Scientific Poster Session (Tuesday)

Breast cancer is one of the most common cancers in women. With early diagnosis, some breast cancers are highly curable. Classifying normal versus tumor breast tissues from microscopy images is an ideal case to use for deep learning and could help diagnose breast cancer with higher reproducibility. Since data preprocessing and hyperparameter tuning have impacts on breast cancer classification accuracies, training a classifier with appropriate data preprocessing and optimized hyperparameters could improve breast cancer classification accuracy. Using 12 combinations of model architectures, data preprocessing, and hyperparameter configurations, the validation accuracy was calculated using the BreAst Cancer Histology (BACH) dataset. The DenseNet201, a non-specialized model architecture, with transfer learning approach achieved 98.61% validation accuracy compared to only 64.00% for the digital pathology (DP)-specialized model architecture. The combination of image data preprocessing and hyperparameters have a profound impact on the performance of deep neural networks for image classification. To identify a well-performing neural network to classify tumor versus normal breast histology, researchers should not only focus on developing new models specifically for DP, since hyperparameter tuning for existing deep neural networks in the computer vision field could also achieve a better prediction accuracy.

Cardiac electrophysiology plays a pivotal role in diagnosing and treating heart rhythm disorders, relying on anatomic electrical mapping for insights into cardiac conduction. This study merges Visible Heart methodologies with Medtronic’s Affera endocardial and CardioInsight epicardial mapping systems to concurrently explore a reanimated swine heart model. By integrating these systems, we aimed to comprehensively characterize functional electrophysiology and assess therapeutic interventions like ablation procedures and implantable devices. The integration allowed us to observe and correlate endocardial and epicardial electrical activities during sinus rhythm, offering unique insights into cardiac conduction dynamics and device-tissue interactions. Despite the combined system complexity, this integrated approach unveils promising implications for tailored patient-specific therapies and advancements in cardiac interventions

An estimated 6.2 million Americans aged 65 or older live with Alzheimer’s Disease and Alzheimer’s Disease Related Dementias in the United States, and 55 million globally. Fall detection, prediction, and prevention patient monitoring technology for this population has not been widely adopted as the standard of care because of privacy concerns with artificial intelligent video surveillance and problematic user experience design with wearables. The current standard of care for falls is eyewitness or self-report and therefore highly susceptible to human error. Therefore, solutions need to be scalable, affordable, and clinically effective with broad technology user acceptance. Despite many prevention and intervention methods that have been tried in past decades, falls remain the number one concern in aging care. The Centers for Medicare and Medicaid Services pay an enormous cost estimated at $50B per year on falls and fall related injuries. Human activity recognition with noninvasive ambient sensors is a versatile approach to patient monitoring as human movement can be translated into activities of daily living with sophisticated algorithms. This method does not use cameras and requires no contact with the body and thus it could be accepted at a higher rate than previous technologies and could therefore be adopted as the standard of care across the continuum. Together, these multimodal algorithms offer unique insights on the correlation of human movement and physical and cognitive health.

Process Integration and Design Optimization (PIDO) tools, which can connect and automate a series of computational processes forming an executable workflow with automated data input, analysis execution, and output collection, have an abundance of potential early in the life cycle of a product, but the utilization of these tools and approaches in late-phase programs can be every bit as valuable. One could even argue that the use of these tools to quickly find root causes and optimize final solutions is even more important in the late phases of a program, as the costs at these phases are much higher. PIDO tools and approaches can automate design iterations, allowing more designs to be tested in a shorter amount of time, which can help form a better understanding of the response space, and can in turn help determine the critical parameters of the system. These critical parameters can then be used to lens design verification (DV) data by drawing engineers' focus to the critical relationships of the DV data in order to make statistical observation about these influential factors controlling the system’s response. Potentially, this could be used to find process solutions to product issues without requiring expensive late[1]phase design changes. This article shows how this very approach was used on a prototype catheter’s hemostasis assembly to troubleshoot a leakage issue prior to locking-in the production tooling design.

we propose a simulation model using Simcenter Amesim for the two patient single ventilator setup. The model captures the connections and control of the mechanical components to ensure the proper ventilating function for pressure control mode. Using multiple model simulations with different lung parameter values, we demonstrate that two patients can be safely paired together on one ventilator if their lung compliances are similar. The modeling approach demonstrated herein can be used to quantify the impact of varying different parameters on the overall system performance and to accelerate the development of mechatronic medical devices.

