Other Biomedical Engineering and Bioengineering Commons^™

Fiber Optic Polarimetric Stress Sensor Improvements, Maxwell R. Richter, Max Randall, Mark C. Harrison

Engineering Faculty Articles and Research

The progression of diseases such as cancer has been correlated with tissue stiffness. For example, breast cancer tissue has been found to be stiffer than healthy mammary tissue. At present, stiffness measurement devices are not suitable for nondestructive, high-resolution measurements on small, delicate samples. We report a compact, portable, and sensitive fiber optic stress sensor that overcomes many of these limitations and is suitable for soft materials such as tissue. We demonstrate several improvements to a previous fiber stress sensor in physical hardware, software, and data analysis. We have designed and fabricated a custom enclosure to shield the sensitive setup …

Dynamic, Reconfigurable, And Hierarchical Biosynthetic Composites Via Collagen Self-Assembly Within Highly Crowded Microgel Pastes, Elif Narbay, Abbygail Caine, Sanika Pandit, Gabrielle Montgomery, Marion Harper, E. Daniel Cárdenas-Vásquez, Hatte Hamilton, Megan Hicks, Daniel Mattar, Kyle Choy, Marco Bisoffi, L. Andrew Lyon

Engineering Faculty Articles and Research

The fabrication of a new class of biomimetic biomaterials is reported using nanostructured microgel pastes formed from “overpacked” assemblies of ultrasoft poly(N-isopropyl acrylamide-co-acrylic acid) microgels and their composites with collagen. Despite the solid-like nature of microgel pastes, collagen fibrillogenesis is robust and rapid, with a 3D collagen network forming throughout the paste volume. Structural organization within the composite is interrogated via a suite of microscopy methods, while rheological characterization provides insight into the static and dynamic mechanical properties of the materials. Long-range fibrillogenesis is enabled by local crowding, dynamics, and spatial reconfigurability of pastes at the …

Palpation Characteristics Of An Instrumented Virtual Cricothyroidotomy Simulator, Melih Turkseven, Trudi Di Qi, Ganesh Sankaranarayanan, Suvranu De

Engineering Faculty Articles and Research

Cricothyroidotomy (CCT) is a critical, life-saving procedure requiring the identification of key neck landmarks through palpation. Interactive virtual simulation offers a promising, cost-effective approach to CCT training with high visual realism. However, developing the palpation skills necessary for CCT requires a haptic interface with tactile sensitivity comparable to human fingers. Such interfaces are often represented by plastic partial mannequins, which require further adaptation to integrate into virtual environments. This study introduces an instrumented physical palpation interface for CCT, integrated into a virtual surgical simulator, and tested on 10 surgeons who practiced the procedure over a training period. Data on haptic …

Conversational Voice User Interfaces Supporting Individuals With Down Syndrome: A Literature Review, Franceli L. Cibrian, Concepción Valdez, Lauren Min, Vivian Genaro Motti

Engineering Faculty Articles and Research

Conversational Voice User Interfaces (CVUIs) are widely used in commercial applications such as personal assistants. CVUIs are beneficial for most users as they enable interaction through speech and natural language. However, recent studies indicate that underrepresented user groups, such as individuals with speech impairments and specifically those with Down syndrome, face challenges in using voice commands to control CVUIs. The anatomical and physiological differences affecting the voice, speech, fluency, and prosody of users with Down syndrome hinder their experience with CVUIs. This article presents the results of 43 papers related to the use of voice user interfaces supporting individuals with …

Movian: Advancing Human Motion Analysis With 3d Visualization And Annotation, Trudi Di Qi, Isaac Browen, David Zhang, Hector M. Camarillo-Abad, Franceli L. Cibrian

Engineering Faculty Articles and Research

Human motion analysis, including data visualization and annotation, is crucial for understanding human behavior and intentions during various activities, aiding in the development of innovative tools that support independent living. Current wearable sensing technology provides rich 3D spatial movement data but generates multimodal complex datasets that require specialized skills for effective analysis. Despite the need, limited research exists on tools for effective visualization and easy annotation of such complex motion data. MoViAn (Motion Data Visualization and Annotation) is an innovative 3D data analysis system offering enriched visual representations of 3D human motion data (e.g., gaze, hand movements), along with an …

