OJEMB presents

Most Impactful

COVID-19 Artificial Intelligence Diagnosis using only Cough Recordings
Abstract: Goal: We hypothesized that COVID-19 subjects, especially including asymptomatics, could be accurately discriminated only from a forced-cough cell phone recording using Artificial Intelligence. To train our MIT Open Voice model we built a data collection pipeline of COVID-19 cough recordings... Read more
Walking Faster and Farther With a Soft Robotic Exosuit: Implications for Post-Stroke Gait Assistance and Rehabilitation
Objective: Soft robotic exosuits can improve the mechanics and energetics of walking after stroke. Building on this prior work, we evaluated the effects of the first prototype of a portable soft robotic exosuit. Methods: Exosuit-induced changes in the overground walking... Read more
A Framework for Biomarkers of COVID-19 Based on Coordination of Speech-Production Subsystems
Goal: We propose a speech modeling and signal-processing framework to detect and track COVID-19 through asymptomatic and symptomatic stages. Methods: The approach is based on complexity of neuromotor coordination across speech subsystems involved in respiration, phonation and articulation, motivated by... Read more
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