BIODEVICES 2024 Abstracts

Full Papers Short Papers
Full Papers
Paper Nr: 32
Title:

Breast Cancer Detection Using Smart Wearable Devices with Thermal Sensors
Authors:

Raniya Ketfi, Zeina Al Masry, Noureddine Zerhouni, Catherine Gay and Christine Devalland
Abstract: Breast cancer is the most frequent cause of cancer-related mortalities among women worldwide. Early detection of breast cancer is one of the best approaches to prevent this disease. In some developed countries, the 5-year relative survival rate of breast cancer patients is above 90% due to early prevention. Many early detection tools have been developed and used such as mammography, ultrasounds, and magnetic resonance imaging (MRI). Still, these tools are not always the best in terms of cost, effectiveness, and risk-free. Developing a more effective, risk-free, and affordable technique for breast cancer detection has always been a necessity to increase survivability. Authors have found the potential of non-radiative and non-invasive thermography for anomaly breast detection. This systematic review aims to provide an introduction and guide for smart wearable devices for breast cancer detection using thermal sensors by discussing the advantages of these devices as well as the challenges of developing and implementing them. A total of 6 relevant works drawn from 286 papers on the subject were carefully analyzed, and the information was synthesized. The selected papers were synthesized according to the design of the wearable device, its data collection, and classification methodologies. Finally, this review tackles the challenges that come with developing such devices and the great promise and advantages they hold for early breast cancer detection.
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Paper Nr: 38
Title:

Biodegradable Biodevices: A Design Approach Based on Cellular Automaton
Authors:

William Solórzano-Requejo, Carlos Aguilar, Gabriel Callejo and Andrés Díaz Lantada
Abstract: This innovative study introduces a comprehensive methodology to simulate the two-dimensional degradation of biodegradable materials, a crucial aspect in biodevice design. Several PVA specimens of diverse shapes were created, and their degradation was computationally modelled using cellular automaton. Deterministic and probabilistic transition rules were explored to identify the most accurate in the simulation of PVA degradation. The results highlight the effectiveness of the probabilistic exponential rule, derived from Markov Chains, for reliable degradation simulation. Furthermore, this approach was successfully applied to the analysis of specific medical devices, enabling a detailed in silico assessment of degradation patterns in coronary stents, tissue engineering scaffolds and craniosynostosis implants. This methodology deepens our fundamental understanding of degradation and provides valuable information for engineers and medical professionals, facilitating the creation of devices that integrate optimally with surrounding biological tissues.
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Paper Nr: 90
Title:

Bioinspired Design and Manufacturing Strategies for next Generation Medical Implants: Trends and Challenges
Authors:

Andrés Díaz Lantada, Adrián Martínez Cendrero, Francisco Franco Martínez, Rodrigo Zapata Martínez, Carlos Aguilar Vega, William Solórzano-Requejo and Alejandro De Blas De Miguel
Abstract: Bioinspired design and manufacturing strategies are enabling radical innovations in healthcare and medical devices. The complex, functionally graded, fractal, multifunctional geometries and structures of nature are inspiring for conceiving highly transformative biomedical engineering solutions, but highly challenging to replicate. Decades (if not centuries) of research, together with a convergent collection of recently developed and emergent software and hardware resources, empower our biomimetic design and manufacturing abilities and render truly bioinspired solutions feasible. Such convergence is analyzed in this study and connected with the engineering of next generation implants, characterized for their life-like features or even with quasi-living behaviors. Synergic design and manufacturing technologies with remarkable impact in implants innovation, tissue engineering, biofabrication and engineered living materials are presented and illustrated by means of different case studies. Current research trends and challenges are discussed.
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Paper Nr: 143
Title:

DKCDF: Dual-Kernel CNN with Dual Feature Fusion for Lung Cancer Detection
Authors:

Wariyo G. Arero, Yaqin Zhao, Longwen Wu and Yi Wang
Abstract: One of the main reasons for cancer-related fatalities worldwide is lung cancer. Early diagnosis is essential for enhancing patient outcomes and lowering mortality rates. Deep learning-based approaches have recently demonstrated promising outcomes in medical image analysis applications, such as lung cancer identification. In order to improve lung cancer detection, this research suggests a unique method that combines a dual-kernel convolutional neural network (DKC) with dual-feature fusion using the Histogram of oriented gradients (HOG) and local binary patterns (LBP). Convolutional neural networks are good at extracting and detecting features. CNN features are built using low-level features from the first convolution layer, which might only partially capture some local features and lead to the loss of some crucial details like edges and contours. HOG is quite good at describing the shape of objects. LBP can record local structure and information about spatial texture. The distribution of edge directions or local gradients in intensity can provide a good definition of an object’s shape and local appearance. The lung image is loaded with bone, air, blood, water and other substances and appears noisy in the lung image. As a result, in this research, we favor the HOG and LBP feature fusion for lung cancer detection.
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Paper Nr: 166
Title:

Sustainable Printed Electrodes for Energy Harvesting from Urine to Power IoT Sensor Nodes in Smart Diapers
Authors:

Muhammad Tanweer, Raimo Sepponen, I. Oguz Tanzer and Kari Halonen
Abstract: The expansion of Internet of Things (IoT) devices is rapidly increasing across various aspects of life, notably in wearable healthcare. With billions of already deployed IoT sensor nodes, this figure is anticipated to escalate into the hundreds of billions in coming years. One of the most significant challenges is how to economically power these devices by adopting sustainable and environment-friendly solutions as the conventional power sources are inadequate to meet the demands of this vast IoT ecosystem. In recent years, innovative approaches have emerged to design energy-optimized electronic systems, opening a pathway for applications based on energy harvesting. In this study, a novel energy harvesting solution is proposed by developing sustainable and disposable harvesting electrodes, leveraging the capabilities of printed electronics technology. These electrodes are engineered to harvest energy from human urine, a readily available resource, to power the energy-efficient wearable IoT sensor nodes of smart diapers. A comprehensive characterization of these harvesting electrodes is conducted using pseudo-urine as an electrolyte within a controlled laboratory environment. The results demonstrate great promise for the development of self-powered IoT sensor nodes of smart diapers, with the capacity for overnight operations lasting up to 12 hours.
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Paper Nr: 279
Title:

Cardiorespiratory Adaptations to Work Volume on an Automobile Assembly Line
Authors:

Dania Furk, Luís Silva, Mariana Dias, Phillip Probst and Hugo Gamboa
Abstract: Automobile assembly workers have to perform repetitive tasks with varying workload volumes, according to their assigned workstation, on a daily basis. With inadequate recovery, this type of occupational activity has been shown to cause cardiovascular problems. Despite these concerns, cardiovascular and respiratory adaptations to workload variations are often overlooked. This study aims to analyze Electrocardiogram (ECG) and Respiratory Inductance Plethysmography (RIP) data to understand the evolution of cardiorespiratory adaptations to three specific work volumes. A sample of sixteen male operators (age = 38±8 years; BMI = 25 ± 3 kg.m2 ) volunteered from three workstations (H1, H2 and H3) with different work cycle durations (1, 3 and 5 minutes, respectively). The results showed that activities with distinct workloads cause different responses through the data collection in cardiovascular load, heart rate variability (HRV), and respiratory frequency, variability, and coordination. The workload volume and work phase both influenced the cardiorespiratory acute response of the operators on the automobile assembly line, something that could improve individual-specific management of tasks assigned to workers.
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Paper Nr: 280
Title:

Development of an Affordable EMC Immunity Assessment Setup Using Direct Power Injection for Biosignals Instrumentation: Application to ECG Monitoring
Authors:

Tiago Nunes, Hugo Plácido da Silva and Hugo Gamboa
Abstract: The increasing number of connected electronic devices in our daily lives contributes to a more dense electromagnetic environment, increasing the challenge of resilience to electromagnetic interference. This is particularly concerning when the context is healthcare and the devices currently used to assess one’s health condition. It is crucial that the development of new devices for biosignals acquisition takes into consideration the electromagnetic compatibility of the device from an early stage of the design. In this paper, a methodology to assess the immunity of a device based on direct power injection is proposed. We describe the setup used and the PCBs designed for the specific case of an ECG acquisition device. The validation of the setup is made with two scenarios previously evaluated in anechoic environment. We show that with the proposed setup we observe the same effects as in anechoic environment.
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Short Papers
Paper Nr: 23
Title:

A POCT to Rapid Detect GBS with Highly Sensitivity
Authors:

Yang Chen, Zhi-Rui Xie and Yao-Gen Shu
Abstract: Group B streptococcus (GBS) is a leading cause of invasive neonatal infections and a significant pathogen in immunocompromised adults. Screening of GBS colonization in pregnant women determines the need for antibiotic prophylaxis in that pregnancy. Therefore, efficient and rapid determination of the GBS colonization status of pregnant women is crucial. Here, we set up a POCT with specific spectral absorption of chromogenic culture media to replace the traditional visual identity of GBS, which greatly improved the sensitivity of GBS detection, and decreased the time to identify it.
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Paper Nr: 28
Title:

An Event-Driven Closed-Loop Ultrasound Stimulator Composed of a Micro-Transducer and Multi-Site Electrodes in Vitro
Authors:

Ryo Furukawa, Shuichi Murakami and Takashi Tateno
Abstract: Ultrasound neuromodulation, in which local and deep brain areas are stimulated, holds promise for clinical applications. However, the mechanisms of action underlying the stimulation effects are still unknown. In vitro experiments are helpful for investigating the stimulation mechanisms because they allow easy control of extracellular conditions. Compared with closed-loop systems, conventional open-loop systems do not permit monitoring of neural activity, and thus can lead to excessive neural stimulation. In this study, we developed a piezoelectric micromachined ultrasound transducer (PMUT) combined with monitoring microelectrodes. To examine the potential of our device as a neuromodulation tool, we measured the cellular responses to generated ultrasound stimulation. Subsequently, we constructed a closed-loop system that combined our PMUT with monitoring electrodes, and applied event-related ultrasound stimulation to brain slices in vitro. We discuss future applications of a closed-loop ultrasound stimulation system.
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Paper Nr: 40
Title:

Prototyping a Low-Cost Flexible Sensor Glove for Diagnostics and Rehabilitation
Authors:

Shival Indermun and Taahirah Mangera
Abstract: Individuals in developing regions who require hand therapy for rehabilitation face difficulties accessing local clinics. The objective of the current study was to create a cost-effective device capable of assessing finger range of motion (ROM) for diagnostic and potential rehabilitation purposes in these disadvantaged areas. The design employs flexible sensors and a soft glove that records the motion of key finger joints during a variety of daily activities performed by ten healthy participants. The results demonstrated the glove’s effectiveness in measuring dynamic ROM for both hands of all participants. This promising outcome suggests that the flexible sensor holds great potential as a tool for hand rehabilitation and diagnosing hand impairment, offering a valuable solution to address accessibility issues in developing countries.
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Paper Nr: 77
Title:

Incorporating an Intelligent System Based on a Quantum Algorithm into Predictive Analysis for Screening COVID-19 Patients
Authors:

Aratã Andrade Saraiva, João Paulo Oliveira da Silva, José Vigno Moura Sousa, N. M. Fonseca Ferreira, Salviano Pinto Soares and António Valente
Abstract: The work seeks to develop an expert prediction system based on artificial intelligence that can serve as a tool for healthcare professionals, as a diagnostic aid when estimating whether a patient with COVID will show rapid clinical improvement or whether they will be intubated. Such a system is important for hospital management in relation to the acquisition of materials, in addition to enabling early treatment of patients with COVID. The predictive analysis algorithm for screening COVID patients addressed was the Variational Quantum Classifier (VQC) and Deep Neural Networks (DNN). As a result, an accuracy of 90% was obtained for DNN and 96% for VQC.
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Paper Nr: 91
Title:

Additive Manufacturing of Nitinol for Smart Personalized Medical Devices: Current Capabilities and Challenges
Authors:

Andrés Díaz Lantada, Carlos Aguilar Vega, Rodrigo Zapata Martínez, Mónica Echeverry Rendón, Muzi Li, Óscar Contreras-Almengor, Jesús Ordoño, William Solórzano-Requejo, Miroslav Vasic, Juan Manuel Munoz-Guijosa and Jon Molina-Aldareguia
Abstract: Shape-morphing smart medical devices constitute a current research trend and are bound to transform healthcare thanks to the improved interactions with the human body they enable. 4D printing technologies facilitate the development of such devices and start to provide innovative solutions like minimally invasive surgical tools and devices, ergonomic appliances and orthoses, evolutive implants and active in vitro biodevices, among others. Most studies so far, dealing with 4D printed biodevices, have been focused on smart polymeric materials and structures, whose biomechanical, biochemical and biological properties cannot always match those from shape-morphing and shape-memory alloys (SMAs). Considering several recent synergic breakthroughs in the additive manufacturing of smart alloys, this study presents 4D printing with SMAs for a new generation of medical devices, illustrated through case studies by our team. The more relevant strategies under research for enhancing the performance of 4D printed NiTi are illustrated and varied foreseen directions for achieving a sustainable and equitable impact in healthcare are discussed.
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Paper Nr: 135
Title:

