Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40040007
Studying the soft robot-tissue mechanical interaction in muscle stimulation devices poses a significant challenge due to the complex behavior of the materials involved. To advance this field, this paper models computationally three types of soft elas...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039938
EEG source imaging is an indispensable tool for non-invasive study of brain function. Existing methods mainly directly deal with the EEG inverse problem by imposing prior constraints. However, different brain activation patterns may produce similar p...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039681
Artificial intelligence & Computer vision have the potential to improve surgical training, especially for minimally invasive surgery by analyzing intraoperative and simulation videos for training or performance improvement purposes. Among these, tech...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039378
Treatments of disuse-induced muscle atrophy entail unmet clinical needs due to the lack of medical devices capable of mimicking physicians manual therapies. Therefore, in this paper we develop and model a wearable soft pneumatic elastomeric actuator ...
Most walking organisms tend to have relatively light limbs and heavy bodies in order to facilitate rapid limb motion. However, the limbs of brittle stars (Class Ophiuroidea) are primarily comprised of dense skeletal elements, with potentially much hi...
The rapid integration of machine learning (ML) predictors into in silico medicine has revolutionized the estimation of quantities of interest that are otherwise challenging to measure directly. However, the credibility of these predictors is critical...
Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. In chemical reaction network modeling, this synergy proves valuable, addressing the high computati...
Interactions between vehicle-pedestrian at intersections often lead to safety-critical situations. This study aims to model the crash avoidance behaviors of vehicles during interactions with pedestrians in near-miss scenarios, contributing to the dev...
Adequate access to radiotherapy is a critical global concern affecting low-resource settings such as low- and middle-income countries and rural regions. We propose to reduce this disparity by developing a novel low-cost radiotherapy device that treat...
Selection of lead therapeutic molecules is often driven predominantly by pharmacological efficacy and safety. Candidate developability, such as biophysical properties that affect the formulation of the molecule into a product, is usually evaluated on...