With the goal of commissural alignment becoming a major goal with transcatheter aortic valve replacement (TAVR) becoming more prevalent, the native positionings of the coronary ostia and aortic valve cusps should be considered in the pre-procedural planning. Coronary access and perfusion post-TAVR are paramount to a patient's long-term outcomes with such procedures. In certain cases of unsymmetrical coronary cusps, commissural alignment may still leave a particularly eccentric coronary, that lays close to the native commissure of the valve, which is then susceptible to coronary obstruction. The Visible Heart® Laboratories have access to over 600 human heart specimens that have been used to analyze the native positionings of the coronary ostia. These specimens have been micro-CT scanned to make 3D-computational models with resolutions ranging from 80-100 microns. Additionally, reanimated swine hearts have been utilized to assess the relative effects of TAVR on coronary perfusion and access in living tissues. To do so, coronary pressure wires have been placed in these swine hearts before and after TAVR to assess how the coronary position could affect coronary perfusion following TAVR. The data collected here should be an educational aid to those performing such procedures as well as those developing the technologies to do so. 

Ultrasound is a relatively low-cost, high-value imaging modality used in a variety of medical specialties.  One of the challenges of deploying ultrasound more widely, especially in low-resource settings, pertains to the availability of the specific expertise needed.  The premise of this research is that a telepresence approach may reduce this barrier and facilitate increased impact of ultrasound technology.  In this paper, we present progress toward developing a robot for remote ultrasound diagnosis, with a focus on requirements specific to pediatric cardiology.  Design objectives, constraints, and rationale are explained, and modeling and prototyping results are presented.

Every day, ten Americans die from asthma, with over 60% of these deaths being preventable with early detection. Characterized by airway inflammation, asthma attacks manifest in symptoms such as wheezing, chest tightness, and coughs, which can be life-threatening. Providing early detection of these symptoms requires constant tracking of airway inflammation biomarkers. Fractional exhaled nitric oxide (FeNO) is a reliable inflammatory biomarker, positively correlated with poor asthma control, increased asthma risk, and reduced lung function. Currently, no devices provide comprehensive asthma risk assessments, and all current FeNO measurement methods lack portability and continuous monitoring. To address this gap, we propose RetainAIR: a personalized smart retainer that offers portable, comfortable, non-invasive, and continuous monitoring; enables point-of-care risk assessments; and permits timely intervention. RetainAIR detects FeNO fluctuations through electrochemical hanges in an ionogel sensor, which are then sent to an AI model that calculates FeNO fluctuations from baseline. The model, which boasts a sensitivity and specificity of 0.75 and 0.99, respectively, sends all values to a user-friendly app where patients can access their data. By continuously tracking and analyzing respiratory NO levels, RetainAIR provides asthma patients with a personalized device, timely warnings of imminent asthma attacks, and an overall analysis of asthma status to increase quality of life, lower economic burdens, and save lives.

The subjective nature in analyzing outcomes following facial plastic surgery poses a great challenge to providing objective evaluations of patients. Currently, there is a lack of accurate quantitative tools to monitor facial appearance and function. We introduce a novel quantitative facial analysis tool dubbed numeriFACE, which utilizes the recent advances in mobile camera technology and machine learning to provide precise and reliable automated facial mapping and scoring. numeriFACE allows for both retrospective analysis of existing 2D images, as well as more advanced prospective analysis utilizing depth information. numeriFACE was used in its two study arms to harvest six key facial measurements: intercanthal distance, mouth width, pronasale to menton, alar base width, mid-face height, and lower-face height. These were then compared to standard of care caliper measurements showing a strong degree of correlation overall. numeriFACE provides a reliable and repeatable point-by-point registration of human facial features. It has potential to be used in a vast array of facial characterization most specifically analyzing mid-face symmetry. Future studies are aimed at utilizing the software in the fields of reconstructive as well as aesthetic surgery. 

