AIMC Topic: Hand
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Generative Artificial Intelligence Responses to Common Patient-Centric Hand and Wrist Surgery Questions: A Quality and Usability Analysis.
The journal of hand surgery Asian-Pacific volume
Jan 5, 2025
Due to the rapid evolution of generative artificial intelligence (AI) and its implications on patient education, there is a pressing need to evaluate AI responses to patients' medical questions. This study assessed the quality and usability of respo...
Highly Responsive Robotic Prosthetic Hand Control Considering Electrodynamic Delay.
Sensors (Basel, Switzerland)
Dec 27, 2024
As robots become increasingly integrated into human society, the importance of human-machine interfaces continues to grow. This study proposes a faster and more accurate control system for myoelectric prostheses by considering the Electromechanical D...
Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference.
mSphere
Dec 19, 2024
The human microbiome, the community of microorganisms that reside on and inside the human body, is critically important for health and disease. However, it is influenced by various factors and may vary among individuals residing in distinct geographi...
STCNet: Spatio-Temporal Cross Network with subject-aware contrastive learning for hand gesture recognition in surface EMG.
Computers in biology and medicine
Dec 13, 2024
This paper introduces the Spatio-Temporal Cross Network (STCNet), a novel deep learning architecture tailored for robust hand gesture recognition in surface electromyography (sEMG) across multiple subjects. We address the challenges associated with t...
In good hands: A case for improving robotic dexterity.
Science (New York, N.Y.)
Dec 12, 2024
Twenty-first-century roboticists envision robots capable of sorting objects and packaging them, of chopping vegetables and folding clothes. But although many today believe that the only factors necessary for robots to achieve dexterous manipulation a...
Classification algorithms trained on simple (symmetric) lifting data perform poorly in predicting hand loads during complex (free-dynamic) lifting tasks.
Applied ergonomics
Dec 10, 2024
The performance of machine learning (ML) algorithms is dependent on which dataset it has been trained on. While ML algorithms are increasingly used for lift risk assessment, many algorithms are often trained and tested on controlled simulation datase...
Learning a Hand Model From Dynamic Movements Using High-Density EMG and Convolutional Neural Networks.
IEEE transactions on bio-medical engineering
Nov 21, 2024
OBJECTIVE: Surface electromyography (sEMG) can sense the motor commands transmitted to the muscles. This work presents a deep learning method that can decode the electrophysiological activity of the forearm muscles into the movements of the human han...
Classification of hand movements from EEG using a FusionNet based LSTM network.
Journal of neural engineering
Nov 20, 2024
. Accurate classification of electroencephalogram (EEG) signals is crucial for advancing brain-computer interface (BCI) technology. However, current methods face significant challenges in classifying hand movement EEG signals, including effective spa...
Prediction and Elimination of Physiological Tremor During Control of Teleoperated Robot Based on Deep Learning.
Sensors (Basel, Switzerland)
Nov 18, 2024
Currently, teleoperated robots, with the operator's input, can fully perceive unknown factors in a complex environment and have strong environmental interaction and perception abilities. However, physiological tremors in the human hand can seriously ...
Improved Surface Electromyogram-Based Hand-Wrist Force Estimation Using Deep Neural Networks and Cross-Joint Transfer Learning.
Sensors (Basel, Switzerland)
Nov 15, 2024
Deep neural networks (DNNs) and transfer learning (TL) have been used to improve surface electromyogram (sEMG)-based force estimation. However, prior studies focused mostly on applying TL within one joint, which limits dataset size and diversity. Her...
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