Subdiaphragmatic vagus nerve stimulation (VNS) is being explored as a device-based option for obesity, but translation is limited by the lack of standardized implantation workflows and cuff electrodes that remain stable at the cuff–nerve interface in a moist in vivo environment. Here, we aimed to establish a bench-to–in vivo feasibility platform that integrates a microfabrication-compatible perfluoroalkoxy alkane (PFA) film cuff with a reproducible rabbit surgical procedure and sham-controlled evaluation. The cuff electrode was fabricated using MEMS-based processes and characterized on the bench (impedance/charge metrics), then implanted on the subdiaphragmatic vagus nerve in diet-induced obese rabbits assigned to sham or intermittent VNS at graded current levels (total n = 8; n = 2/group). Body weight was tracked as an exploratory outcome under variable delivered exposure. During the stimulation window, weight trajectories showed heterogeneous, non-monotonic patterns across current levels, with partial rebound after stimulation cessation. Gross inspection and hematoxylin and eosin (H&E) histology indicated preserved fascicular organization with a thin peri-neural fibrotic capsule, assessed qualitatively in this pilot cohort. Overall, these results support feasibility of reproducible subdiaphragmatic implantation and cuff–nerve interface operation and motivate powered studies with exposure-matched delivery logging and expanded metabolic and longitudinal endpoints.

Recently, SHapley Additive exPlanations (SHAP) has been widely utilized in various research domains. This is particularly evident in application fields, where SHAP analysis serves as a crucial tool for identifying biomarkers and assisting in result validation. However, despite its frequent usage, SHAP is often not applied in a manner that maximizes its potential contributions. A review of recent papers employing SHAP reveals that many studies subjectively select a limited number of features as 'important' and analyze SHAP values by approximately observing plots without assessing statistical significance. Such superficial application may hinder meaningful contributions to the applied fields. To address this, we propose a library package designed to simplify the interpretation of SHAP values. By simply inputting the original data and SHAP values, our library provides: 1) the number of important features to analyze, 2) the pattern of each feature via univariate analysis, and 3) the interaction between features. All information is extracted based on its statistical significance and presented in simple, comprehensible sentences, enabling users of all levels to understand the interpretations. We hope this library fosters a comprehensive understanding of statistically valid SHAP results.

Reliable chip integration remains a major challenge in implantable devices, where continuous fluid exposure, mechanical deformation, and severe space constraints must be addressed simultaneously. Existing chip packaging approaches often create structural dead space and require complex encapsulation, which can increase vulnerability to fluid ingress and long-term reliability degradation under implantation-relevant conditions. This study presents a chip integration strategy based on structural embedding using cyclic olefin copolymer (COC). Integrated circuit chips were embedded into a thermoplastic polymer substrate through an inverse truncated pyramid (ITP) geometry, enabling direct electrical integration without additional interconnection space. The integrated structure was subjected to a broad set of evaluations under implantation-relevant conditions, including in vitro biocompatibility assessment, electrical connectivity measurement, mechanical and thermal reliability testing, long-term insulation evaluation, and functional validation. The proposed approach achieved an electrical connectivity yield of up to 87% after PEDOT:PSS reinforcement. Finite element analysis showed that the ITP geometry redistributed mechanically induced stress away from the chip in terface and facilitated spatial dissipation of chip-generated heat. Long-term soak testing confirmed stable electrical insulation for 380 days, corresponding to aprojectedoperational lifetime of approximately 14.5 years under physiological conditions. Embedded functional devices also retained stable electrical performance after integration. These results demonstrate that the proposed structural embedding strategy enables monolithic, space efficient, and mechanically robust chip integration under implantation-relevant conditions. Taken together, the findings suggest that the proposed approach may offer a promising basis for further development toward compact and reliable implantable devices with integrated electronics.