Keywords: Facial Analysis, Machine Learning, Computer Vision, Facial Reconstruction, Plastic Surgery, Otolaryngology, Preoperative Planning, Postoperative monitoring

Hearing aids are medical-grade hearing healthcare devices that are built for superior sound quality and to encourage hearing aid wearers to live a more active lifestyle. With the introduction of on-ear sensor and rechargeable batteries, coupled with health and wellness features inspired an evolution in the benefit hearing aids could provide beyond aural rehabilitation.  The ability to track physical activity came with the responsibility to ensure the hearing aids can withstand the heat, sweat, and varied environments they are subjected to. While most hearing aids today are designed to withstand wear and tear associated with being in constant contact with the wearer’s skin, in or around the ear, hearing aids continue to push the limits of the lifestyles the wearers maintain.

The unique challenge with hearing aids is the use of glue is not allowed to seal the interfaces due to the increased sustainability and repairability emphasis. Further these devices have atmospheric acoustic openings to allow input sound to the mics. Since its introduction close to two decades ago, nanocoating technology has become a hearing aid industry standard that protects the device by acting as a first layer of defense from liquids, oils, and solids that may degrade the components of the hearing aids over time. The latest hearing aid design presented in this paper is engineered inside out, with multiple ingress protection barriers to ensure reliability of the product throughout its lifespan and to make it waterproof and weather proof. A novel set of tests are designed and developed specifically to replicate the harshest conditions and use cases these wearable devices will come across in the real world application and the results show how the new design elements helped achieve successfully passing those tests.

Cardiovascular diseases are the leading cause of death globally. Ventricular assist devices (VADs) have emerged as crucial tools in treating heart conditions, especially considering the limited availability of heart transplants. However, challenges like device reliability and blood damage persist.

This study introduces a numerical setup to simulate centrifugal blood pumps, focusing on one approved by the FDA. Through robust shape optimization, the aim is to mitigate operating uncertainties and enhance device performance, particularly in terms of hydrodynamics and hemocompatibility. While demonstrated on a specific pump, the approach is adaptable to more complex VAD designs. Ultimately, this method could lead to the development of safer and more effective blood pumps, reducing postoperative risks for patients.

Implementing music therapy as an approach to decrease caregiver stress may help reduce physiological signs of stress e.g. heart rate. Coordinated heart rate, or heart rate synchrony, may reflect trust building, therapeutic calming of the body, and stress reaction through participant-therapist interactions. This study investigates the feasibility of data collection and analysis as indicated by heart rate synchrony between an adult and a music therapist before, during, and after therapy sessions. Utilizing Garmin smartwatches and a secure data transfer system, vital signs data was collected and analyzed with MATLAB. Preliminary results reveal some synchrony between participant and music therapist during therapy sessions. The identified synchrony underscores the potential significance of music therapy in fostering physiological alignment between participants, laying the foundation for future research in support of caregiver health and wellbeing.  

Lymphedema is an incurable, progressive condition characterized by painful swelling that affects 140 to 200 million people worldwide [1,2]. The primary treatment for lymphedema is manual lymphatic drainage (MLD) massage combined with compression garments. MLD is performed by certified lymphedema therapists, which may limit the frequency of treatment sessions and patient independence. We have created a wearable device that uses vibration to mimic the patterns of MLD, with the long-term goal to enable at-home maintenance therapy between MLD sessions. In this study, the acceleration and frequency of our motors were tested and compared to vibratory, handheld massagers that have been combined clinically with MLD. Acceleration testing utilized an accelerometer placed in the center of an arm-mimicking tissue phantom, with a model of our current device placed on the outside. Data was collected at varying voltages and motor configurations, and frequency information was calculated in MATLAB using an FFT. Acceleration and frequency of our motors were within a close range of values collected from handheld vibration tools. This indicates that our device has similar vibration characteristics to clinical tools currently used by certified lymphedema therapists.

Keywords: Lymphedema, wearables, vibration, manual lymphatic drainage, frequency, and acceleration.