Etherealbreathing: A Holographic Biofeedback Game To Support Relaxation In Autistic Children, Arturo Morales Téllez, Isabel López Hurtado, Franceli L. Cibrian, Monica Tentori

Engineering Faculty Articles and Research

Biofeedback training for box breathing is becoming increasingly accessible due to advancements in consumer-grade breathing sensors. However, there is limited research on their design and applications for specialized populations. This study evaluates a novel biofeedback holographic game, EtherealBreathing, designed to support autistic children. In EtherealBreathing, children practice box breathing to collect virtual elements to maintain the Earth's balance, using a wearable sensor to measure chest expansion for breath detection. A deployment study with 20 autistic children revealed that EtherealBreathing effectively promotes box breathing, leading to better health-related outcomes, such as lowering participants’ heart and respiratory rates than traditional practices. Biofeedback …

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 …

Advancing Brain Tumor Segmentation With Spectral–Spatial Graph Neural Networks, Sina Mohammadi, Mohamed Allali

Engineering Faculty Articles and Research

In the field of brain tumor segmentation, accurately capturing the complexities of tumor sub-regions poses significant challenges. Traditional segmentation methods usually fail to accurately segment tumor subregions. This research introduces a novel solution employing Graph Neural Networks (GNNs), enriched with spectral and spatial insight. In the supervoxel creation phase, we explored methods like VCCS, SLIC, Watershed, Meanshift, and Felzenszwalb–Huttenlocher, evaluating their performance based on homogeneity, moment of inertia, and uniformity in shape and size. After creating supervoxels, we represented 3D MRI images as a graph structure. In this study, we combined Spatial and Spectral GNNs to capture both local and …

Adaptive Octree Meshes For Simulation Of Extracellular Electrophysiology, Christopher Bc Girard, Dong Song

Engineering Faculty Articles and Research

Objective. The interaction between neural tissues and artificial electrodes is crucial for understanding and advancing neuroscientific research and therapeutic applications. However, accurately modeling this space around the neurons rapidly increases the computational complexity of neural simulations. Approach. This study demonstrates a dynamically adaptive simulation method that greatly accelerates computation by adjusting spatial resolution of the simulation as needed. Use of an octree structure for the mesh, in combination with the admittance method for discretizing conductivity, provides both accurate approximation and ease of modification on-the-fly. Main results. In tests of both local field potential estimation and multi-electrode stimulation, dynamically adapted meshes …

Counterventions: A Reparative Reflection On Interventionist Hci, Rua Mae Williams, Louanne E. Boyd, Juan E. Gilbert

Engineering Faculty Articles and Research

Research in HCI applied to clinical interventions relies on normative assumptions about which bodies and minds are healthy, valuable, and desirable. To disrupt this normalizing drive in HCI, we define a “counterventional approach” to intervention technology design informed by critical scholarship and community perspectives. This approach is meant to unsettle normative assumptions of intervention as urgent, necessary, and curative. We begin with a historical overview of intervention in HCI and its critics. Then, through reparative readings of past HCI projects in autism intervention, we illustrate the emergent principles of a counterventional approach and how it may manifest research outcomes that …

Split And Join: An Efficient Approach For Simulating Stapled Intestinal Anastomosis In Virtual Reality, Di Qi, Suvranu De

Engineering Faculty Articles and Research

Colorectal cancer is a life-threatening disease. It is the second leading cause of cancer-related deaths in the United States. Stapled anastomosis is a rapid treatment for colorectal cancer and other intestinal diseases and has become an integral part of routine surgical practice. However, to the best of our knowledge, there is no existing work simulating intestinal anastomosis that often involves sophisticated soft tissue manipulations such as cutting and stitching. In this paper, for the first time, we propose a novel split and join approach to simulate a side-to-side stapled intestinal anastomosis in virtual reality. We mimic the intestine model using …

An Adaptive Model To Support Biofeedback In Ami Environments: A Case Study In Breathing Training For Autism, Arturo Morales, Franceli L. Cibrian, Luis A. Castro, Monica Tentori