Implantable device systems play a critical role in modern medicine, serving both as therapeutic tools for various diseases and as an essential means of interpreting biological phenomena. However, implanted electrodes frequently induce immune responses or cause persistent damage to the surrounding tissues owing their mechanical properties and biocompatibility. Additionally, unlike controlled in vitro environments, the stimulation efficiency often decreases in vivo due to the irregular surface of target tissues. In this study, we optimized the shape of a substrate and the pressing conditions for the fabrication of the plateau shaped electrodes based on perfluoroalkoxy alkane (PFA) film to enhance contact efficiency and biocompatibility. By optimizing the electrode structure, we aimed to enhance the performance in irregular biological environments while mitigating immune reactions and minimizing tissue damage.Clinical relevanceThe clinical relevance of this study lies in its potential for improving the long-term performance, safety, and stimulation efficiency of implantable electrodes. Minimizing cavity formation and its associated complications -such as bacterial growth, inflammation, increased impedance, and current leakage- three-dimensional (3D) electrodes can enhance the reliability of bioelectronic devices. Additionally, the improved contact between the electrode and tissue allows for more efficient current delivery, reduced power requirements and improved stimulation precision. This advancement could lead to more effective therapeutic outcomes in patients who require neural interfaces or other implants.

This study proposes a visualization and analysis method for eye blinking pattern using high-frame-rate videos. The high-frame-rate video clips for visualization are taken using a camera without additional equipment. The partial video clips of eye blinking except for eyelid flutters and microsleeps are extracted from the entire video clip. The changes in shapes and positions of the upper eyelid during the eye blinking sequences are evaluated, and each eye blinking is visualized as a single image. The various parameters regarding eye blinking are calculated to analyze blinking patterns. The single eye blinking sequence is divided into phases to analyze and classify eye blinking patterns in more detail. In this experiment conducted on 80 volunteers, the proposed method was able to quantitatively analyze eyelid movements, and various parameters related to eye blinking were calculated. Additionally, different types of eye blinking patterns were visualized as graph images, and incomplete eye blinking and consecutive eye blinking were defined and detected. The proposed method can overcome the spatial and situational limitations of conventional bio-signal analysis methods, as it allows non-contact measurement in ordinary environments. In addition, since quantitative eye blink data obtained from high-frame-rate video contain more information than data obtained from bio-signals, it is expected that analysis methods using videos can be easily applied to a wider range of fields.

Ocular myasthenia gravis (OMG) is a challenging condition to diagnose, with Cogan's lid twitch (CLT) serving as a key clinical sign. Early and accurate diagnosis of OMG is crucial for timely intervention and improved patient outcomes. However, current diagnostic methods for CLT rely primarily on visual assessment by clinicians, which is inherently subjective and prone to interobserver variability, highlighting the need for more objective diagnostic tools. This pilot study was the first to investigate the potential of video-based eyelid tracking for simplified diagnosis of Cogan's lid twitch (CLT), a key sign of ocular myasthenia gravis (OMG). The importance of this research lies in its potential to enhance diagnostic accuracy, enable earlier treatment initiation, and improve the overall management of OMG patients. We analyzed pixel value changes and eyelid position in a video recording of CLT, employing preprocessing techniques to stabilize footage and reduce lighting artifacts. Eyelid tracking was performed using contour detection and polynomial fitting. Our results showed detectable variations in eyelid position during CLT occurrences, though with inconsistent accuracy. Challenges included distinguishing subtle CLT movements from normal blinks and addressing issues like double eyelids. While further refinement is needed, this research suggests the potential of video-based tracking as a non-invasive tool for OMG diagnosis, offering significant clinical implications.Clinical Relevance— This study suggests the potential for simplified diagnosis of Cogan's lid twitch through video-based tracking, indicating significant clinical implications.

Increasing the proximity of microelectrode arrays (MEA) to targeted neural tissues can establish efficient neural interfaces for both recording and stimulation applications. This has been achieved by constructing protruding three-dimensional (3D) structures on top of conventional planar microelectrodes via additional micromachining steps. However, this approach adds fabrication complexities and limits the 3D structures to certain shapes. We propose a one-step fabrication of MEAs with versatile microscopic 3D structures via “microelectrothermoforming (μETF)” of thermoplastics, by utilizing 3D-printed molds to locally deform planar MEAs into protruding and recessing shapes. Electromechanical optimization enabled a 3D MEA with 80 μm protrusions and/or recession for 100 μm diameter. Its simple and versatile shaping capabilities are demonstrated by diverse 3D structures on a single MEA. The benefits of 3D MEA are evaluated in retinal stimulation through numerical simulations and ex vivo experiments, confirming a threshold lowered by 1.7 times and spatial resolution enhanced by 2.2 times.