Can Electromyography Alone Reveal Facial Action Units? A Pilot EMG-Based Action Unit Recognition Study with Real-Time Validation
Authors:

Abhinav Veldanda, Hui Liu, Rainer Koschke, Tanja Schultz and Dennis Küster
Abstract: Facial expressions play a crucial role in non-verbal and visual communication, often observed in everyday life. The facial action coding system (FACS) is a prominent framework for categorizing facial expressions as action units (AUs), which reflect the activity of facial muscles. This paper presents a proof-of-concept study for upper face action unit recognition (AUR) using electromyography (EMG) data. The study recorded facial EMG data of a subject over four sessions, who imitated facial expressions corresponding to four different AUs. The subject-dependent models that were trained achieved high accuracy in near-real time and were able to classify AUs not directly underneath the recording sites.
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Paper Nr: 174
Title:

Concentric Ring Tattoo Electrodes for Biosignal Recordings
Authors:

Gema Prats-Boluda, Eduardo Garcia-Breijo, José L. Martinez-de-Juan, Javier Garcia-Casado, Yiyao Ye-Lin, Oleksandr Makeyev and Piero Cossedu
Abstract: Non-invasive bioelectrical recordings utilize monopolar or bipolar disc electrodes. However, these electrodes suffer from poor spatial resolution, leading to susceptibility to physiological interferences. Concentric ring electrodes have been implemented on rigid and flexible substrates to enhance spatial resolution. The present work aims to develop an ultra-flexible and ergonomic concentric ring tattoo electrode based on PEDOT: PSS ink and check its feasibility of picking up surface bioelectric signals such as the electrocardiogram. Results reveal that it is possible to capture good quality bioelectric signals with tattoo electrodes implemented through inkjet techniques on tattoo paper substrate using PEDOT: PSS as ink. The main problem associated with this option is the cost in time of the machine for manufacturing the electrodes.
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Paper Nr: 217
Title:

RehabVisual: Adapting and Testing the Visuomotor Skills Stimulation Platform on Patients with Multiple Sclerosis
Authors:

Margarida Henriques, Maria Irene Mendes, Ana Martins, Carla Quintão and Cláudia Quaresma
Abstract: Multiple Sclerosis (MS), the most prevalent immune-mediated inflammatory demyelinating disease affecting the Central Nervous System (CNS), has an estimated global incidence of 2,8 million individuals. Although its symptomatology is highly varied and unpredictable, depending on the lesions’ location in the CNS, visual impairments are among the most common manifestations. However, conventional methods for assessing and rehabilitating visuomotor competences are not sufficient to deliver objective assessments or personalized therapies. The current study addresses this gap by adapting and testing the RehabVisual platform’s usability in MS patients. RehabVisual, developed in previous studies, aims to objectively assess visuomotor skills through an integrated low-cost eye tracking system, offering specific clinical intervention. Before clinical application, a normative base was established using 50 healthy individuals for later comparison. The experimental group comprised 25 MS patients with and without confirmed visuomotor alterations. The protocol involved viewing three visual stimuli for later calculation of the mean Euclidean distance between the gaze and stimulus positions using the eye tracker, for further assessment of the patients’ performance in tracking the stimulus. The findings confirmed diagnosed visual impairments, along with their quantification and storage for monitoring and rehabilitation purposes, highlighting the platform’s potential as an auxiliary tool for healthcare professionals.
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Paper Nr: 224
Title:

Machine Learning-Based Smart-Textile for COVID-19 Monitoring
Authors:

Nkengue Marc Junior, Xianyi Zeng, Ludovic Koehl, Xuyuan Tao, François Dassonville and Nicolas Dumont
Abstract: We propose a new low-cost wearable system to guaranty patient mobility and robust monitoring of COVID-19 using physiological signals. Considering the correlation between two key signals (ECG and PPG), the proposed wearable system will integrate an Variational AutoEncoder (VAE) with self-attention block to reconstruct robust ECG, PPG Red and IR signals from a noisy ECG time series. The model performance is evaluated using the Mean Square Error (MSE), the root-mean-square error (RMSE), Mean Absolute Error (MAE) and the Signal-to-Noise Ratio (SNRoutput) for the signals. With a low MSE, RMSE and MAE, as well as good SNR, the model can generate robust and clean data from the noisy ECG waveform measured by the wearable system. we believe that the proposed wearable system can not only help to provide robust online COVID-19 symptoms monitoring but also for other applications.
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Paper Nr: 234
Title:

Dynamic Characteristic of the Pleural Cavity Pressure Sensor
Authors:

T. Mimra, M. Cerny, C. Guerin and N. Noury
Abstract: We are developing an implantable sensor to measure the interface pressure in the pleural cavity. A 3D printing process was used to evaluate different shapes and materials for the transducer part. The better compromise resulted in a disk-shaped, 10 cm diameter, printed with biocompatible TPU (Thermoplastic polyurethane) filaments with a hardness 92A, offering the best compromise in terms of static sensitivity. We now investigate the dynamic characteristics of our sensor.
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Paper Nr: 255
Title:

Numerical Modelling and Simulation of a Lab-on-a-Chip for Blood Cells’ Optical Analysis
Authors:

Ahmed Fadlelmoula, Vítor Carvalho, Susana O. Catarino and Graça Minas
Abstract: Blood is a treasure of information about the functioning of the whole body. Thus, there is a continuous need for new, accurate, fast, and precise techniques to analyse blood samples. The goal of this work is to design and numerically simulate a low-cost lab-on-a-chip device, which, in the future, can be used to quickly diagnose diseases by using a tiny drop of a blood sample from the patient. The designed microdevice includes two fluid inlets, a serpentine area for achieving a continuous and fully developed flow, as well as a detection chamber able for optical measurements. The numerical model of the designed microdevice was computed using COMSOL Multiphysics software, taking into account the flow and tracking of microparticles, mimicking blood cells. In order to reach the best lab-on-a-chip geometry, i.e., achieving a high and stable number of particles in the detection chamber during the entire microfluidic assay, the inlet velocity, the channel width, and the diameter of the detection chamber were individually optimized. A mesh study was also performed to achieve the best results’ accuracy, with lowest computational effort. From the achieved results, it was observed that a lab-on-a-chip geometry with a 0.5 mm channel width and a 2- or 3-mm detection chamber radius, with a fluid inlet velocity of 3 mm/s, was the one with the most interesting results for the intended application, with a constant number of particles flowing through the detection chamber (142 in average, for the selected inlet conditions).
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Paper Nr: 263
Title:

Behind the Lens: Exploring UV Reflection
Authors:

J. Fonseca, P. Teixeira and L. Ventura
Abstract: Current UV protection regulations mainly center on sunglass lenses’ light passage, using quantitative criteria based on sunglass categories. Yet, studies, including this one, stress the necessity to enhance and adjust these norms. Our findings underscore aligning standards, notably the Brazilian ISO NBR 12312-1, with ICNIRP guidelines. Environmental radiation dispersion where sunglasses are worn can impact eye safety despite dark lenses, potentially harming protection due to pupil dilation. This project marks a pivotal step in UV protection analysis, crafting a methodology to measure light entering the eyes as UV rays penetrate sunglass lenses. We devised an apparatus with LEDs, sensors, and a mannequin to gauge eye-reaching radiation. Preliminary results reveal 10 to 15% of this wavelength’s light penetrates the eyes, varying based on lens characteristics like material and curvature. However, these initial tests only validated the system with red LEDs, limiting their scope. Validating this research urges adapting existing norms to assess UV radiation reaching the eyes and establish effective protection methods.
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Paper Nr: 281
Title:

Overall Additive Manufacturing of Capacitive Sensors Integrated into Textiles: A Preliminary Analysis on Contact Pressure Estimation
Authors:

