AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Gestures

Showing 1 to 10 of 232 articles

Clear Filters

Eye-gesture control of computer systems via artificial intelligence.

F1000Research
BACKGROUND: Artificial Intelligence (AI) offers transformative potential for human-computer interaction, particularly through eye-gesture recognition, enabling intuitive control for users and accessibility for individuals with physical impairments.

Flexible hybrid self-powered piezo-triboelectric nanogenerator based on BTO-PVDF/PDMS nanocomposites for human machine interaction.

Scientific reports
As flexible and wearable electronics play more and more important role in smart watches, smart glass and virtual reality, and the power supply to the wearable electronics have been revealed more attentions for long-term usage and continuous healthy m...

Using Gesture and Speech to Control Surgical Lighting Systems: Mixed Methods Study.

JMIR human factors
BACKGROUND: Surgical lighting systems (SLSs) provide optimal lighting conditions for operating room personnel. Current systems are mainly adjusted by hand; surgeons either accommodate the light themselves or communicate their requirements to an assis...

EMGCipher: Decoding Electromyography for Upper-limb Gesture Classification with Explainable AI for Resource Optimization.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Assistive limb devices often employ surface electromyography (sEMG) and deep learning (DL) models for gesture classification. While DL models effectively classify diverse upper-limb gestures, their decision-making mechanisms often lack transparency. ...

A Graph Neural Network Model for Real-Time Gesture Recognition Based on sEMG Signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
For seemless control of advanced hand prostheses and augmented reality, accurate and immediate hand gestures recognition is essential. Surface electromyography (sEMG) signals obtained from the forearm are commonly employed for this purpose. In this p...

Gesture Recognition Achieved by Utilizing LoRa Signals and Deep Learning.

Sensors (Basel, Switzerland)
This study proposes a novel gesture recognition system based on LoRa technology, integrating advanced signal preprocessing, adaptive segmentation algorithms, and an improved SS-ResNet50 deep learning model. Through the combination of residual learnin...

Real-Time sEMG Processing With Spiking Neural Networks on a Low-Power 5K-LUT FPGA.

IEEE transactions on biomedical circuits and systems
The accurate modeling of hand movement based on the analysis of surface electromyographic (sEMG) signals offers exciting opportunities for the development of complex prosthetic devices and human-machine interfaces, moving from discrete gesture recogn...

Real-Time American Sign Language Interpretation Using Deep Learning and Keypoint Tracking.

Sensors (Basel, Switzerland)
Communication barriers pose significant challenges for the Deaf and Hard-of-Hearing (DHH) community, limiting their access to essential services, social interactions, and professional opportunities. To bridge this gap, assistive technologies leveragi...

Innovative hand pose based sign language recognition using hybrid metaheuristic optimization algorithms with deep learning model for hearing impaired persons.

Scientific reports
Sign language (SL) is an effective mode of communication, which uses visual-physical methods like hand signals, expressions, and body actions to communicate between the difficulty of hearing and the deaf community, produce opinions, and carry signifi...

Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm.

Scientific reports
This study introduces an innovative method for gesture recognition in medical robotics, utilizing Capsule Neural Networks (CNNs) in conjunction with the Modified Spring Search Algorithm (MSSA). This approach achieves remarkable efficiency in gesture ...