This paper presents an absolute capacitive rotary encoder using a sample-and-hold demodulator (SHD) to reduce interference between sine and cosine channels. The capacitive encoder measures the rotation angle of a shaft and is widely used in industrial fields, such as servo motors, robot joint and gimbal positioning. The encoder converts the capacitive changes of sine and cosine channel electrodes, which vary with the rotation of the sinusoidal-patterned rotor, into voltage signals through a charge amplifier. Since the charge amplifier receives signals from each channel simultaneously, interference can occur between the sine and cosine channels. To reduce the interference, this paper proposes SHD. The SHD is a simple circuit composed of an operational amplifier and switches, which effectively separates multi-channel signals by adjusting the sampling timing. The signals from the sine and cosine channels separated by the SHD are smoothed by low pass filters to become analog signals. These analog signals are converted into digital signals and processed by a field programmable gate array to calculate the rotation angle. A MATLAB simulation was conducted to demonstrate that SHD can ideally reduce channel interference by 94.9%. The proposed encoder was designed and tested. It achieved a signal-to-noise ratio of 68.7 dB, accuracy of +/- 0.022 degrees, resolution of 0.0055 degrees, and nonlinearity of 0.27%.

As artificial intelligence (AI) becomes increasingly central to modern healthcare, medical education must move beyond passive knowledge transfer and adopt a system-wide approach to convergence training. This narrative review shares a 5-year case study from Seoul National University College of Medicine (SNU Medicine), which developed a comprehensive, multi-level model for integrating AI into medical education. Instead of relying on pilot programs or piecemeal curriculum updates, SNU Medicine established a governance-driven, modular framework that includes institutional infrastructure, interdisciplinary teaching strategies, cross-campus credit integration, and alignment with national digital health policies. Based on this long-term case, we propose four key design principles—modularity, transdisciplinary alignment, infrastructure-curriculum coupling, and policy embeddedness—as a framework for creating scalable and sustainable convergence education in medical AI. While rooted in Korea’s unique policy environment, this model provides transferable insights for medical institutions worldwide, particularly those operating within public or policy-constrained environments.

In tabular data analysis, high model accuracy is often regarded as a prerequisite for discussing feature importance. This assumption stems from the expectation that the validity of feature importance correlates with model performance. In this work, we challenge this prevailing belief by demonstrating that even low-performing models can provide reliable feature importance on biomedical datasets. We conduct experiments to observe how feature importance rankings change as model performance progressively degrades. Using three synthetic datasets and four real-world biomedical datasets, we compare feature rankings from the full datasets to those obtained after reducing either the number of samples (samples removal) or the number of features (features removal), using different feature stability indices. Our results reveal that, in both synthetic and real datasets, feature rankings remain stable during performance degradation caused by features removal. In contrast, sample removal introduces greater discrepancies in feature importance rankings as performance deteriorates more severely. By analyzing the distribution of feature importance values and theoretically examining the probability that the model fails to distinguish importance between features, we show that models can still reliably identify feature importance despite performance degradation due to features removal. We conclude that the validity of feature importance can be preserved even at suboptimal model performance levels, as long as the degradation stems from insufficient features rather than insufficient samples. This has a considerable impact on biomedical research, where feature importance analysis plays a pivotal role in clinical decision support and translational bioinformatics.

Skeletal muscle is composed of multiple fascicles, which are parallel bundles of muscle fibers surrounded by connective tissues that contain blood vessels and nerves. Here, we fabricated multifascicle human skeletal muscle scaffolds that mimic the natural structure of human skeletal muscle bundles using a seven-barrel nozzle. For the core material to form the fascicle structure, human skeletal myoblasts were encapsulated in Matrigel with calcium chloride. Meanwhile, the shell that plays a role as the connective tissue, human fibroblasts and human umbilical vein endothelial cells within a mixture of porcine muscle decellularized extracellular matrix and sodium alginate at a 95:5 ratio was used. We assessed four types of extruded scaffolds monolithic-monoculture (Mo-M), monolithic-coculture (Mo-C), multifascicle-monoculture (Mu-M), and multifascicle-coculture (Mu-C) to determine the structural effect of muscle mimicking scaffold. The Mu-C scaffold outperformed other scaffolds in cell proliferation, differentiation, vascularization, mechanical properties, and functionality. In an in vivo mouse model of volumetric muscle loss, the Mu-C scaffold effectively regenerated the tibialis anterior muscle defect, demonstrating its potential for volumetric muscle transplantation. Our nozzle will be further used to produce other volumetric functional tissues, such as tendons and peripheral nerves.

