Biomedical Engineering and Bioengineering Commons^™

In Vitro Microfluidics System For Mechanobiologic Investigations, Michael A. Daanen

Honors Theses

Mechanobiology is an emerging field that aims to study the relationships between mechanical forces and cellular behavior. Such mechanobiological relationships are especially critical in the cardiovascular system, where endothelial cells lining the vasculature align in response to fluid shear stresses from blood flow (Sinha, 2016). Implanted flow devices, diabetes, chronic hypertension, and various other diseases and pathophysiologies alter vessel geometries and flow dynamics. Such alterations impact fluid shear stress and endothelial cell behavior, leading to microcirculatory dysfunction, vessel leakage, and organ failure (Poredos, 2021; Papadaki, 1999; Leitschuh, 1987). To simulate dysfunctional endothelial cell behavior in vitro and evaluate novel therapeutic …

Synthesis And Characterization Of Free Radical Scavenging Dendrimer Nanogels Via Cross-Linking Reaction-Enabled Flash Nanoprecipitation, Lin Qi, Da Huang, Huari Kou, Anna Chernatynskaya, Nuran Ercal, Hu Yang

Chemistry Faculty Research & Creative Works

This work reports the development and evaluation of dendrimer-based nanogels based on Poly amidoamine (PAMAM) dendrimer generation 5, engineered to act as a carrier with reactive oxygen species (ROS)-scavenging capabilities. We developed a cross-linking reaction-enabled flash nanoprecipitation method in which the cross-linking reaction occurs during the flash nanoprecipitation process to form a cross-linked nanostructure. Using this approach, an N-hydroxy succinimide (NHS)-functionalized ROS-responsive thioketal cross-linker (TK-NHS) was synthesized and utilized to cross-link DAB-core PAMAM dendrimer G5, resulting in the formation of G5-TK nanogels. The resulting nanogels were characterized using dynamic light scattering and transmission electron microscopy, and their cytocompatibility, irritancy, cellular …

Explorations Of Dna-Single-Walled Carbon Nanotube Interactions To Develop Multiplexed Molecularly Specific Biosensors For Inflammation, Amelia K. Ryan

Dissertations and Theses

Inflammatory cytokines such as interleukin-6 (IL-6) and interleukin-12 (IL-12) are central regulators of immune signaling and key biomarkers of disease, yet existing assays for their detection remain slow, invasive, and lack multiplexing ability. This dissertation advances the development of single-walled carbon nanotube (SWCNT) optical nanosensors capable of real-time, multiplexed, and molecularly specific cytokine detection through innovative use of single-stranded DNA (ssDNA) interfaces.

First, an IL-6-specific DNA aptamer was employed as both a dispersing agent and recognition probe for SWCNT fluorescence sensing. Sequence modifications, including anchor domains, truncations, and thermally induced refolding, were systematically tested to optimize sensitivity and selectivity. The …

Advances In Bacterial Cellulose-Based Scaffolds For Tissue Engineering: Review, Rewati Raman Ujjwal, Gymama Slaughter

Center for Bioelectronics Publications

Bacterial cellulose (BC) has emerged as a highly versatile and promising biomaterial in tissue engineering, with potential applications across skin, bone, cartilage, and vascular regeneration. Its exceptional properties like high mechanical strength, superior biocompatibility, excellent moisture retention, and inherent ability to support cell adhesion and proliferation, make BC particularly effective for wound healing and skin regeneration. These attributes accelerate tissue repair and foster new tissue formation, highlighting its value in skin-related applications. Additionally, BC's capacity to support osteogenic differentiation, combined with its mechanical robustness, positions it as a strong candidate for bone tissue engineering, facilitating regeneration and repair. Recent advancements …

Automation To Autonomy: Temporal Dynamics Of Trust And Visual Attention Allocation Did Not Evolve, Tetsuya Sato, Eric Chancey, Yusuke Yamani

Psychology Faculty Publications

Emerging work environments are expected to implement autonomy that performs various functions without human input. Previous works has shown that trust in automation is negatively correlated with visual attention allocation, indicating that trust is a dynamic construct. Moreover, trust in automation and trust in autonomy appears to evolve in similar ways. However, recent work has demonstrated differences between trust in automation and trust in autonomy within Kaber’s (2018) theoretical framework (Sato et al., 2023b). Yet, it is uncertain whether the development of trust and visual attention allocation differs between automation and autonomy. The present study examined the temporal dynamics of …