About 90% of medical devices in the US enter the market through the FDA’s 510(k) clearance pathway. However, healthcare industry professionals have raised concerns that devices approved under this pathway, primarily based on the equivalence of new devices to previously approved devices (predicate devices), may be more prone to recalls. These recalls can impose substantial patient harm and financial strain on the healthcare system. In response, this work proposes a data-driven approach for predicting 510(k) device recalls, aiming to alleviate such safety concerns. Following the design science paradigm and informed by the empirical findings from our prior research, the predictive model introduced in this work leverages the characteristics of the network formed by predicate device citation relationships (predicate network). We apply natural language processing on publicly available 510(k) documents to extract predicate device information and create the predicate network. Based on the predicate network, our model incorporates various deep learning techniques to tackle two predictive model design challenges, including learning the network structure and capturing the temporal patterns of network characteristics. Rigorous analyses based on 45,236 medical devices approved by the FDA between 2003 to 2020 show that our approach significantly outperforms standard prediction models. The improved medical device recall prediction performance and the insights into the performance variations across device categories provide actionable implications for preemptive reactions to potential recalls and improving the current 510(k) pathway requirements to reduce device safety issues.

Peripheral neuropathy (PN) results from damage to the nerves in the peripheral nervous system [1] and can cause loss of feeling or numbness in the hands and feet [2]. This leads to several challenges, including difficulty walking. Our goal was to create a device that gives sensory feedback during gait to a portion of the limb that still has sensation and ultimately reduces the chance of trips and falls. Additional constraints were placed on the system being cost-effective and easy to use. To do this, we have composed a device using a closed, human-actuated air bladder system. An underfoot input air bladder compresses during walking, which in turn, inflates an air bladder on the leg that stimulates sensory nerves. To test the device, an Instron was used to apply a load to the input  bladder, and the force generated by an output bladder was measured on a mannequin leg. Four devices were evaluated in total, with two different output bladder designs and two different fluid connection systems between the bladders. It was found that both output bladder designs were effective and the connection system consisting of polyurethane tubing was superior in translating the input force onto the leg. This design also had the fastest force release, which could prove beneficial during the naturally cyclical process of walking.  

Keywords: Peripheral Neuropathy, Pneumatic Air Bladder, Soft-Robotics, Neuroprosthetic Device 

Outcomes for children with hypoplastic left heart syndrome have improved over the years, but there remains a subgroup for which the mortality rate remains extremely high: those with an intact/restrictive atrial septum. Fetal surgical approaches for this group involve balloon septoplasty or stenting (off-label use of adult coronary stents) of the atrial septum to relieve left atrial hypertension. However, significant challenges exist with these approaches on account of atrial recoil and the lack of devices engineered for this application. We present two device concepts that demonstrate potential to address these challenges. The first is a self-expanding flanged stent that eases positioning challenges and reduces the risk of stent migration. The second is a balloon with an electrode array that uses radiofrequency electrical energy to denature the atrial septal tissue following a balloon septoplasty to reduce the degree of tissue recoil. The two device concepts were tested for first-order feasibility on an atrial septum analogue. The stent device was fabricated from a commercially available self-expanding carotid stent and the balloon device was simulated using an electrode array bonded to a dilating mandrel. Both devices successfully created a channel in the atrial septum analogue, demonstrating the feasibility of these device concepts.

Various research studies utilize formalin to preserve cardiac tissues to investigate and quantify cardiac anatomies and device-tissue interactions. However, how the fixation process alters cardiac anatomy and what fixation method minimizes these changes has not been fully investigated. Fresh human hearts were formalin fixed in an end-diastolic state using three different methods including submerging, submerging while perfusing the coronaries, and submerging while pressurizing all four chambers. Micro CT scans were performed before and after fixation, and measurements of the aorta, right and left ventricle lateral walls and septum thicknesses were performed and compared. The ventricular wall and septum thicknesses tended to increase after fixation; however, the degree of change was relatively inconsistent. Pressurizing all four chambers internally seems to minimize the ventricular wall thickening and reduction in blood volume. Though, additional studies are needed to determine if this method will consistently reduce anatomical changes and if the changes are constant or predictable over a large sample size. Regardless of the fixation method, up to 6 mm of wall thickening was seen, which may contribute to potential error in anatomical measurements in fixed hearts. Therefore, one should consider fixation methods and how it changes the anatomy when performing pre-clinical studies on formalin fixed specimens.