Smartwatches have become popular for blood pressure estimation, offering continuous monitoring with advanced convenience. However, clinical guidelines have not fully endorsed their use due to validation concerns. Many studies have compared watch-based BP measurements with cuff-based devices, but there is no clear consensus. To overcome previous methodological limitations, we collected systolic blood pressure measurements from both watch and cuff devices simultaneously, taking two readings at the same time of measurement (six participants over four days). Simply averaging the difference between watch and cuff measurements was slightly above the clinical threshold. Average error depended on individuals and calibration. Proper calibration may achieve clinically acceptable accuracy. The data showed that cuff BP measurements also vary, affecting comparative accuracy. After adjusting the inconsistency of cuff-based devices, watch-based blood pressure errors were within the clinical threshold. Daily variation analysis indicated watches being more conservative. The watch was able to distinguish participants with higher or lower daily standard deviations. The circadian cycle detected by the watch showed some relation to the cuff, but it is too early to confirm statistically significant similarity. This study evaluated the validity of watch-based BP monitoring from various perspectives, concluding that the watch might be valid for clinical use in young consumers for preventive or pre-diagnosis purpose. We also provided methodological guidelines for validating watch devices by cuff-based devices.

Augmented reality (AR) has emerged as a powerful tool for enhancing human spatial awareness by overlaying digital information onto the physical world. This paper presents a review of the methodologies that enable AR-based spatial perception, with a focus on challenging environments such as underwater and disaster scenarios. We review state-of-the-art deep learning approaches for 3D data interpretation and completion, including voxel-based, point-based, and view-based methods. As part of this review, we implement an AR-enabled spatial awareness system, where the investigated deep learning solutions can be tested directly. In our approach, a robotic arm with an ultrasound sensor performs 2D scans underwater, from which a 3D point cloud of the scene is reconstructed. Using the reviewed deep learning networks, the point cloud is segmented in order to identify objects of interest, and point cloud completion is performed to infer missing structure. We report experimental results from synthetic data and underwater scanning trials, demonstrating that the system can recover and augment unseen spatial information for the user. We discuss the outcomes, including segmentation accuracy and completeness of reconstructions, as well as challenges such as data scarcity, noise, and real-time constraints. The paper concludes that, when combined with robust sensing and 3D deep learning techniques, AR enhances human spatial awareness in environments where direct perception is limited. The need for more adequate metrics to describe point clouds and for more labeled sonar datasets is discussed.

Retinal prostheses have been developed to restore vision in patients with photoreceptor degeneration, with neural interfaces playing a crucial role in effective stimulation. Conventional planar electrodes, commonly used in subretinal prostheses, exhibit limitations such as restricted cell-electrode contact and uncontrolled current dispersion, which reduce stimulation efficiency. To address these issues, we developed a novel plateau-structured electrode designed to enhance contact with retinal cells and improve localized stimulation. The electrodes were fabricated using a post-forming process with cyclic olefin copolymer (COC) thermoforming and lamination, ensuring structural stability and reliable encapsulation. Impedance spectroscopy confirmed the electrical performance of the electrodes, with an average impedance of approximately 100 Ω at 1 kHz, demonstrating their suitability for neural stimulation. Future studies will focus on cell adhesion experiments with NIH3T3 fibroblasts to assess biocompatibility and computational modeling using COMSOL Multiphysics® to simulate electric field distribution and optimize stimulation efficiency. The proposed plateau-structured electrode presents a promising approach to overcoming the limitations of conventional planar electrodes in subretinal prostheses. The findings contribute to the advancement of bioelectronic interfaces, with potential applications extending beyond retinal prostheses to neural stimulation devices requiring precise and stable cell-electrode interactions. Furthermore, the structural and fabrication methodologies developed in this study may be applicable to a wide range of biomedical devices where improved electrode stability and selectivity are critical.

