The human hand is often viewed as the pinnacle of dexterity, and many robotic hands adopt anthropomorphic designs, while others pursue non-anthropomorphic forms for structural balance or task optimization. However, human-like asymmetry and reliance o...
BACKGROUND: Autism spectrum disorder (ASD) is a prevalent neurodevelopmental condition that can be quite difficult to diagnose due to a lack of objective diagnostic methods in the currently used behavioral assessments. Recent work has shown that chil...
Bionic hands can replicate many movements of the human hand, but our ability to intuitively control these bionic hands is limited. Humans' manual dexterity is partly due to control loops driven by sensory feedback. Here, we describe the integration o...
Bone age assessment and adult height prediction are essential for evaluating pediatric growth. Traditional methods rely on manual radiographic interpretation, which is subjective, time-consuming, and prone to inter-observer variability. This study pr...
Real-time and accurate hand gesture detection is essential for safe and intuitive Human-Robot Interaction (HRI), enabling robots to interpret non-verbal cues and respond appropriately in dynamic environments. This research evaluates the effectiveness...
In this paper, we propose a novel neural network architecture, the convolutional spider neural network (CS-Net), combined with a transfer learning (TL) strategy, to classify hybrid gestures that integrate wrist postures and hand movements.The CS-Net ...
In recent years, Hand Gesture Recognition (HGR) devices have been designed to recognize gestures in real time using machine-learning classifiers (MLCs). However, the performance of these classifiers heavily relies on the tuning of their hyperparamete...
International journal of neural systems
Oct 18, 2025
Decoding electroencephalographic (EEG) signals is of key importance in the development of brain-computer interface (BCI) systems. However, high inter-subject variability in EEG signals requires user-specific calibration, which can be time-consuming a...
The increasing adoption of prosthetic devices in medical applications introduces complex and variable load conditions, particularly due to the diverse nature of user disabilities. To address the resulting control challenges, this paper proposes a nov...
Surface electromyography (EMG) provides a non-invasive human-machine interaction interface that can promote the coherence of human-machine interaction operations. Decomposing surface electromyographic signals into hand joint angles in real time can b...
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