Synthesis And Assessment Of Biobased Acrylated Epoxidized Soybean Oil Resins For Stereolithography 3d Printing Of Microfluidic Devices, Natalie S. Romero Figueroa

College of Graduate Studies: Theses & Dissertations

This research focuses on the development and characterization of a biobased photocurable resin synthesized from soybean oil for use in stereolithography (SLA) 3D printing of microfluidic devices. The study explores a sustainable alternative to petroleum-based resins by performing an acrylation reaction on epoxidized soybean oil (ESO) to produce acrylated epoxidized soybean oil (AESO), which was then formulated into a photocurable resin with the addition of a photo initiator. The fabrication process involved designing microfluidic molds in SolidWorks and printing them using an Elegoo Mars 4 SLA printer under various exposure and layer thickness parameters. The printed samples consisted of microchannels …

Coldstartcpi: Induced-Fit Theory-Guided Dti Predictive Model With Improved Generalization Performance, Qichang Zhao, Haochen Zhao, Linyuan Gao, Kai Zheng, Yajie Li, Qiao Ling, Jing Tang, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Predicting compound-protein interactions (CPIs) plays a crucial role in drug discovery. Traditional methods, based on the key-lock theory and rigid docking, often fail with novel compounds and proteins due to their inability to account for molecular flexibility and the high sparsity of CPI data. Here, we introduce ColdstartCPI, a framework inspired by induced-fit theory, which leverages unsupervised pre-training features and a Transformer module to learn both compound and protein characteristics. ColdstartCPI treats proteins and compounds as flexible molecules during inference, aligning with biological insights. It outperforms state-of-the-art sequence-based models, particularly for unseen compounds and proteins, and shows strong generalization capability …

Insights In Adaptation: Examining Self-Reflection Strategies Of Job Seekers With Visual Impairments In India, Akshay Kolgar Nayak, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Significant changes in the digital employment landscape, driven by rapid technological advancements and the COVID-19 pandemic, have introduced new opportunities for blind and visually impaired (BVI) individuals in developing countries like India. However, a significant portion of the BVI population in India remains unemployed despite extensive accessibility advancements and job search interventions. Therefore, we conducted semi-structured interviews with 20 BVI persons who were either pursuing or recently sought employment in the digital industry. Our findings reveal that despite gaining digital literacy and extensive training, BVI individuals struggle to meet industry requirements for fulfilling job openings. While they engage in self-reflection …

Benchmarking Batch-Effect Correction Methods Towards The Construction Of A Triple-Negative Breast Cancer Cell Atlas, Peter Scheible, Amy H. Tang, Jing He, Jiangwen Sun

Computer Science Faculty Publications

Triple-negative breast cancer (TNBC) requires detailed cellular mapping given its aggressive nature, immense tumor heterogeneity and genetic diversity. We integrated 156,794 cells from six scRNA-seq datasets—including tumors, metastases, and cell lines—to build a TNBC scRNA cell atlas, focusing on batch effect mitigation while maintaining biological and molecular details. Preprocessing f ilters noise, normalizes data, and leverages PCA for integration readiness. We utilized scANVI, a semi-supervised tool, to align datasets, preserving TNBC’s complex tumor heterogeneity via marker annotations [1]. UMAPs demonstrate biological clustering in integrated data, contrasted with datasetdriven unintegrated patterns. Assessments verifying effective batch correction. This method aligns with NASA’s …

Adaptive Fusion Neural Networks For Sparse-Angle X-Ray 3d Reconstruction, Shaoyong Hong, Bo Yang, Yan Chen, Hao Quan, Shan Liu, Minyi Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

3D medical image reconstruction has significantly enhanced diagnostic accuracy, yet the reliance on densely sampled projection data remains a major limitation in clinical practice. Sparse-angle X-ray imaging, though safer and faster, poses challenges for accurate volumetric reconstruction due to limited spatial information. This study proposes a 3D reconstruction neural network based on adaptive weight fusion (AdapFusionNet) to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images. To address the issue of spatial inconsistency in multi-angle image reconstruction, an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion, thereby improving …

