AIMC Topic: Hand
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Identification of Spared and Proportionally Controllable Hand Motor Dimensions in Motor Complete Spinal Cord Injuries Using Latent Manifold Analysis.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 9, 2024
The loss of bilateral hand function is a debilitating challenge for millions of individuals that suffered a motor-complete spinal cord injury (SCI). We have recently demonstrated in eight tetraplegic individuals the presence of highly functional spar...
Deep Learning Detection of Hand Motion During Microvascular Anastomosis Simulations Performed by Expert Cerebrovascular Neurosurgeons.
World neurosurgery
Oct 5, 2024
OBJECTIVE: Deep learning enables precise hand tracking without the need for physical sensors, allowing for unsupervised quantitative evaluation of surgical motion and tasks. We quantitatively assessed the hand motions of experienced cerebrovascular n...
Rapid and noninvasive estimation of human arsenic exposure based on 4-photo-set of the hand and foot photos through artificial intelligence.
Journal of hazardous materials
Oct 2, 2024
Chronic exposure to arsenic is linked to the development of cancers in the skin, lungs, and bladder. Arsenic exposure manifests as variegated pigmentation and characteristic pitted keratosis on the hands and feet, which often precede the onset of int...
Enhancing stroke rehabilitation with whole-hand haptic rendering: development and clinical usability evaluation of a novel upper-limb rehabilitation device.
Journal of neuroengineering and rehabilitation
Sep 27, 2024
INTRODUCTION: There is currently a lack of easy-to-use and effective robotic devices for upper-limb rehabilitation after stroke. Importantly, most current systems lack the provision of somatosensory information that is congruent with the virtual trai...
Hand gesture recognition using sEMG signals with a multi-stream time-varying feature enhancement approach.
Scientific reports
Sep 27, 2024
Hand gesture recognition based on sparse multichannel surface electromyography (sEMG) still poses a significant challenge to deployment as a muscle-computer interface. Many researchers have been working to develop an sEMG-based hand gesture recogniti...
Machine Learning-Based Gesture Recognition Glove: Design and Implementation.
Sensors (Basel, Switzerland)
Sep 23, 2024
In the evolving field of human-computer interaction (HCI), gesture recognition has emerged as a critical focus, with smart gloves equipped with sensors playing one of the most important roles. Despite the significance of dynamic gesture recognition, ...
Effects of high-definition tDCS targeting individual motor hotspot with EMG-driven robotic hand training on upper extremity motor function: a pilot randomized controlled trial.
Journal of neuroengineering and rehabilitation
Sep 20, 2024
BACKGROUND: Delivering HD-tDCS on individual motor hotspot with optimal electric fields could overcome challenges of stroke heterogeneity, potentially facilitating neural activation and improving motor function for stroke survivors. However, the inte...
Decoupling visual and identity features for adversarial palm-vein image attack.
Neural networks : the official journal of the International Neural Network Society
Sep 19, 2024
Palm-vein has been widely used for biometric recognition due to its resistance to theft and forgery. However, with the emergence of adversarial attacks, most existing palm-vein recognition methods are vulnerable to adversarial image attacks, and to t...
Enhanced 2D Hand Pose Estimation for Gloved Medical Applications: A Preliminary Model.
Sensors (Basel, Switzerland)
Sep 17, 2024
(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...
Insights Into Detecting Adult ADHD Symptoms Through Advanced Dual-Stream Machine Learning.
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...
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