AIMC Topic: Gestures

Clear Filters Showing 21 to 30 of 264 articles

Self-Healing Triboelectric Sensors with Enhanced Durability for Gesture Recognition and Human-Machine Interaction.

Nano letters
The emergence of triboelectric nanogenerators (TENGs) has significantly developed the landscape of wearable electronics. However, the durability and self-healing capabilities of TENGs remain challenging. Herein, a self-healing triboelectric nanogener...

Gesture recognition for hearing impaired people using an ensemble of deep learning models with improving beluga whale optimization-based hyperparameter tuning.

Scientific reports
Sign language (SL) is the linguistics of speech and hearing-impaired individuals. The hand gesture is the primary model employed in SL by speech and hearing-challenged people to talk with themselves and ordinary persons. At present, hand gesture dete...

Recognizing American Sign Language gestures efficiently and accurately using a hybrid transformer model.

Scientific reports
Gesture recognition plays a vital role in computer vision, especially for interpreting sign language and enabling human-computer interaction. Many existing methods struggle with challenges like heavy computational demands, difficulty in understanding...

A strategy based on paraconsistent random forest for sEMG gesture recognition systems robust to contaminated data.

Computers in biology and medicine
Applying machine learning algorithms to physical signals is always challenging since undesirable events can occur when signals are acquired outside a controlled environment. Among several applications, movement recognition through sEMG signals is esp...

ASLDetect: Arabic sign language detection using ResNet and U-Net like component.

Scientific reports
Sign languages are essential for communication among over 430 million deaf and hard-of-hearing individuals worldwide. However, recognizing Arabic Sign Language (ArSL) in real-world settings remains challenging due to issues like background noise, lig...

A Robust Cross-Platform Solution With the Sense2Quit System to Enhance Smoking Gesture Recognition: Model Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Smoking is a leading cause of preventable death, and people with HIV have higher smoking rates and are more likely to experience smoking-related health issues. The Sense2Quit study introduces innovative advancements in smoking cessation t...

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...

The art of chimpanzee (Pan troglodytes) diplomacy: Unraveling the secrets of successful negotiations using machine learning.

Journal of comparative psychology (Washington, D.C. : 1983)
Social negotiation is crucial in human interactions and often involves clear communication, strong socialization skills, adept problem-solving abilities, and strategic planning. Chimpanzees exhibit evidence of social negotiation through manual gestur...

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 ...

Understanding Robot Gesture Perception in Children with Autism Spectrum Disorder during Human-Robot Interaction.

International journal of neural systems
Social robots are increasingly being used in therapeutic contexts, especially as a complement in the therapy of children with Autism Spectrum Disorder (ASD). Because of this, the aim of this study is to understand how children with ASD perceive and i...