The objective of this study is to investigate the rolling dynamics of leukocytes in microchannel flows using a hybrid continuum-particle approach. Leukocytes play an essential role in the immune system, and their margination behavior has been extensively studied both experimentally and numerically. In this study, we have developed a series of numerical experiments using a hybrid DPD-CFD solver with the membrane stiffness of the modeled leukocytes as the primary investigation subject. Our results show that increasing the stiffness of the cell's membrane influences its deformability and trajectory in microchannel flows. The results obtained from this study could be valuable in designing next-generation micro-carriers for targeted drug delivery systems, which mimic the margination behavior of leukocytes.

Keywords: Continuum-Particle Method, White Blood Cells, Cell-Fluid Interaction, Margination.

Peripheral Arterial Disease (PAD) is a chronic and progressive disease that affects blood circulation. Poor glycemic control, especially in people with diabetes, might accelerate this illness. Photo-plethysmography (PPG) signals assess vascular health non-invasively. Acceleration Photo-plethysmograph (APG) ratios correlate with aging and vascular health. Very few studies have reported the relationship of APG ratios against age and diabetes. Various APG ratios were measured for 60 subjects (30 healthy and 30 with diabetes). Among healthy subjects, the levels of the APG ratios notably varied with age (p-value is 0.001 for b/a and p-value is 0.008 for b-c-d-e/a). The b/a ratio varied linearly with age (y = 0.001x - 1.1, R2 = 0.36), as did the b-c-d-e ratio (y = 0.008x - 1.2, R2 = 0.13). The b/a and b-c-d-e/a ratios significantly correlated with ABI (p-value 0.001). Subjects with normal ABI exhibited a negative b/a ratio. The b/a ratio increased with the severity of PAD (as per ABI) in both groups. A linear regression model of the b/a ratio effectively differentiates subjects with abnormal ABI from those with normal ABI. The b/a and (b-c-d-e)/a ratios can be used for easy and faster monitoring of peripheral arterial disease in people with diabetes.

The ballistocardiogram (BCG) is a relevant unobtrusive alternative to traditional vital monitoring signals. Through the measurement of the heart’s ballistic force, representative signals can be collected that contain cardiac related health features. However, the BCG’s morphology can vary based on the measurement system and subject. This paper seeks to quantify the system-level distortion applied to measured BCG signals in a bed-based acquisition system. The characteristic “ring” of commonly acquired signals are modeled and correction techniques including ideal lowpass filtering, band stop filtering, linear predictive coding, and frequency domain deconvolution are utilized to attempt to remove this distortion. The time-domain and frequency-domain characteristics of the resulting signals are analyzed. These results document a reduction in “ring” of characteristically distorted signals and promote further research into the source of this distortion. Such results are relevant to the enhancement of understanding regarding the characteristics of bed-based BCG acquisition as well as future applications in non-contact vitals monitoring systems.

Myoelectric prostheses could enable amputees to better perform daily activities. This paper documents a preliminary investigation to identify muscle fatigue using electromyography (EMG), which could improve myoelectric prosthetic devices. A low-cost wearable myoelectric armband utilizing brass dry-type electrodes was developed. It was tested against a PowerLab medical-grade EMG machine in terms of providing signals from which muscle fatigue can be successfully interpreted. The extracted features representing muscle fatigue were: the integral of time-series EMG (IEMG), root mean square (RMS), mean frequency (MNF) and median frequency (MDF). For both the low-cost armband and the PowerLab machine, IEMG and RMS increased with increasing muscle fatigue, while MNF and MDF decreased—which were expected results. The armband and PowerLab devices showed similar performances when compared using RMS and IEMG features (average error of 35% and correlation of 0.71), but not using MNF and MDF features (average error of 112% and correlation of 0.13). This suggests that the low-cost EMG armband may be able to acquire EMG of sufficient quality to enable muscle fatigue interpretation. However, further testing and development is necessary.