Engineering Faculty Articles and Research

Biofeedback systems have shown promising clinical results in regulating the autonomic nervous system (ANS) of individuals. However, they typically offer a “one-size-fits-all” solution in which the personalization of the stimuli to the needs and capabilities of its users has been largely neglected. Personalization is paramount in vulnerable populations like children with autism given their sensory diversity. Ambient intelligence (AmI) environments enable creating effective adaptive mechanisms in biofeedback to adjust the stimuli to each user’s performance. Yet, biofeedback models with adaptive mechanisms are scarce in the AmI literature. In this paper, we propose an adaptive model to support biofeedback that takes …

Admittance Method For Estimating Local Field Potentials Generated In A Multi-Scale Neuron Model Of The Hippocampus, Clayton S. Bingham, Javad Paknahad, Christopher Bc Girard, Kyle Loizos, Jean-Marie C. Bouteiller, Dong Song, Gianluca Lazzi, Theodore W. Berger

Engineering Faculty Articles and Research

Significant progress has been made toward model-based prediction of neral tissue activation in response to extracellular electrical stimulation, but challenges remain in the accurate and efficient estimation of distributed local field potentials (LFP). Analytical methods of estimating electric fields are a first-order approximation that may be suitable for model validation, but they are computationally expensive and cannot accurately capture boundary conditions in heterogeneous tissue. While there are many appropriate numerical methods of solving electric fields in neural tissue models, there isn't an established standard for mesh geometry nor a well-known rule for handling any mismatch in spatial resolution. Moreover, the …

Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead

Engineering Faculty Articles and Research

Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC’s efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also …

Identification And Analysis Of Behavioral Phenotypes In Autism Spectrum Disorder Via Unsupervised Machine Learning, Elizabeth Stevens, Dennis R. Dixon, Marlena N. Novack, Doreen Granpeesheh, Tristram Smith, Erik Linstead

Engineering Faculty Articles and Research

Background and objective: Autism spectrum disorder (ASD) is a heterogeneous disorder. Research has explored potential ASD subgroups with preliminary evidence supporting the existence of behaviorally and genetically distinct subgroups; however, research has yet to leverage machine learning to identify phenotypes on a scale large enough to robustly examine treatment response across such subgroups. The purpose of the present study was to apply Gaussian Mixture Models and Hierarchical Clustering to identify behavioral phenotypes of ASD and examine treatment response across the learned phenotypes.

Materials and methods: The present study included a sample of children with ASD (N = 2400), …

Deswelling Induced Morphological Changes In Dual Ph And Temperature Responsive Ultra-Low Crosslinked Poly (N-Isopropyl Acrylamide)-Co-Acrylic Acid Microgels, Molla R. Islam, Maddie Tumbarello, L. Andrew Lyon

Engineering Faculty Articles and Research

Poly(N-isopropylacrylamide) microgels prepared without exogenous cross-linker are extremely “soft” as a result of their very low cross-linking density, with network connectivity arising only from the self-crosslinking of pNIPAm chains. As a result of this extreme softness, our group and others have taken interest in using these materials in a variety of bioengineering applications, while also pursuing studies of their fundamental properties. Here, we report deswelling triggered structural changes in poly(N-isopropylacrylamide-co-acrylic acid) (ULC10AAc) microgels prepared by precipitation polymerization. Dynamic light scattering suggests that the deswelling of these particles not only depends on the collapse of …

Portable Polarimetric Fiber Stress Sensor System For Visco-Elastic And Biomimetic Material Analysis, Mark C. Harrison, Andrea M. Armani

Engineering Faculty Articles and Research

Non-destructive materials characterization methods have significantly changed our fundamental understanding of material behavior and have enabled predictive models to be developed. However, the majority of these efforts have focused on crystalline and metallic materials, and transitioning to biomaterials, such as tissue samples, is non-trivial, as there are strict sample handling requirements and environmental controls which prevent the use of conventional equipment. Additionally, the samples are smaller and more complex in composition. Therefore, more advanced sample analysis methods capable of operating in these environments are needed. In the present work, we demonstrate an all-fiber-based material analysis system based on optical polarimetry. …