AIMC Topic: Hand

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Post-stroke hand gesture recognition via one-shot transfer learning using prototypical networks.

Journal of neuroengineering and rehabilitation
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
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)
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
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
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...

A quality and readability comparison of artificial intelligence and popular health website education materials for common hand surgery procedures.

Hand surgery & rehabilitation
INTRODUCTION: ChatGPT and its application in producing patient education materials for orthopedic hand disorders has not been extensively studied. This study evaluated the quality and readability of educational information pertaining to common hand s...

Vision-aided grasp classification: design and evaluation of compact CNN for prosthetic hands.

Biomedical physics & engineering express
Powered prosthetic hands capable of executing various grasp patterns are highly sought-after solutions for upper limb amputees. A crucial requirement for such prosthetic hands is the accurate identification of the intended grasp pattern and subsequen...

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
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...

Ηand dexterities assessment in stroke patients based on augmented reality and machine learning through a box and block test.

Scientific reports
A popular and widely suggested measure for assessing unilateral hand motor skills in stroke patients is the box and block test (BBT). Our study aimed to create an augmented reality enhanced version of the BBT (AR-BBT) and evaluate its correlation to ...