the two groups in terms of the clinical scores (International Knee Documentation Committee subjective, Lysholm, and Tegner activity scores), range of motion, and posterior drawer test. Radiological outcomes also showed no intergroup differences in the side-to-side differences of posterior tibial translation and osteoarthritis progression. Side-to-side difference on the Telos stress radiograph was 5.2 ± 2.9 mm in group A and 5.2 ± 2.7 mm in group H (n.s.). There were four failures in group A (12.1%) and one in group H (3.3%). The differences between the groups were not statistically significant. CONCLUSION: The clinical and radiological outcomes and failure rates of the high femoral tunnels were comparable with those of the anatomical femoral tunnels at the 2-year follow-up after remnant-preserving single-bundle PCL reconstruction. The findings of this study suggest that high femoral tunnels can be considered an alternative in remnant-preserving single-bundle PCL reconstruction. LEVEL OF EVIDENCE: III.

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.

Post-Voltage-Boost Circuit-Supported Single-Ended Class-B Amplifier for Piezoelectric Transducer Applications.

Piezoelectric transducers are important devices that are triggered by amplifier circuits in mobile ultrasound systems. Therefore, amplifier performance is vital because it determines the acoustic piezoelectric transducer performances. Particularly, mobile ultrasound applications have strict battery performance and current consumption requirements; hence, amplifier devices should exhibit good efficiency because the direct current (DC) voltage in the battery are provided to the supply voltages of the amplifier, thus limiting the maximum DC drain voltages of the main transistors in the amplifier. The maximum DC drain voltages are related with maximum output power if the choke inductor in the amplifier is used. Therefore, a need to improve the amplifier performance of piezoelectric transducers exists for mobile ultrasound applications. In this study, a post-voltage-boost circuit-supported class-B amplifier used for mobile ultrasound applications was developed to increase the acoustic performance of piezoelectric transducers. The measured voltage of the post-voltage-boost circuit-supported class-B amplifier (62 VP-P) is higher than that of only a class-B amplifier (50 VP-P) at 15 MHz and 100 mVP-P input. By performing the pulse-echo measurement test, the echo signal with the post-voltage-boost circuit-supported class-B amplifier (10.39 mVP-P) was also noted to be higher than that with only a class-B amplifier (6.15 mVP-P). Therefore, this designed post-voltage-boost circuit can help improve the acoustic amplitude of piezoelectric transducers used for mobile ultrasound applications.

Wireless Ultrasound Surgical System with Enhanced Power and Amplitude Performances.

A wireless ultrasound surgical system (WUSS) with battery modules requires efficient power consumption with appropriate cutting effects during surgical operations. Effective cutting performances of the ultrasound transducer (UT) should be produced for ultrasound surgical knives for effective hemostasis performance and efficient dissection time. Therefore, we implemented a custom-made UT with piezoelectric material and re-poling process, which is applied to enhance the battery power consumption and output amplitude performances of the WUSS. After the re-poling process of the UT, the quality factor increased from 1231.1 to 2418 to minimize the unwanted heat generation. To support this UT, we also developed a custom-made generator with a transformer and developed 2nd harmonic termination circuit, control microcontroller with an advanced reduced instruction set computer machine (ARM) controller, and battery management system modules to produce effective WUSS performances. The generator with a matching circuit in the WUSS showed a peak-to-peak output voltage and current amplitude of 166 V and 1.12 A, respectively, at the resonant frequency. The performance with non-contact optical vibrators was also measured. In the experimental data, the developed WUSS reduced power consumption by 3.6% and increased the amplitude by 20% compared to those of the commercial WUSS. Therefore, the improved WUSS performances could be beneficial for hemostatic performance and dissection time during surgical operation because of the developed UT with a piezoelectric material and re-poling process.

Development of an Accurate Resonant Frequency Controlled Wire Ultrasound Surgical Instrument.

Our developed wire ultrasound surgical instrument comprises a bolt-clamped Langevin ultrasonic transducer (BLUT) fabricated by PMN-PZT single crystal material due to high mechanical quality factor and electromechanical coupling coefficient, a waveguide in the handheld instrument, and a generator instrument. To ensure high performance of wire ultrasound surgical instruments, the BLUT should vibrate at an accurate frequency because the BLUT's frequency influences hemostasis and the effects of incisions on blood vessels and tissues. Therefore, we implemented a BLUT with a waveguide in the handheld instrument using a developed assembly jig process with impedance and network analyzers that can accurately control the compression force using a digital torque wrench. A generator instrument having a main control circuit with a low error rate, that is, an output frequency error rate within ±0.5% and an output voltage error rate within ±1.6%, was developed to generate the accurate frequency of the BLUT in the handheld instrument. In addition, a matching circuit between the BLUT and generator instrument with a network analyzer was developed to transfer displacement vibration efficiently from the handheld instrument to the end of the waveguide. Using the matching circuit, the measured S-parameter value of the generator instrument using a network analyzer was -24.3 dB at the resonant frequency. Thus, our proposed scheme can improve the vibration amplitude and accuracy of frequency control of the wire ultrasound surgical instrument due to developed PMN-PZT material and assembly jig process.

Mechanical characterization of HIV-1 with a solid-state nanopore sensor.

Enveloped viruses fuse with cells to transfer their genetic materials and infect the host cell. Fusion requires deformation of both viral and cellular membranes. Since the rigidity of viral membrane is a key factor in their infectivity, studying the rigidity of viral particles is of great significance in understating viral infection. In this paper, a nanopore is used as a single molecule sensor to characterize the deformation of pseudo-type human immunodeficiency virus type 1 at sub-micron scale. Non-infective immature viruses were found to be more rigid than infective mature viruses. In addition, the effects of cholesterol and membrane proteins on the mechanical properties of mature viruses were investigated by chemically modifying the membranes. Furthermore, the deformability of single virus particles was analyzed through a recapturing technique, where the same virus was analyzed twice. The findings demonstrate the ability of nanopore resistive pulse sensing to characterize the deformation of a single virus as opposed to average ensemble measurements.

Fully Integrated Light-Sensing Stimulator Design for Subretinal Implants.

This paper presents a fully integrated photodiode-based low-power and low-mismatch stimulator for a subretinal prosthesis. It is known that a subretinal prosthesis achieves 1600-pixel stimulators on a limited single-chip area that is implanted beneath the bipolar cell layer. However, the high-density pixels cause high power dissipation during stimulation and high fabrication costs because of special process technologies such as the complementary metal-oxide semiconductor CMOS image sensor process. In addition, the many residual charges arising from the high-density pixel stimulation have deleterious effects, such as tissue damage and electrode corrosion, on the retina tissue. In this work, we adopted a switched-capacitor current mirror technique for the single-pixel stimulator (SPStim) that enables low power consumption and low mismatch in the subretinal device. The customized P+/N-well photodiode used to sense the incident light in the SPStim also reduces the fabrication cost. The 64-pixel stimulators are fabricated in a standard 0.35-µm CMOS process along with a global digital controller, which occupies a chip area of 4.3 × 3.2 mm² and are ex-vivo demonstrated using a dissected pig eyeball. According to measured results, the SPStim accomplishes a maximum biphasic pulse amplitude of 143 µA, which dissipates an average power of 167 µW in a stimulation period of 5 ms, and an average mismatch of 1.12 % between the cathodic and anodic pulses.