Objective: Cuff-less blood pressure (BP) measurement devices integrated into smartwatches have gained prominence for daily monitoring, yet limited studies provide the analysis of real-world BP data collected by such devices. In this study, we evaluated the feasibility of photoplethysmographic BP measuring smartwatch by analyzing data collected in real-world. Design and method: The campaign, “Smartwatch Blood Pressure Monitoring Challenge with Korean Hypertension Society”, was held in June 1-14, 2023 and 896 participants reported 35592 BP values measured by smartwatch (Samsung Galaxy Watch 6, approved in Korean Ministry of Food and Drug Safety). Participants were instructed to measure BP daily, in the morning (5AM-8AM) and evening (6PM-9PM) for two weeks, with initial calibration and re-calibration after the first week. We evaluated 1) BP difference between before and after re-calibration, and 2) difference in morning and evening BP. We also evaluated the determining factors of the BP differences. Results: Morning and evening BP values showed significant difference, higher in the evening by 1.42±5.25 mmHg (p<0.05). However, the diurnal variation was much smaller than reported in other studies using conventional BP monitoring devices. ANOVA identified significant variables for evening-morning differences, including basal metabolic rate, skeletal muscle mass, total body water, average systolic BP (SBP), diastolic BP (DBP), and heart rate in the morning (p < 0.01 in both ITT and PP). Participants who have evening-morning difference higher than the third quartile, where evening SBP was significantly higher than morning SBP, exhibited smaller variable sizes. Turkey’s Honest Significant Difference showed that this relationship is statistically significant between Q1-Q4 and Q2-Q4 in all variables. The calibration stability was assessed by the difference in average BP before and after calibration, resulting in an SBP difference of 4.64±4.73 mmHg and DBP of 3.66±3.62 mmHg, smaller than a 2021 campaign (6.8±5.6mmHg). When the difference of average was measured between same period of time (morning versus morning and evening versus evening), SBP of 5.39±5.22 mmHg and DBP of 4.3±3.99 mmHg. Conclusions: In conclusion, watch-based devices may not detect clinical-level BP variability, but refining calibration protocols offers improvement potential.

OBJECTIVE:In this paper, the fabrication of perfluoro-alkoxy alkane (PFA) film-based planar neural electrodes was proposed. METHODS:The fabrication of PFA-based electrodes started with cleaning of PFA film. The argon plasma pretreatment was performed on the PFA film surface and attached to a dummy silicon wafer. Metal layers were deposited and patterned using the standard Micro Electro Mechanical Systems (MEMS) process. Electrode-sites and pads were opened using reactive ion etching (RIE). Lastly, the electrode patterned PFA substrate film was thermally laminated with the other bare PFA film. Electrical-physical evaluation tests were conducted along with in vitro tests, ex vivo tests and soak tests to evaluate the electrode performance and biocompatibility. RESULTS:The electrical and physical performance of PFA-based electrodes had better performances compared to other biocompatible polymer-based electrodes. Also, the biocompatibility and longevity were verified by cytotoxicity test, elution test, and accelerated life test. CONCLUSION:The PFA film-based planar neural electrode fabrication was established and evaluated. The PFA based electrodes showed excellent benefits such as long-term reliability, low water absorption rate, and flexibility using the neural electrode. SIGNIFICANCE:For implantable neural electrodes, hermetic sealing is required for in vivo durability. PFA fulfilled a low water absorption rate with relatively low Young's modulus to increase the longevity and biocompatibility of the devices.

This research was conducted to apply polyimide tape, which has the advantages of low price ans strong adhesive strength, to the neural electrode process. In addition, to maximize the low-cost characteristics, a fabrication process based on UV laser patterning rather than a photolithography process was introduced. The fabrication process started by attaching the gold sheet on the conductive double-sided tape without being torn or crushed. Then, the gold sheet and the double-sided tape were patterned together using UV laser. The patterned layer was transferred to the single-side polyimide tape. For insulation layer, electrode site opened single-sided polyimide tape was prepared. Polydimethylsiloxane was used as an adhesion layer, and alignment between electrode sites and opening sites was processed manually. The minimum line width achieved through the proposed fabrication process was approximately 100 μ m, and the sheet resistance of the conductive layer was 0.635 Ω /sq. Measured cathodal charge storage capacity was 0.72 mC/cm ^2 and impedance at 1 kHz was 4.07 k Ω /cm ^2 . Validation of fabricated electrode was confirmed by conducting 30 days accelerated soak test, flexibility test, adhesion test and ex vivo stimulation test. The novel flexible neural electrodes based on single-sided polyimide tape and UV laser patterned gold sheet was fabricated successfully. Conventional neural electrode fabrication processes based on polyimide substrate has a disadvantages such as long fabrication time, expensive costs, and probability of delamination between layers. However, the novel fabrication process which we introduced can overcome many shortcomings of existing processes, and offers great advantages such as simplicity of fabrication, inexpensiveness, flexibility and long-term reliability.

