IEEE Open Journal of Engineering in Medicine and Biology
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Lung Nodule Malignancy Prediction from Longitudinal CT Scans with Siamese Convolutional Attention Networks
Goal: We propose a convolutional attention-based network that allows for use of pre-trained 2-D convolutional feature extractors and is extendable to multi-time-point classification in a Siamese structure. Methods: Our proposed framework is evaluated for single- and multi-time-point classification to explore... Read more
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Robust Classification of Intramuscular EMG Signals to Aid the Diagnosis of Neuromuscular Disorders
Objective: This article presents the design and validation of an accurate automatic diagnostic system to classify intramuscular EMG (iEMG) signals into healthy, myopathy, or neuropathy categories to aid the diagnosis of neuromuscular diseases. Method: First, an iEMG signal is decimated... Read more
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Examining the Effect of Haptic Factors for Vascular Palpation Skill Assessment Using an Affordable Simulator
Goal: Simulators that incorporate haptic feedback for clinical skills training are increasingly used in medical education. This study addresses the neglected aspect of rendering simulated feedback for vascular palpation skills training by systematically examining the effect of haptic factors on... Read more
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Specificity Analysis of Genome Based on Statistically Identical K-Words With Same Base Combination
Goal: Individual characteristics are determined through a genome consisting of a complex base combination. This base combination is reflected in the k-word profile, which represents the number of consecutive k bases. Therefore, it is important to analyze the genome-specific statistical... Read more
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Rate-Dependent and Relaxation Properties of Porcine Aortic Heart Valve Biomaterials
Objective: This work evaluates the rate-dependent and relaxation properties of native porcine heart valves, glutaraldehyde fixed porcine pericardium, and decellularized sterilized porcine pericardium. Methods: Biaxial tension testing was performed at strain-rates of 0.001 s -1 , 0.01 s -1 , 0.1 s -1 , and 1... Read more
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A Patient-Specific Computational Framework for the Argus II Implant
Goal: Retinal prosthesis performance is limited by the variability of elicited phosphenes. The stimulating electrode’s position with respect to retinal ganglion cells (RGCs) affects both perceptual threshold and phosphene shape. We created a modeling framework incorporating patient-specific anatomy and electrode... Read more
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A Structured Cleaving Mesh for Bioheat Transfer Application
Goal: The thermoregulation mechanism is a complex system that executes vital processes in the human body. Various models have been proposed to simulate the thermoregulatory response of an adult human to environmental stimuli. However, these models generally rely on stylized... Read more
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A Multimodal Pancreas Phantom for Computer-Assisted Surgery Training
Training of surgical residents and the establishment of innovative surgical techniques require training phantoms that realistically mimic human anatomy. Because animal models have their limitations due to ethical aspects, costs, and the required efforts to set up such training, artificial... Read more
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Comparison of Signal Processing Methods for Reducing Motion Artifacts in High-Density Electromyography During Human Locomotion
Objective: High-density electromyography (EMG) is useful for studying changes in myoelectric activity within a muscle during human movement, but it is prone to motion artifacts during locomotion. We compared canonical correlation analysis and principal component analysis methods for signal decomposition... Read more
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Smartphone-Based Estimation of Item 3.8 of the MDS-UPDRS-III for Assessing Leg Agility in People With Parkinson’s Disease
Goal: In this paper we investigated the use of smartphone sensors and Artificial Intelligence techniques for the automatic quantification of the MDS-UPDRS-Part III Leg Agility (LA) task, representative of lower limb bradykinesia. Methods: We collected inertial data from 93 PD... Read more
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For Motion Assistance Humans Prefer to Rely on a Robot Rather Than on an Unpredictable Human
Objective: The last decades have seen a surge of robots for physical training and work assistance. How to best control these interfaces is unknown, although arguably the interaction should be similar to human movement assistance. Methods: We compare the behaviour... Read more
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Assessment of Fractional-Order Arterial Windkessel as a Model of Aortic Input Impedance
Goal: Fractional-order Windkessel model is proposed to describe the aortic input impedance. Compared with the conventional arterial Windkessel, the main advantage of the proposed model is the consideration of the viscoelastic nature of the arterial wall using the fractional-order capacitor... Read more
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Small-World Propensity Reveals the Frequency Specificity of Resting State Networks
Functional connectivity (FC) is an important indicator of the brain’s state in different conditions, such as rest/task or health/pathology. Here we used high-density electroencephalography coupled to source reconstruction to assess frequency-specific changes of FC during resting state. Specifically, we computed... Read more
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Modulating the Structure of Motor Variability for Skill Learning Through Specific Muscle Synergies in Elderlies and Young Adults
Motor variability – performance variations across task repetitions – has been assumed to be undesirable. But recent studies argue that variability facilitates early motor learning by allowing exploratory search of reward-generating motion, and that variability’s structure may be modulated by... Read more
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On Error-Related Potentials During Sensorimotor-Based Brain-Computer Interface: Explorations With a Pseudo-Online Brain-Controlled Speller
Brain-computer interface (BCI) spelling is a promising communication solution for people in paralysis. Currently, BCIs suffer from imperfect decoding accuracy which calls for methods to handle spelling mistakes. Detecting error-related potentials (ErrPs) has been early identified as a potential remedy.... Read more
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Accelerometry-Based Digital Gait Characteristics for Classification of Parkinson’s Disease: What Counts?
Gait may be a useful biomarker that can be objectively measured with wearable technology to classify Parkinson’s disease (PD). This study aims to: (i) comprehensively quantify a battery of commonly utilized gait digital characteristics (spatiotemporal and signal-based), and (ii) identify... Read more
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Predicting Lymphoma Development by Exploiting Genetic Variants and Clinical Findings in a Machine Learning-Based Methodology With Ensemble Classifiers in a Cohort of Sjögren’s Syndrome Patients
Lymphoma development constitutes one of the most serious clinico-pathological manifestations of patients with Sjögren’s Syndrome (SS). Over the last decades the risk for lymphomagenesis in SS patients has been studied aiming to identify novel biomarkers and risk factors predicting lymphoma... Read more
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Engineered Three-Dimensional Scaffolds Modulating Fate of Breast Cancer Cells Using Stiffness and Morphology Related Cell Adhesion
Artificially engineering the tumor microenvironment in vitro as a vital tool for understanding the mechanism of tumor progression. In this study, we developed three-dimensional cell scaffold systems with different topographical features and mechanical properties but similar surface chemistry. The cell... Read more
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Ultrasound Based Planning and Navigation for Non-Anatomical Liver Resections – An Ex-Vivo Study
Non-anatomical resections of liver tumors can be very challenging as the surgeon cannot use anatomical landmarks on the liver surface or in the ultrasound image for guidance. This makes it difficult to achieve negative resection margins (R0) and still preserve... Read more
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Ultrasound Stimulations Induce Prolonged Depolarization and Fast Action Potentials in Leech Neurons
Ultrasound (US) stimulation carries the promise of a selective, reversible, and non-invasive modulation of neural activity without the need for genetic manipulation of neural structures. However, the mechanisms of US-induced generation of action potentials (APs) are still unclear. Methods: Here... Read more
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Temozolomide in Combination With NF-κB Inhibitor Significantly Disrupts the Glioblastoma Multiforme Spheroid Formation
Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor, accounting for 50% of all cases. GBM patients have a five-year survival rate of merely 5.6% and a median overall survival of 14.6 months with the “Stupp” regimen, 20.9... Read more