Scalable Fabrication Of High-Payload Dendrimer-Based Nanoparticles For Targeted Atherosclerosis Therapy, Huari Kou, Lin Qi, Da Huang, Jiandong Wu, Honglan Shi, Hu Yang

Chemistry Faculty Research & Creative Works

Nanoparticle-based therapeutics hold promise for the treatment of atherosclerosis, but challenges such as low drug-loading capacity and a lack of scalable, controllable production hinder their clinical translation. Flash nanoprecipitation, a continuous synthesis method, offers a potential solution for scalable and reproducible nanoparticle production. In this study, we employed a custom-designed multi-inlet vortex mixer to perform cross-linking reaction-enabled flash nanoprecipitation, facilitating controlled and scalable synthesis of cross-linked Poly amidoamine (PAMAM) dendrimer nanoparticles. Notably, this approach allows simultaneous nanoparticle cross-linking and drug loading in a single step. The mannose moiety enabled specific targeting of macrophages via mannose receptors, enhancing the localization of …

Synthesis Of Bio-Orthogonal Hydrogels For 3d Cell Culture Via Penicillamine Β-Thiolactone-Mediated Native Chemical Ligation, Kaelin E. Marshall, Matthew E. Currier, Nathan J. Oldenhuis

Honors Theses and Capstones

Many hydrogel systems designed to mimic the extracellular matrix (ECM) employ thiol-based chemistries with undesirable functional groups, including vinyl sulfones and methacrylates. In downstream applications, any unreacted functional groups are problematic and render hydrogels non-viable for human use. Here, we introduce modifications to the Native Chemical Ligation (NCL) mechanism, exploring the elimination of cytotoxic byproducts and increased reaction rate by using a β-thiolactone. The inclusion of the β-thiolactone results in retention of the thiol within the gel, as well as enhanced kinetics due to the thermodynamic favorability of the ring opening and amide formation. We achieved this by functionalizing 4-arm …

Determination Of Electrochemical Parameters For Predicting Reaction Mechanism And Algorithmic Approaches To Pain Assessment, Huize Xue

Dissertations

This dissertation introduces novel advancements in electrochemical kinetics and pain assessment, structured into two main parts. The first part focuses on the comprehensive analysis of the kinetic and mechanistic aspects of electrochemical reactions, utilizing a combination of experimental techniques and simulation methods. A new software tool, Envismetrics, was developed using Python to facilitate the analysis of complex electrochemical data, including cyclic voltammetry (CV), chronoamperometry (CA), and hydrodynamic voltammetry (HDV). The software was rigorously tested and validated with well-characterized redox systems such as the ferricyanide/ferrocyanide couple, dimethylamine borane (DMAB), and Per- and Polyfluoroalkyl Substances (PFAS). It was successfully used to determine …

Automated Segmentation Of The Ulnar Nerve In Mri Using Deep Learning Techniques, Akhil Nagulapalli

Theses

Cubital Tunnel Syndrome (CuTS), a condition caused by compression of the ulnar nerve, results in numbness, tingling, pain, and even muscle atrophy, affecting fine motor skills and diminishing patient quality of life. Accurate diagnosis of CuTS is challenging, as current diagnostic methods—including clinical exams, nerve conduction studies, and unaided MRI—often lack the precision to reliably identify the nerve and detect compression in its early stages. Deep learning-based segmentation offers a promising solution, enabling precise and automated identification of nerve structures in MRI images, which could significantly improve diagnostic accuracy and support timely intervention.

A novel deep learning model for segmenting …

Developing A Nearly Automated Open-Source Pipeline For Conducting Computational Fluid Dynamics Simulations In Anterior Brain Vasculature: A Feasibility Study, Mostafa Rezaeitaleshmahalleh, Nan Mu, Zonghan Lyu, Joseph Gemmete, Aditya Pandey, Jingfeng Jiang