Background: Sleep apnea, encompassing obstructive, central, and complex forms, significantly impacts global health, affecting a broad segment of the population. This condition can lead to serious cardiovascular and neurological damage due to recurrent hypoxia. Despite its prevalence, many individuals remain undiagnosed, partly due to the absence of accessible and accurate screening tools.

Objective: To record and quantify sleep events using an accelerometer that will be placed on the sternal notch.

Method: A Python algorithm was developed to collect data from an open-source biosensor which was displaced 6 consecutive times across 20 trials along the y-axis to mimic movement along the anteroposterior axis. This algorithm then processed the data and displayed the results in a user interface, allowing for simple determination of OSA events with timestamps for reference along with plotting.

Results: The system demonstrated 100% accuracy, consistently identifying all six disruptions per trial with no false detections despite the variability in displacements.

Conclusion: This study validates the potential of an advanced monitoring system in diagnosing and understanding sleep apnea, proposing a promising avenue for improving patient care through precise detection and analysis.

Cardiovascular diseases are the leading cause of death worldwide. An estimated 1.28 billion adults aged 30–79 years worldwide have hypertension. Out of these, 46% of adults with hypertension are unaware that they have the condition. Less than half of adults (42%) with hypertension are diagnosed and treated. Hypertension is a major cause of premature death worldwide. High blood pressure (hypertension) and diabetes are both aspects of metabolic syndrome and often occur together. Possible reasons for this may be that they have similar risk factors or that high blood sugar levels damage cells in the cardiovascular system.

Anterior Cervical Discectomy and Fusion (ACDF) surgeries are one of the most common spine surgeries performed on patients who are experiencing pain, numbness, and weakness caused by herniated intervertebral discs compressing their spinal cord. ACDF surgeries can be single level, removing one intervertebral disc and fusing the vertebrae, or multilevel, removing two to five intervertebral discs. To reach the cervical spine anteriorly, surgeons must move the surrounding anatomy using a retractor system. This provides a visualization window and protection of the surrounding anatomy. Many of the current retractor systems on the market are designed for single level surgeries, which means the retractor designs limit surgeon movement and leave patients receiving multilevel surgeries at risk for surgical device accidents or related incidents. To resolve this need, we have designed a modular retractor system with a sleek, rectangular design that will accommodate multiple blades of varying widths to protect the surrounding anatomy and significantly reduce the space consumed. An ImageJ analysis showed that the newly designed modular retractor is over 50% smaller in area compared to retractors currently in use.

Valgus angles during knee movements are a measure of interest both for rehabilitation and injury prevention applications. However, textile-based sensing technologies are generally less accurate than traditional methods for measuring joint angles. Sensor misalignment and drift due to garment shifting during movements is a key source of error, and is caused by poor coupling between the garment and the body surface.

This study (n=3 participants) tested medial knee sensor responses during optical motion capture with garment prototype variants with and without circumferential anchors. Major findings included mixed effects from anchoring, affected by participant and type of squat. Crosstalk between flexion and valgus movements is discussed as a primary contributor to the variability in sensor response. The ability to effectively sense and disambiguate these out-of-plane rotational effects remains a primary challenge for sensing complex movements with garment-integrated textile sensors.

Doppler ultrasound is applied towards the detection and diagnosis of blood vessel disorders and disease. Through the comparison of three Doppler systems, a difference in the sensitivity between readily available Doppler systems was noted and used to determine if a new standard should be implemented to guarantee that each commercially available Doppler system reaches a minimum degree of sensitivity. The three Doppler systems tested all include a Doppler device and pencil probe. The angle of the probe relative to the blood vessel, flow of blood through the vessel, gel used as an ultrasound coupling medium, and simulated blood (22% hematocrit) were all held constant throughout the experiment. The distance from directly on top of the blood vessel to the closest point at which the Doppler system detected a signal-to-noise ratio of 2:1 was recorded for a total of 10 trials. Normal distributions of the distances found in the 10 trials for each Doppler system were created and a one-way ANOVA test was conducted from these distributions. The ANOVA test resulted in a p-value of 1.176E-10, proving a significant difference in the sensitivity between Doppler systems. The clinical use of Doppler systems that lack sensitivity may result in misdiagnosis or false negatives. Therefore, a significant difference in the sensitivity between systems suggests that a standard should be implemented to ensure that all Doppler systems operate with a minimum degree of sensitivity.

