Engineering Commons^™

Correlation Enhanced Distribution Adaptation For Prediction Of Fall Risk, Ziqi Guo, Teresa Wu, Thurmon Lockhart, Rahul Soangra, Hyunsoo Yoon

Physical Therapy Faculty Articles and Research

With technological advancements in diagnostic imaging, smart sensing, and wearables, a multitude of heterogeneous sources or modalities are available to proactively monitor the health of the elderly. Due to the increasing risks of falls among older adults, an early diagnosis tool is crucial to prevent future falls. However, during the early stage of diagnosis, there is often limited or no labeled data (expert-confirmed diagnostic information) available in the target domain (new cohort) to determine the proper treatment for older adults. Instead, there are multiple related but non-identical domain data with labels from the existing cohort or different institutions. Integrating different …

Dense & Attention Convolutional Neural Networks For Toe Walking Recognition, Junde Chen, Rahul Soangra, Marybeth Grant-Beuttler, Y. A. Nanehkaran, Yuxin Wen

Physical Therapy Faculty Articles and Research

Idiopathic toe walking (ITW) is a gait disorder where children’s initial contacts show limited or no heel touch during the gait cycle. Toe walking can lead to poor balance, increased risk of falling or tripping, leg pain, and stunted growth in children. Early detection and identification can facilitate targeted interventions for children diagnosed with ITW. This study proposes a new one-dimensional (1D) Dense & Attention convolutional network architecture, which is termed as the DANet, to detect idiopathic toe walking. The dense block is integrated into the network to maximize information transfer and avoid missed features. Further, the attention modules are …

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 …

Emulating Future Neurotechnology Using Magic, Jay A. Olson, Mariève Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall, Matthew L. Tompkins, Amir Raz, Petter Johansson

Psychology Faculty Articles and Research

Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion of privacy to an increase in self-understanding. Yet, evaluating these predictions is difficult given that people are poor at forecasting their reactions. To address this, we developed a paradigm using elements of performance magic to emulate future neurotechnologies. We led 59 participants to believe that a (sham) neurotechnological machine could infer their preferences, detect their errors, and reveal their deep-seated attitudes. The machine gave participants randomly assigned positive …

Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors And Machine Learning Algorithms, Rahul Soangra, Yuxin Wen, Hualin Yang, Marybeth Grant-Beuttler

Physical Therapy Faculty Articles and Research

Idiopathic toe walking (ITW) is a gait abnormality in which children’s toes touch at initial contact and demonstrate limited or no heel contact throughout the gait cycle. Toe walking results in poor balance, increased risk of falling, and developmental delays among children. Identifying toe walking steps during walking can facilitate targeted intervention among children diagnosed with ITW. With recent advances in wearable sensing, communication technologies, and machine learning, new avenues of managing toe walking behavior among children are feasible. In this study, we investigate the capabilities of Machine Learning (ML) algorithms in identifying initial foot contact (heel strike versus toe …

Machine Learning Based Medical Image Deepfake Detection: A Comparative Study, Siddharth Solaiyappan, Yuxin Wen

Engineering Faculty Articles and Research

Deep generative networks in recent years have reinforced the need for caution while consuming various modalities of digital information. One avenue of deepfake creation is aligned with injection and removal of tumors from medical scans. Failure to detect medical deepfakes can lead to large setbacks on hospital resources or even loss of life. This paper attempts to address the detection of such attacks with a structured case study. Specifically, we evaluate eight different machine learning algorithms, which include three conventional machine learning methods (Support Vector Machine, Random Forest, Decision Tree) and five deep learning models (DenseNet121, DenseNet201, ResNet50, ResNet101, VGG19) …

Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead

Engineering Faculty Articles and Research

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …

Digital Markers Of Autism, Ivonne Monarca, Franceli L. Cibrian, Monica Tentori

Engineering Faculty Articles and Research

Autism Spectrum Disorder (ASD) is a neurological condition that affects how a people communicate and interact with others. The use of screening tools during childhood is very important to detect those children who need to be referred for a diagnosis of ASD. However, most screening tools are based on parents' responses so the result can be subjective. In addition, most screening tools focus on social and communicative skills leaving aside sensory features, which have shown to have the potential to be ASD markers. Tactile processing has been little explored due to lack of tools to asses it, however with the …

Feel And Touch: A Haptic Mobile Game To Assess Tactile Processing, Ivonne Monarca, Monica Tentori, Franceli L. Cibrian

Engineering Faculty Articles and Research

Haptic interfaces have great potential for assessing the tactile processing of children with Autism Spectrum Disorder (ASD), an area that has been under-explored due to the lack of tools to assess it. Until now, haptic interfaces for children have mostly been used as a teaching or therapeutic tool, so there are still open questions about how they could be used to assess tactile processing of children with ASD. This article presents the design process that led to the development of Feel and Touch, a mobile game augmented with vibrotactile stimuli to assess tactile processing. Our feasibility evaluation, with 5 children …

Dimensionality Reduction For Classification Of Object Weight From Electromyography, Elnaz Lashgari, Uri Maoz