Michigan Tech Publications

Intracranial aneurysms (IA) pose significant health risks and are often challenging to manage. Computational fluid dynamics (CFD) simulation has emerged as a powerful tool for understanding lesion-specific hemodynamics in and around IAs, aiding in the clinical management of patients with an IA. However, the current workflow of CFD simulations is time-consuming, complex, and labor-intensive and, thus, does not fit the clinical environment. To address these challenges, we have developed a semi-automated pipeline integrating multiple open-source software packages to streamline the CFD simulation process. Specifically, the study utilized medical angiography data from 18 patients. An in-house open-source DL image segmentation model …

Surgical Suturing Skill Assessment Using Estimated Hand Roll Angle From A Deep-Learning Computer Vision Algorithm, Jianxin Gao, Amir Mehdi Shayan, Simar P. Singh, Joe Bible, Ravikiran Singapogu, Richard E. Groff

Publications

This paper proposes a deep-learning computer vision algorithm to estimate hand roll angles for metric-based assessment of surgical suturing skills. The number of rolls metric, previously calculated directly from IMU data, counts the number of hand roll reversals during a single suture. To calculate this metric using computer vision, we apply a deep-learning algorithm that can reliably estimate hand roll angles after training on suturing videos collected on the SutureCoach simulator. Results show that the estimation accuracy of the deep-learning algorithm is robust to different video backgrounds. The number of rolls metrics were used to analyze suturing performance in the …

Assessing Reproducibility Challenges In Clinical Metabolics, Darcy Lin Cochran

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Current metabolomics research is expanding to be multiplatform and interdisciplinary. Metabolomic analysis has the potential to provide detailed insight into any biological system of interest to analyze the underlying molecular mechanisms of variables like environment, disease, and genetics. Human clinical metabolomics is a major research area that is often focused on finding biomarkers or panels of biomarkers for different diseases. However, results are difficult to compare across different laboratories since the field of metabolomics has yet to widely adopt best practices for sample preparation, data acquisition and data processing, results are difficult to compare across different laboratories.

This thesis focuses …

Physicochemical Property Effects On Immune Modulating Polymeric Nanoparticles: Potential Applications In Spinal Cord Injury, Daniel J. Kolpek, Jaechang Kim, Hisham Mohammed, John C. Gensel, Jonghyuck Park

Markey Cancer Center Faculty Publications

Nanoparticles (NPs) offer promising potential as therapeutic agents for inflammation-related diseases, owing to their capabilities in drug delivery and immune modulation. In preclinical studies focusing on spinal cord injury (SCI), polymeric NPs have demonstrated the ability to reprogram innate immune cells. This reprogramming results in redirecting immune cells away from the injury site, downregulating pro-inflammatory signaling, and promoting a regenerative environment post-injury. However, to fully understand the mechanisms driving these effects and maximize therapeutic efficacy, it is crucial to assess NP interactions with innate immune cells. This review examines how the physicochemical properties of polymeric NPs influence their modulation of …

Mechanically Cost-Effective Approach For Bipedal Walking In Robots Using Instantaneous Collision Angle, Smit R. Patel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Humans, as bipedal locomotors, are effective at reducing the mechanical cost of transport (CoTmech) by adopting movement strategies and gaits that minimize energy expenditure for a given distance. By using different gaits at different speeds, leveraging their long spring-like tendons and muscle elasticity which store and release energy during movement, humans reduce the mechanical effort required for locomotion. Current locomotion solutions offered in bipedal robots, based on legacy walking and running gait models, are not great at energy efficiency unless walking at very low speeds. Additionally, the control system of robots, designed to ensure stability and adaptability, requires substantial resources, …

Advancing Biofabrication Methodologies To Develop Biomimetic Tissue Scaffolds For Musculoskeletal Applications, Nashaita Yezdi Patrawalla

Theses and Dissertations

Musculoskeletal injuries impose a significant global burden, affecting millions and generating an economic toll exceeding $14 billion. Tissue engineering has gained traction as a promising strategy offering potential for functional restoration of damaged musculoskeletal tissues. This research aims to advance biofabrication techniques for generation of biomimetic tissue scaffolds, by optimizing scaffold design and modulating fabrication process parameters to generate scaffolds for musculoskeletal regeneration with application-specific tailored properties. In this realm, collagen-based biomaterials have been extensively investigated for tendon and ligamentous applications, and in combination with bioceramics incorporated into the collagen framework to produce composite scaffolds that better recapitulate the native …