Tiziano Fapanni, Raphael Palucci Rosa, Edoardo Cantù, Federica Agazzi, Nicola Francesco Lopomo, Giuseppe Rosace and Emilio Sardini
Abstract: Printed electronics approaches in deploying sensors offers several advantages over traditional methods, including their capability to be integrated into flexible substrates, including textiles. Additionally, printed sensors can be manufactured at relatively low cost and overall include sustainable materials, making them a more accessible option for a wider range of applications. Utilizing additive manufacturing techniques like stereolithography and aerosol jet printing, this work focused on creating fully printed capacitive pressure sensors within textiles. The sensors were designed as planar capacitors with micro-structured dielectrics to enhance linearity and measurement range. Three devices, incorporating 3D pyramidal structures, were produced and characterized under varying loads; the dielectric part was realized by using stereolithography and directly incorporating fabric on the top/bottom sections, whereas carbon-based ink was then deposited to produce the conductive plates and connection pads. Results indicated primarily capacitive behavior up to 10 MHz, with tunable capacitance affected by surface areas and air/resin ratio; hysteresis was also observed, revealing inherent non-linear behavior. These main findings provide important insights into the feasibility of the design and the additive manufacturing process. This innovation holds promise for applications in a variety of fields, including safety and sports.
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Paper Nr: 86
Title:

Real-Time Stand-Up Evaluation Using Low-Cost Hardware
Authors:

Luis Rodriguez-Cobo, Guillermo Diaz-Sanmartin, Jose Francisco Algorri, Carlos Fernandez-Viadero, Jose-Miguel Lopez-Higuera and Adolfo Cobo
Abstract: In this study, we’ve equipped an ordinary chair with budget-friendly electronics capable of tracking the temporal distribution of weight changes. This electronic system is specifically crafted to analyze typical human motions, such as sitting down and standing up. These everyday movements greatly affect different motor skills, such as walking patterns, the likelihood of falling, and insights into sarcopenia. However, there’s no precise way to measure the quality of these actions, lacking an absolute standard. To tackle this issue, the developed analyzer incorporates variables like Smoothness and Percussion, aiming to enhance information and establish an objective metric in evaluating stand-up/sit-down actions. This approach not only introduces a more precise assessment but also provides clinicians with additional insights, making the evaluation more objective and informed.
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Paper Nr: 97
Title:

Development of a Machine Learning Based in-Home Physical Activity Monitoring System Using Wrist Actigraphy and Real-Time Location System
Authors:

Seyyed Mahdi Torabi, Mohammad Narimani and Edward J. Park
Abstract: In this study, a multi-modal sensing approach was employed to enhance human activity recognition (HAR). The approach integrated data from a wearable wristband and a Real-Time Location System (RTLS) to perform physical posture classification (PPC) and indoor localization (IL). The performance of conventional machine learning techniques such as Logistic Regression (LR) and Long Short-Term Memory (LSTM) models were compared. The results demonstrated that LSTM models superior performance in terms of accuracy and robustness. The LSTM’s efficacy stems from its ability to capture temporal dependencies inherent in human activity data, making it suited for HAR tasks. Our findings underscored the benefits of employing a multi-modal, LSTM-based approach for enhancing HAR. The proposed approach increased the comprehensiveness of the HAR system. The proposed system holds potential for various in-home activity monitoring scenarios, suggesting promising implications for improving the quality of remote patient monitoring.
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Paper Nr: 157
Title:

Experimental Flow Studies in PDMS Intracranial Aneurysms Manufactured by Two Different Techniques
Authors:

Andrews Souza, Inês Afonso, Violeta Carvalho, Diana F. Rodrigues, Senhorinha Teixeira, João Eduardo Ribeiro, José Eduardo Socha Pereira, Reinaldo Rodrigues de Souza, Rui Lima and Ana Sofia Moita
Abstract: The aim of this study was to investigate the flow within intracranial aneurysms, which are localized dilations of the cerebral arteries that pose a risk of rupture and strokes. The experimental analysis was conducted on scaled-down biomodels of a cerebral aneurysm to better understand its flow patterns. To carry out the experimental phase, the biomodels were manufactured using rapid prototyping and lost core casting techniques. The biomodels were assessed for optical transparency and dimensions, confirming their suitability for flow visualization tests. The findings revealed that within the recirculation zones of the aneurysm, the flow velocities were notably lower when compared to the entry and exit points. As the flow rate increased, the recirculation focus gradually approached the aneurysm wall. Furthermore, the geometry of the aneurysm played an important role in influencing the flow behavior. These insights are crucial, as they are linked to some extent with the risk of intracranial aneurysm rupture, which may entail severe consequences. This study enriches our understanding of the aneurysm flow dynamics and contributes to the development of the inherent preventative and treatment measures.
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