The prevalence of fatty liver disease is on the rise, posing a significant global health concern. If left untreated, it can progress into more serious liver diseases. Therefore, accurately diagnosing the condition at an early stage is essential for m...
The increasing number of individuals with disabilities-over 61 million adults in the United States alone-underscores the urgent need for technologies that enhance autonomy and independence. Among these individuals, millions rely on wheelchairs and of...
: Caregivers experience high rates of occupational injuries, especially during wheelchair transfers, which often result in back pain and musculoskeletal disorders due to the physical demands of lifting and repositioning. While mechanical floor lifts,...
In terms of facial expressions, micro-expressions are more realistic than macro-expressions and provide more valuable information, which can be widely used in psychological counseling and clinical diagnosis. In the past few years, deep learning metho...
Non-contact heart monitoring is crucial in advancing telemedicine, fitness tracking, and mass screening. Remote photoplethysmography (rPPG) is a non-contact technique to obtain information about heart pulse by analyzing the changes in the light inten...
BACKGROUND: As the Internet of Things (IoT) expands, it enables new forms of communication, including interactions mediated by teleoperated robots like avatars. While extensive research exists on the effects of these devices on communication partners...
The detection of fetal ultrasound standard planes (FUSPs) is important for the diagnosis of fetal malformation and the prevention of perinatal death. As a promising deep-learning technique in FUSP detection, SonoNet's network parameters have a large ...
In rehabilitation, physicians plan lower-limb exercises via linear guidance. Ensuring efficacy and safety, they design patient-specific paths, carefully plotting smooth trajectories to minimize jerks. Replicating their precision in robotics is a majo...
This article introduces a novel approach to detecting honey adulteration by combining ultra-fast gas chromatography (UF-GC) with advanced machine learning techniques. Machine learning models, particularly support vector regression (SVR) and least abs...
Accurate polyp image segmentation is of great significance, because it can help in the detection of polyps. Convolutional neural network (CNN) is a common automatic segmentation method, but its main disadvantage is the long training time. Transformer...