The Impact Of Cumulative And Acute Loading On Achilles Tendon Health, Performance, And Reported Pain In Collegiate Gymnasts, Julio Serrano Samayoa

Electronic Theses and Dissertations

Gymnasts are at a high risk of Achilles tendon (AT) injuries due to intense loads during takeoffs and landings. To better understand better the relationship between impact loading and its effects on tendon adaptation and athletic performance, this study uses Inertial Measurement Units (IMUs) to track AT loading across a collegiate gymnastics season. This data were compared against physiological and athletic performance metrics, obtained through force plates and ultrasound imaging, to explore how mechanical load influences reported pain and athletic performance. Results varied, with cumulative impacts being correlated with improved jump height (Spearman 0.362, Pearson 0.348), while peak power and …

Detection Of Methane Leaks By The Use Of Mid-Range Infrared Camera, Jared Rosario, Oscar Salcido

Undergraduate Research Symposium Posters

Timely detection of methane leaks from natural gas infrastructure, like pipelines and valves, is essential for mitigating environmental and safety risks. This research focuses on using mid-wave infrared (MwIR) cameras on unmanned aerial systems (UAS) to detect leaks. By leveraging machine learning, the study aims to develop an efficient, real-time methane inspection system that operates directly on embedded processors on UAS platforms.

This project employs the FLIR G300a OGI camera for remote gas inspection, utilizing video preprocessing and optical flow to mask gas plumes in footage. The YOLOv8 deep learning model is used to detect gas pixels and segment the …

Ptsd Increases Risk For Hypertension Development Through Pvn Activation And Vascular Dysfunction In Sprague Dawley Rats, Xinqian Chen, Xin Yan, Chunxiu Yu, Qing-Hui Chen, Lanrong Bi, Zhiying Shan

Michigan Tech Publications

This study investigates the impact of single prolonged stress (SPS), a model of post-traumatic stress disorder (PTSD), on cardiovascular responses, hypothalamic paraventricular nucleus (PVN) activity, and vascular function to elucidate the mechanisms linking traumatic stress to hypertension. Although SPS did not directly cause chronic hypertension in male Sprague Dawley (SD) rats, it induced acute but transient increases in blood pressure and heart rate and significantly altered the expression of hypertension-associated genes, such as vasopressin, angiotensin II type 1 receptor (AT1R), and FOSL1 in the PVN. Notably, mitochondrial reactive oxygen species (mtROS) were predominantly elevated in the pre-autonomic regions of the …

Noncontact Diffuse Reflectance Spectroscopy Of Synovial Fluid Samples For Rapid Identification Of Infections, Erin E. Drewke, Robert L. Brand, Caroline G. Geels, Hanna K. Jensen, Kevin Wong, Jarret D. Sanders, Narasimhan Rajaram

Biomedical Engineering Faculty Publications and Presentations

Severe joint infections, such as septic arthritis, require rapid diagnostic testing of the synovial fluid aspirated from joints level so that a surgical team can be assembled quickly. We present a diffuse reflectance spectroscopy (DRS) system for noncontact determination of infection. Using a light-tight syringe holder and fiber optic probe, diffusely reflected light from 475 to 655 nm was acquired from 18 patient samples through the wall of a syringe in a noncontact and sterile manner. We determined the reflectance ratios at two different wavelengths—R ₄₉₀/R ₆₀₀ and R ₅₈₀/R ₆₀₀ and found statistically significant …

Assessing The Impact Of Femur Morphological Variations On Pediatric Hip Joint Biomechanics Using Statistical Shape Modeling, Tamara Chambers

Doctoral Dissertations and Master's Theses

This dissertation aimed to (1) quantify morphological variations in the pediatric hip joint and (2) evaluate the sensitivity of an infant musculoskeletal model (MSM) to these variations, considering hip joint center estimation errors. A shape statistical model (SSM) of decedent infant femurs from the Ortolani collection was created using ShapeWorks, capturing key morphological features, such as variations in the femoral neck-shaft and anteversion angles. Seven synthetic femurs were generated from the SSM to create SSM-informed MSMs, which were systematically evaluated through kinematics and kinetics analyses in OpenSim. Incorporating the SSM led to slight changes in the pediatric MSMs’ kinematics but …