This study designs a biomechanically optimized wearable airbag system to prevent fall-induced injuries among the elderly. The system uses sensors to detect falls, deploying airbags with helium to cushion the body, specifically protecting the pelvis, femur, and spine. Simulations replicate fall conditions to evaluate the impact and injury reduction capabilities of the airbag, measuring forces and injury severity through established criteria like HIC and CTI. The results show that the airbag significantly decreases the risk of fractures and serious injuries during falls. The simulations are supplemented with real-world tests to validate the protective benefits of the airbag system. Both sets of data agree, confirming the airbag's potential to enhance elderly safety. These findings suggest that the proposed system could serve as an effective tool in reducing fall-related injuries, providing a new direction in fall prevention strategies for the aging society. This research contributes to the growing field of eldercare technology and opens avenues for further innovations in personal safety devices for the elderly.

This study designs a biomechanically optimized wearable airbag system to prevent fall-induced injuries among the elderly. The system uses sensors to detect falls, deploying airbags with helium to cushion the body, specifically protecting the pelvis, femur, and spine. Simulations replicate fall conditions to evaluate the impact and injury reduction capabilities of the airbag, measuring forces and injury severity through established criteria like HIC and CTI. The results show that the airbag significantly decreases the risk of fractures and serious injuries during falls. The simulations are supplemented with real-world tests to validate the protective benefits of the airbag system. Both sets of data agree, confirming the airbag's potential to enhance elderly safety. These findings suggest that the proposed system could serve as an effective tool in reducing fall-related injuries, providing a new direction in fall prevention strategies for the aging society. This research contributes to the growing field of eldercare technology and opens avenues for further innovations in personal safety devices for the elderly.

Deep vein thrombosis (DVT) is a potentially life-threatening condition where a blood clot forms in deep veins, typically in the calf muscle region of our lower extremities. It may cause leg pain or swelling, and it might break down, resulting in pulmonary embolism (PE). When DVT and PE occur concurrently, it is commonly referred to as venous thromboembolism (VTE). This research develops an innovative methodology for DVT segmentation in medical imaging. Using a novel approach, we provide an updated U-Net architecture that includes residual and inception blocks to improve the model's capacity to precisely identify DVT areas. In addition, we investigate the use of Convolutional Neural Networks (CNN), for semantic segmentation in order to obtain an in-depth segmentation of DVT. In comparison to conventional approaches, our results illustrate that the proposed architecture is effective in recognizing DVT edges with better accuracy and resilience. Our model is trained using binary cross-entropy loss and the Adam optimizer and evaluated using performance metrics like accuracy, loss, and sensitivity. Our research enhances the area of medical image processing by presenting a potential path for automated and robust techniques in DVT segmentation.

Keywords: Deep Vein Thrombosis, Computer Tomography, Calf muscle, Pulmonary Embolism, Deep Learning, Machine Learning, Imaging Techniques, Segmentation, Feature extraction.

Bio-Implants are essential to restore normal functionality to the damaged or failing body parts of the patients. A wide range of strategies and methods for wireless powering are being explored. The key components for the proper and reliable powering of implants are biocompatible antennas, that are resonated at any of the different frequency bands such as the wireless medical telemetry service frequency band (WMTS, 1.395–1.4 GHz), the medical implantable communication service frequency band (MICS, 402–405 MHz) and the industrial, scientific, and medical frequency bands (ISM, 433–434 MHz, 902–908 MHz, 2.4–2.48 GHz). This paper suggests the design of a WMTS (1.39 – 1.42 GHz) band implantable antenna for bio-telemetric applications such as efficient powering of the implantable device. Moreover, in this design, the size of the proposed antenna is reduced to (19x14) mm 2 . In order to improve the conductivity of the patch, a shorting pin is utilized. The 1.4 GHz working frequency, small size, and low specific absorption rate (SAR) of the proposed antenna ensure the suitability for wireless powering of implants and other biotelemetric applications.

Keywords: Bio-implants, Bio-Telemetry, Implantable Antenna, Wireless power transfer, Specific Absorption Rate.