Terahertz (THz) wave imaging has potential features for medicine, such as cancer detection. Nevertheless, traditional lenses are heavy, bulky, low spatial resolution, and difficult to integrate. Recently, metasurface has emerged as a compelling approach for achieving lightweight, ultrathin, and easy integration. Although many THz metasurface lenses have been proposed for the wave-focusing applications, there are a few THz metalenses that are polarization insensitive and have a high spatial resolution for THz imaging. In this paper, an ultra-thin, planar, polarization-independent, and high numerical aperture metalens has been proposed using double split-ring resonator (DSRR) structures for high-resolution THz wave focusing. The combination method of the propagation phase (adjusting the diameter of the outer ring of the DSRR) and the geometric phase (changing the slit of the DSRR) is applied to build the unit cell library including eight DSRRs, which can cover the full phase from 0 to $2\pi $ and is independent with the polarization of the incident wave. By arranging the DSRRs into the concentric rings on a thin substrate, an ultrathin, polarization-insensitive, and high numerical aperture metalens is designed with a thickness of $0.55\lambda $ , a focal length of $660~\mu \text{m}$ ( $4\lambda$ ), radius of 4.678 mm ( $28.35~\lambda$ ), and numerical aperture of 0.99 that can work at 1.82 THz (wavelength ( $\lambda$ ) of $165~\mu \text{m}$ ). The designed metalens with a near-unity numerical aperture achieves a high spatial resolution of $89~\mu \text{m}$ ( $0.54\lambda$ ), which can produce high-quality images. It means that the proposed metalens can resolve the microscale features separated by a sub-wavelength distance ( $ < 90~\mu \text{m}$ ). Therefore, the suggested metalens can serve as an objective lens for the miniaturized microscopy, opening a new avenue for microscopic THz imaging and showing potential usage in tiny THz imaging systems for cancer detection applications.

Recent advancements in smartwatch technology have introduced photoplethysmography (PPG)-based blood pressure (BP) estimation, enabling convenient and continuous monitoring of BP. However, concerns about accuracy and validation for clinical use persist. This study uses real-world data from a Samsung Galaxy Watch campaign to assess smartwatch-based BP measurements. The approach examines calibration stability by comparing average systolic BP (SBP) before and after calibration, identifying factors affecting stability through regression analysis. User-level strategies are suggested to mitigate calibration instability and emphasize guideline adherence. Notably, calibration instability is found to decrease during night-time measurements and when averaging multiple readings in the same time frame. Guideline adherence is vital, particularly for the elderly, females, and individuals with hypertension. The research enhances measurement reliability through extensive datasets, shedding light on calibration stability.

Holographic near-eye displays are a promising technology to solve long-standing challenges in virtual and augmented reality display systems. Over the last few years, many different computer-generated holography (CGH) algorithms have been proposed that are supervised by different types of target content, such as 2.5D RGB-depth maps, 3D focal stacks, and 4D light fields. It is unclear, however, what the perceptual implications are of the choice of algorithm and target content type. In this work, we build a perceptual testbed of a full-color, high-quality holographic near-eye display. Under natural viewing conditions, we examine the effects of various CGH supervision formats and conduct user studies to assess their perceptual impacts on 3D realism. Our results indicate that CGH algorithms designed for specific viewpoints exhibit noticeable deficiencies in achieving 3D realism. In contrast, holograms incorporating parallax cues consistently outperform other formats across different viewing conditions, including the center of the eyebox. This finding is particularly interesting and suggests that the inclusion of parallax cues in CGH rendering plays a crucial role in enhancing the overall quality of the holographic experience. This work represents an initial stride towards delivering a perceptually realistic 3D experience with holographic near-eye displays.