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3D volume segmentation is a fundamental task in many scientific and medical applications. Producing accurate segmentations efficiently is challenging, in part due to low imaging data quality (e.g., noise and low image resolution) and…
Deep-UV ~ 250 nm (4.96 eV) tilted in-situ co-illumination of the sample under imaging by scanning electron microscope (SEM) is developed at a robust and practical instrument level. Precise mechanical control of the lateral position and tilt…
Electroencephalography (EEG) recordings are analyzed using battery-powered wearable devices to monitor brain activities and neurological disorders. These applications require long and continuous processing to generate feasible results.…
Current pain assessment within hospitals often relies on self-reporting or non-specific EKG vital signs. This system leaves critically ill, sedated, and cognitively impaired patients vulnerable to undertreated pain and opioid overuse.…
This paper proposes and implements an intuitive and pervasive solution for neonatal EEG monitoring assisted by sonification and deep learning AI that provides information about neonatal brain health to all neonatal healthcare professionals,…
Early detection of cardiovascular diseases is crucial for effective treatment and an electrocardiogram (ECG) is pivotal for diagnosis. The accuracy of Deep Learning based methods for ECG signal classification has progressed in recent years…
Micromanipulations, perfusions and measurements performed using glass microelectrodes filled with an electrolyte is a conventional technique for experimental morphological and membrane electrophysiological studies at a single cell and…
Mobile medical imaging devices are invaluable for clinical diagnostic purposes both in and outside healthcare institutions. Among the various imaging modalities, only a few are readily portable. Magnetic resonance imaging (MRI), the gold…
Epilepsy is one of the most prevalent brain disorders that disrupts the lives of millions worldwide. For patients with drug-resistant seizures, there exist implantable devices capable of monitoring neural activity, promptly triggering…
Traditional human activity recognition uses either direct image analysis or data from wearable inertial measurement units (IMUs), but can be ineffective in challenging underwater environments. We introduce a novel hybrid approach that…
Nano-machines circulating inside the human body, collecting data on tissue conditions, represent a vital part of next-generation medical diagnostic systems. However, for these devices to operate effectively, they need to relay not only…
Ubiquitous positioning for pedestrian in adverse environment has served a long standing challenge. Despite dramatic progress made by Deep Learning, multi-sensor deep odometry systems yet pose a high computational cost and suffer from…
Objective: A clinical decision support tool that automatically interprets EEGs can reduce time to diagnosis and enhance real-time applications such as ICU monitoring. Clinicians have indicated that a sensitivity of 95% with a specificity…
Single-channel electroencephalogram (EEG) is a cost-effective, comfortable, and non-invasive method for monitoring brain activity, widely adopted by researchers, consumers, and clinicians. The increasing number and proportion of articles on…
Robotic prostheses and exoskeletons can do wonders compared to their non-robotic counterpart. However, in a cost-soaring world where 1 in every 10 patients has access to normal medical prostheses, access to advanced ones is, unfortunately,…
Transcatheter valve repair presents significant challenges due to the mechanical limitations and steep learning curve associated with manual catheter systems. This paper investigates the use of robotics to facilitate transcatheter…
This paper presents a dataset containing recordings of the electroencephalogram (EEG) and the electromyogram (EMG) from eight subjects who were assisted in moving their right arm by an active orthosis device. The supported movements were…
Incorrectly sized balloon catheters can lead to increased post-surgical complications, yet even with preoperative imaging, correct selection remains a challenge. With limited feedback during surgery, it is difficult to verify correct…
Epilepsy is typically diagnosed through electroencephalography (EEG) and long-term video-EEG (vEEG) monitoring. The manual analysis of vEEG recordings is time-consuming, necessitating automated tools for seizure detection. Recent…
Billions of vascular access procedures are performed annually worldwide, serving as a crucial first step in various clinical diagnostic and therapeutic procedures. For pediatric or elderly individuals, whose vessels are small in size…