AIMC Topic: Fingers
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Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements.
Journal of neuroscience methods
Aug 14, 2024
BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing m...
Zero-Biased Bionic Fingertip E-Skin with Multimodal Tactile Perception and Artificial Intelligence for Augmented Touch Awareness.
Advanced materials (Deerfield Beach, Fla.)
Aug 11, 2024
Electronic skins (E-Skins) are crucial for future robotics and wearable devices to interact with and perceive the real world. Prior research faces challenges in achieving comprehensive tactile perception and versatile functionality while keeping syst...
DSFE: Decoding EEG-Based Finger Motor Imagery Using Feature-Dependent Frequency, Feature Fusion and Ensemble Learning.
IEEE journal of biomedical and health informatics
Aug 6, 2024
Accurate decoding finger motor imagery is essential for fine motor control using EEG signals. However, decoding finger motor imagery is particularly challenging compared with ordinary motor imagery. This paper proposed a novel EEG decoding method of ...
Glove-Net: Enhancing Grasp Classification with Multisensory Data and Deep Learning Approach.
Sensors (Basel, Switzerland)
Jul 5, 2024
Grasp classification is pivotal for understanding human interactions with objects, with wide-ranging applications in robotics, prosthetics, and rehabilitation. This study introduces a novel methodology utilizing a multisensory data glove to capture i...
Characterizing Disease Progression in Parkinson's Disease from Videos of the Finger Tapping Test.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 26, 2024
INTRODUCTION: Parkinson's disease (PD) is characterized by motor symptoms whose progression is typically assessed using clinical scales, namely the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Despite its reliabilit...
An optimized EEGNet decoder for decoding motor image of four class fingers flexion.
Brain research
Jun 12, 2024
As a cutting-edge technology of connecting biological brain and external devices, brain-computer interface (BCI) exhibits promising applications on extensive fields such as medical and military. As for the disable individuals with four limbs losing t...
Deep learning of Parkinson's movement from video, without human-defined measures.
Journal of the neurological sciences
Jun 10, 2024
BACKGROUND: The core clinical sign of Parkinson's disease (PD) is bradykinesia, for which a standard test is finger tapping: the clinician observes a person repetitively tap finger and thumb together. That requires an expert eye, a scarce resource, a...
Towards Efficient Neural Decoder for Dexterous Finger Force Predictions.
IEEE transactions on bio-medical engineering
May 20, 2024
OBJECTIVE: Dexterous control of robot hands requires a robust neural-machine interface capable of accurately decoding multiple finger movements. Existing studies primarily focus on single-finger movement or rely heavily on multi-finger data for decod...
Effect of task-oriented training assisted by force feedback hand rehabilitation robot on finger grasping function in stroke patients with hemiplegia: a randomised controlled trial.
Journal of neuroengineering and rehabilitation
May 14, 2024
BACKGROUND: Over 80% of patients with stroke experience finger grasping dysfunction, affecting independence in activities of daily living and quality of life. In routine training, task-oriented training is usually used for functional hand training, w...
Development of a Two-Finger Haptic Robotic Hand with Novel Stiffness Detection and Impedance Control.
Sensors (Basel, Switzerland)
Apr 18, 2024
Haptic hands and grippers, designed to enable skillful object manipulation, are pivotal for high-precision interaction with environments. These technologies are particularly vital in fields such as minimally invasive surgery, where they enhance surgi...
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