Psychology Faculty Articles and Research

Electromyography (EMG) is a simple, non-invasive, and cost-effective technology for measuring muscle activity. However, multi-muscle EMG is also a noisy, complex, and high-dimensional signal. It has nevertheless been widely used in a host of human-machine-interface applications (electrical wheelchairs, virtual computer mice, prosthesis, robotic fingers, etc.) and, in particular, to measure the reach-and-grasp motions of the human hand. Here, we developed an automated pipeline to predict object weight in a reach-grasp-lift task from an open dataset, relying only on EMG data. In doing so, we shifted the focus from manual feature-engineering to automated feature-extraction by using pre-processed EMG signals and thus …

Supporting Coordination Of Children With Asd Using Neurological Music Therapy: A Pilot Randomized Control Trial Comparing An Elastic Touch-Display With Tambourines, Franceli L. Cibrian, Melisa Madrigal, Marina Avelais, Monica Tentori

Engineering Faculty Articles and Research

Aim

To evaluate the efficacy of Neurologic Music Therapy (NMT) using a traditional and a technological intervention (elastic touch-display) in improving the coordination of children with Autism Spectrum Disorder (ASD), as a primary outcome, and the timing and strength control of their movements as secondary outcomes.

Methods

Twenty-two children with ASD completed 8 NMT sessions, as a part of a 2-month intervention. Participants were randomly assigned to either use an elastic touch-display (experimental group) or tambourines (control group). We conducted pre- and post- assessment evaluations, including the Developmental Coordination Disorder Questionnaire (DCDQ) and motor assessments related to the control of …

Circus In Motion: A Multimodal Exergame Supporting Vestibular Therapy For Children With Autism, Oscar Peña, Franceli L. Cibrian, Monica Tentori

Engineering Faculty Articles and Research

Exergames are serious games that involve physical exertion and are thought of as a form of exercise by using novel input models. Exergames are promising in improving the vestibular differences of children with autism but often lack of adaptation mechanisms that adjust the difficulty level of the exergame. In this paper, we present the design and development of Circus in Motion, a multimodal exergame supporting children with autism with the practice of non-locomotor movements. We describe how the data from a 3D depth camera enables the tracking of non-locomotor movements allowing children to naturally interact with the exergame . A …

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 …

Automatic Detection Of Dynamic And Static Activities Of The Older Adults Using A Wearable Sensor And Support Vector Machines, Jian Zhang, Rahul Soangra, Thurmon E. Lockhart

Physical Therapy Faculty Articles and Research

Although Support Vector Machines (SVM) are widely used for classifying human motion patterns, their application in the automatic recognition of dynamic and static activities of daily life in the healthy older adults is limited. Using a body mounted wireless inertial measurement unit (IMU), this paper explores the use of an SVM approach for classifying dynamic (walking) and static (sitting, standing and lying) activities of the older adults. Specifically, data formatting and feature extraction methods associated with IMU signals are discussed. To evaluate the performance of the SVM algorithm, the effects of two parameters involved in SVM algorithm—the soft margin constant …

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 …

The Natural Historian’S Guide To The Ct Galaxy: Step-By-Step Instructions For Preparing And Analyzing Computed Tomographic (Ct) Data Using Cross-Platform, Open Access Software, T. J. Buser, O. F. Boyd, A. Cortés, Cassandra M. Donatelli, M. A. Kolmann, J. L. Luparell, J. A. Pfeiffenberger, B. L. Sidlauskas, A. P. Summers

Engineering Faculty Articles and Research

The decreasing cost of acquiring computed tomographic (CT) data has fueled a global effort to digitize the anatomy of museum specimens. This effort has produced a wealth of open access digital three-dimensional (3D) models of anatomy available to anyone with access to the Internet. The potential applications of these data are broad, ranging from 3D printing for purely educational purposes to the development of highly advanced biomechanical models of anatomical structures. However, while virtually anyone can access these digital data, relatively few have the training to easily derive a desirable product (e.g., a 3D visualization of an anatomical structure) from …

Supporting Self-Regulation Of Children With Adhd Using Wearables: Tensions And Design Challenges, Franceli L. Cibrian, Kimberley D. Lakes, Arya Tavakoulnia, Kayla Guzman, Sabrina Schuck, Gillian R. Hayes

Engineering Faculty Articles and Research

The design of wearable applications supporting children with Attention Deficit Hyperactivity Disorders (ADHD) requires a deep understanding not only of what is possible from a clinical standpoint but also how the children might understand and orient towards wearable technologies, such as a smartwatch. Through a series of participatory design workshops with children with ADHD and their caregivers, we identified tensions and challenges in designing wearable applications supporting the self-regulation of children with ADHD. In this paper, we describe the specific challenges of smartwatches for this population, the balance between self-regulation and co-regulation, and tensions when receiving notifications on a smartwatch …

Learning In The Machine: To Share Or Not To Share?, Jordan Ott, Erik Linstead, Nicholas Lahaye, Pierre Baldi

Engineering Faculty Articles and Research

Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sharing is necessary. If so, to which degree of precision? If not, what are the alternatives? The goal of this study is to investigate these questions, primarily through simulations where the weight-sharing assumption is relaxed. Taking inspiration from neural circuitry, we explore the use of Free Convolutional Networks and neurons with variable connection patterns. Using Free Convolutional Networks, we show that while weight-sharing is a pragmatic optimization …

How Degrees Of Freedom Affects Sense Of Agency, Akima Connelly, Jungsu Pak, Tian Lan, Uri Maoz

Student Scholar Symposium Abstracts and Posters

Can the rubber-hand illusion be extended to a moving robotic arm in different degrees of freedom (DOF), inducing sense of ownership & agency over the arm? We hypothesize that DOF closer to what humans possess will result in a stronger sense of ownership and agency.

Using Green Emitting Ph-Responsive Nanogels To Report Environmental Changes Within Hydrogels: A Nanoprobe For Versatile Sensing, Mingning Zhu, Dongdong Lu, Shanglin Wu, Qing Lian, Wenkai Wang, L. Andrew Lyon, Weiguang Wang, Paulo Bártolo, Brian R. Saunders

Engineering Faculty Articles and Research

Remotely reporting the local environment within hydrogels using inexpensive laboratory techniques has excellent potential to improve our understanding of the nanometer-scale changes that cause macroscopic swelling or deswelling. Whilst photoluminescence (PL) spectroscopy is a popular method for such studies this approach commonly requires bespoke and time-consuming synthesis to attach fluorophores which may leave toxic residues. A promising and more versatile alternative is to use a pre-formed nanogel probe that contains a donor/acceptor pair and then “dope” that into the gel during gel assembly. Here, we introduce green-emitting methacrylic acid-based nanogel probe particles and use them to report the local environment …

Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead

Engineering Faculty Articles and Research

Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing ASD, exploring its genetic underpinnings, and designing effective interventions. This paper provides a comprehensive review of 45 papers utilizing supervised machine learning in ASD, including algorithms for classification and text analysis. The goal of the paper is to identify and describe supervised machine learning trends in ASD literature as …

Bendablesound: An Elastic Multisensory Surface Using Touch-Based Interactions To Assist Children With Severe Autism During Music Therapy, Franceli L. Cibrian, Oscar Peña, Deysi Ortega, Monica Tentori

Engineering Faculty Articles and Research

Neurological Music Therapy uses live music to improve the sensorimotor regulation of children with severe autism. However, they often lack musical training and their impairments limit their interactions with musical instruments. In this paper, we present our co-design work that led to the BendableSound prototype: an elastic multisensory surface encouraging users to practice coordination movements when touching a fabric to play sounds. We present the results of a formative study conducted with 18 teachers showing BendableSound was perceived as “usable” and “attractive”. Then, we present a deployment study with 24 children with severe autism showing BendableSound is “easy to use” …

Hydrothermally Processed 1d Hydroxyapatite: Mechanism Of Formation And Biocompatibility Studies, Zoran Stojanović, Nenad Ignjatović, Victoria M. Wu, Vojca Žunič, Ljiljana Veselinović, Srečo D. Škapin, Miroslav Miljković, Vuk Uskoković, Dragab Uskoković

Pharmacy Faculty Articles and Research

Recent developments in bone tissue engineering have led to an increased interest in one-dimensional (1D) hydroxyapatite (HA) nano- and micro-structures such as wires, ribbons and tubes. They have been proposed for use as cell substrates, reinforcing phases in composites and carriers for biologically active substances. Here we demonstrate the synthesis of 1D HA structures using an optimized, urea-assisted, high-yield hydrothermal batch process. The one-pot process, yielding HA structures composed of bundles of ribbons and wires, was typified by the simultaneous occurrence of a multitude of intermediate reactions, failing to meet the uniformity criteria over particle morphology and size. To overcome …

Calcium Phosphate As A Key Material For Socially Responsible Tissue Engineering, Vuk Uskoković, Victoria M. Wu

Pharmacy Faculty Articles and Research

Socially responsible technologies are designed while taking into consideration the socioeconomic, geopolitical and environmental limitations of regions in which they will be implemented. In the medical context, this involves making therapeutic platforms more accessible and affordable to patients in poor regions of the world wherein a given disease is endemic. This often necessitates going against the reigning trend of making therapeutic nanoparticles ever more structurally complex and expensive. However, studies aimed at simplifying materials and formulations while maintaining the functionality and therapeutic response of their more complex counterparts seldom provoke a significant interest in the scientific community. In this review …

When 1 + 1 > 2: Nanostructured Composites For Hard Tissue Engineering Applications, Vuk Uskoković

Pharmacy Faculty Articles and Research

Multicomponent, synergistic and multifunctional nanostructures have taken over the spotlight in the realm of biomedical nanotechnologies. The most prospective materials for bone regeneration today are almost exclusively composites comprising two or more components that compensate for the shortcomings of each one of them alone. This is quite natural in view of the fact that all hard tissues in the human body, except perhaps the tooth enamel, are composite nanostructures. This review article highlights some of the most prospective breakthroughs made in this research direction, with the hard tissues in main focus being those comprising bone, tooth cementum, dentin and enamel. …