AIMC Topic: Hand
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Reply to the article "A Quality and Readability Comparison of Artificial Intelligence and Popular Health Website Education Materials for Common Hand Surgery Procedures".
Hand surgery & rehabilitation
Jul 4, 2024
Hybrid Brain-Computer Interface Controlled Soft Robotic Glove for Stroke Rehabilitation.
IEEE journal of biomedical and health informatics
Jul 2, 2024
Soft robotic glove controlled by a brain-computer interface (BCI) have demonstrated effectiveness in hand rehabilitation for stroke patients. Current systems rely on static visual representations for patients to perform motor imagination (MI) tasks, ...
Adaptive Multi-Dimensional Weighted Network With Category-Aware Contrastive Learning for Fine-Grained Hand Bone Segmentation.
IEEE journal of biomedical and health informatics
Jul 2, 2024
Accurately delineating and categorizing individual hand bones in 3D ultrasound (US) is a promising technology for precise digital diagnostic analysis. However, this is a challenging task due to the inherent imaging limitations of the US and the insig...
Deep Learning for hand tracking in Parkinson's Disease video-based assessment: Current and future perspectives.
Artificial intelligence in medicine
Jun 17, 2024
BACKGROUND: Parkinson's Disease (PD) demands early diagnosis and frequent assessment of symptoms. In particular, analysing hand movements is pivotal to understand disease progression. Advancements in hand tracking using Deep Learning (DL) allow for t...
Deep learning-based classification of erosion, synovitis and osteitis in hand MRI of patients with inflammatory arthritis.
RMD open
Jun 17, 2024
OBJECTIVES: To train, test and validate the performance of a convolutional neural network (CNN)-based approach for the automated assessment of bone erosions, osteitis and synovitis in hand MRI of patients with inflammatory arthritis.
Post-stroke hand gesture recognition via one-shot transfer learning using prototypical networks.
Journal of neuroengineering and rehabilitation
Jun 12, 2024
BACKGROUND: In-home rehabilitation systems are a promising, potential alternative to conventional therapy for stroke survivors. Unfortunately, physiological differences between participants and sensor displacement in wearable sensors pose a significa...
Deep learning classification of EEG-based BCI monitoring of the attempted arm and hand movements.
Biomedizinische Technik. Biomedical engineering
Jun 4, 2024
OBJECTIVES: The primary objective of this research is to improve the average classification performance for specific movements in patients with cervical spinal cord injury (SCI).
Dual Stream Long Short-Term Memory Feature Fusion Classifier for Surface Electromyography Gesture Recognition.
Sensors (Basel, Switzerland)
Jun 4, 2024
Gesture recognition using electromyography (EMG) signals has prevailed recently in the field of human-computer interactions for controlling intelligent prosthetics. Currently, machine learning and deep learning are the two most commonly employed meth...
Task-Oriented Training by a Personalized Electromyography-Driven Soft Robotic Hand in Chronic Stroke: A Randomized Controlled Trial.
Neurorehabilitation and neural repair
May 29, 2024
BACKGROUND: Intensive task-oriented training has shown promise in enhancing distal motor function among patients with chronic stroke. A personalized electromyography (EMG)-driven soft robotic hand was developed to assist task-oriented object-manipula...
Evaluating initial usability of a hand augmentation device across a large and diverse sample.
Science robotics
May 29, 2024
The advancement of motor augmentation and the broader domain of human-machine interaction rely on a seamless integration with users' physical and cognitive capabilities. These considerations may markedly fluctuate among individuals on the basis of th...
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