Medical & biological engineering & computing
Sep 18, 2024
Accurate and fast extraction of step parameters from video recordings of gait allows for richer information to be obtained from clinical tests such as Timed Up and Go. Current deep-learning methods are promising, but lack in accuracy for many clinica...
(1) Background: As digital health technology evolves, the role of accurate medical-gloved hand tracking is becoming more important for the assessment and training of practitioners to reduce procedural errors in clinical settings. (2) Method: This stu...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 17, 2024
Advancements in machine learning offer promising avenues for the identification of ADHD symptoms in adults, an endeavour traditionally encumbered by the intricacies of human behavioural patterns. In this paper, we introduce three innovative dual-stre...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Sep 17, 2024
Facial action units (AUs) focus on a comprehensive set of atomic facial muscle movements for human expression understanding. Based on supervised learning, discriminative AU representation can be achieved from local patches where the AUs are located. ...
BACKGROUND AND AIMS: Deep learning algorithms gained attention for detection (computer-aided detection [CADe]) of biliary tract cancer in digital single-operator cholangioscopy (dSOC). We developed a multimodal convolutional neural network (CNN) for ...
BACKGROUND: Mild cognitive impairment (MCI) is the transition stage between the cognitive decline expected in normal aging and more severe cognitive decline such as dementia. The early diagnosis of MCI plays an important role in human healthcare. Cur...
Advances in health sciences education : theory and practice
Sep 9, 2024
Health professional education stands to gain substantially from collective efforts toward building video databases of skill performances in both real and simulated settings. An accessible resource of videos that demonstrate an array of performances -...
OpenPose-based motion analysis (OpenPose-MA), utilizing deep learning methods, has emerged as a compelling technique for estimating human motion. It addresses the drawbacks associated with conventional three-dimensional motion analysis (3D-MA) and hu...
Uncovering the relationships between neural circuits, behavior, and neural dysfunction may require rodent pose tracking. While open-source toolkits such as DeepLabCut have revolutionized markerless pose estimation using deep neural networks, the trai...
Facial expression recognition(FER) is a hot topic in computer vision, especially as deep learning based methods are gaining traction in this field. However, traditional convolutional neural networks (CNN) ignore the relative position relationship of ...
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