Amino Acid-Based Protein-Mimic Hydrogel Incorporating Pro-Regenerative Lipid Mediator And Microvascular Fragments Promotes The Healing Of Deep Burn Wounds, Yan Lu, Shanchun Su, Chih Chang Chu, Yuichi Kobayashi, Abdul Razak Masoud, Hongying Peng, Nathan Lien, Mingyu He, Christopher Vuong, Ryan Tran, Song Hong

School of Medicine Faculty Publications

Pro-regenerative lipid mediator 1 (PreM1) is a specialized pro-resolving lipid mediator that promotes wound healing and regenerative functions of mesenchymal stem cells (MSCs), endothelial cells, and macrophages. The healing of third-degree (3°) burns and regenerative functions of MSCs are enhanced by ACgel1, an arginine-and-chitosan-based protein-mimic hybrid hydrogel. Adipose-tissue derived microvascular fragments (MVFs) are native vascularization units and a rich source of MSCs, endothelial cells, and perivascular cells for tissue regeneration. Here we describe an innovative PreM1-MVFs-ACgel1 construct that incorporated PreM1 and MVFs into ACgel1 via optimal design and fabrication. This construct delivered PreM1 to 3°-burn wounds at least up to …

Paper-Recorded Ecg Digitization Method With Automatic Reference Voltage Selection For Telemonitoring And Diagnosis, Liang Hung Wang, Chao Xin Xie, Tao Yang, Hong Xin Tan, Ming Hui Fan, I. Chun Kuo, Zne Jung Lee, Tsung Yi Chen, Pao Cheng Huang, Shih Lun Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

In electrocardiograms (ECGs), multiple forms of encryption and preservation formats create difficulties for data sharing and retrospective disease analysis. Additionally, photography and storage using mobile devices are convenient, but the images acquired contain different noise interferences. To address this problem, a suite of novel methodologies was proposed for converting paper-recorded ECGs into digital data. Firstly, this study ingeniously removed gridlines by utilizing the Hue Saturation Value (HSV) spatial properties of ECGs. Moreover, this study introduced an innovative adaptive local thresholding method with high robustness for foreground–background separation. Subsequently, an algorithm for the automatic recognition of calibration square waves was proposed …

Microwave Catalysis-Enabled Membrane Processes For Microbial Inactivation, Fangzhou Liu

Dissertations

The COVID-19 pandemic has highlighted the urgent need for advanced technologies to combat virus transmission. Traditional membrane filtration technologies primarily serve as physical barriers, capturing pollutants but failing to inactivate microbial agents such as bacteria and viruses. These membranes typically target larger particles but are ineffective against sub-micrometer viral particles. Thus, there's a critical demand for membrane filtration processes that combine robust filtration with antifouling and reaction -enabled functions for efficient pathogen disinfection. This research explores a novel microwave-assisted membrane filtration process incorporating catalytic reactions to enhance microbial disinfection and prevent membrane fouling, offering a groundbreaking solution to global challenges …

Mitochondrial Function In Lungs Of Rats With Different Susceptibilities To Hyperoxia-Induced Acute Lung Injury, Pardis Taheri, Devanshi D. Dave, Ranjan K. Dash, Guru P. Sharma, Anne V. Clough, Elizabeth R. Jacobs, Said H. Audi

Biomedical Engineering Faculty Research and Publications

Adult rats exposed to hyperoxia (>95% O₂) die from respiratory failure in 60–72 h. However, rats preconditioned with >95% O₂ for 48 h followed by 24 h in room air acquire tolerance of hyperoxia (H-T), whereas rats preconditioned with 60% O₂ for 7 days become more susceptible (H-S). Our objective was to evaluate lung tissue mitochondrial bioenergetics in H-T and H-S rats. Bioenergetics was assessed in mitochondria isolated from lung tissue of H-T, H-S, and control rats. Expressions of complexes involved in oxidative phosphorylation (OxPhos) were measured in lung tissue homogenate. Pulmonary endothelial filtration coefficient …

Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation, Isaac Browen, Hector M. Camarillo-Abad, Franceli L. Cibrian, Trudi Di Qi

Engineering Faculty Articles and Research

This paper presents a novel 3D system for human motion analysis - Motion Data Visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening …