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Electroencephalography (EEG) is an integral tool in neurocognitive research worldwide. However, research grade EEG (32/64ch) systems are expensive and have cumbersome setup designed for clinical usage not suited for rugged environment of…
Electrocardiogram (ECG) is one of the most important diagnostic tools in clinical applications. With the advent of advanced algorithms, various deep learning models have been adopted for ECG tasks. However, the potential of Transformer for…
Electrocardiogram (ECG) biometrics have emerged as a promising modality for continuous, liveness-aware authentication in wearable systems. However, many prior studies report overly optimistic results due to data leakage (e.g., random splits…
The last two decades have witnessed a dramatic growth of wearable sensor technology, mainly represented by flexible, stretchable, on-skin electronic sensors that provide rich information of the wearer's health conditions and surroundings. A…
Entropy is a difficult concept to teach using real-world examples. Unlike temperature, pressure, volume, or work, it's not a quantity which most students encounter in their day-to-day lives. Even the way entropy is often qualitatively…
Conventional scalp-based EEG systems are cumbersome to use, requiring extensive setup, restrictive wiring, and conductive gels that can dry out and limit long-term monitoring, while also carrying social stigma. As a result, there is…
Human body fitting, which aligns parametric body models such as SMPL to raw 3D point clouds of clothed humans, serves as a crucial first step for downstream tasks like animation and texturing. An effective fitting method should be both…
Speech enhancement is a fundamental challenge in signal processing, particularly when robustness is required across diverse acoustic conditions and microphone setups. Deep learning methods have been successful for speech enhancement, but…
Fabrication of porous GaN distributed Bragg reflectors (DBRs) via the selective electrochemical etching (ECE) of conductive Si-doped layers, separated by non-intentionally doped (NID) layers, provides a straightforward methodology for…
Regressively-based surface electromyography (sEMG) prosthetics are widely used for their ability to continuously convert muscle activity into finger force and motion. However, they typically require additional kinematic or dynamic sensors,…
The design of modular, passive, and static artificial metasurfaces to be used as electromagnetic skins (EMSs) of buildings for improving the coverage in urban millimeter-wave communication scenarios is addressed. Towards this end, an ad-hoc…
The human neuromuscular system consisting of skeletal muscles and neural circuits is a complex system that is not yet fully understood. Surface electromyography (EMG) can be used to study muscle behavior from the outside. Computer…
Extensibility is beyond the paradigm of classical soft glassy materials, and more broadly, yield-stress fluids. Recently, model yield-stress fluids with significant extensibility have been designed by adding polymeric phases to classically…
3D printing technology offers the possibility of producing synthetic samples with accurately defined microstructures. As indicated by effective medium theory (EMT), the shapes, orientations, and sizes of voids significantly affect the…
Wearable exoskeletons hold transformative promise for restoring mobility across diverse users with muscular weakness or other impairments. However, their translation beyond laboratory environments remains limited by sensing systems that…
Three-dimensional (3D) printing has emerged as a powerful tool for material, food, and life science research and development, where the technology democratization necessitates the advancement of open-source platforms. Herein, we developed a…
Large scale graphene electronics desires lithographic patterning of narrow graphene nanoribbons (GNRs) for device integration. However, conventional lithography can only reliably pattern ~20nm wide GNR arrays limited by lithography…
We introduce a novel wearable textile-garment featuring an innovative electrode placement aimed at minimizing noise and motion artifacts, thereby enhancing signal fidelity in Electrocardiography (ECG) recordings. We present a comprehensive,…
Deep learning-based surface electromyography (sEMG) gesture recognition is frequently bottlenecked by data scarcity and limited subject diversity. While synthetic data generation via Generative Adversarial Networks (GANs) and diffusion…
Dielectric barrier discharge (DBD) plasma actuator arrays have been suggested as active flow control devices due to the robust electrohydrodynamic (EHD) force generation in variable atmospheric conditions. DBD plasma augmentation schemes…