AIMC Topic: Gestures

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A Multimodal Multilevel Converged Attention Network for Hand Gesture Recognition With Hybrid sEMG and A-Mode Ultrasound Sensing.

IEEE transactions on cybernetics
Gesture recognition based on surface electromyography (sEMG) has been widely used in the field of human-machine interaction (HMI). However, sEMG has limitations, such as low signal-to-noise ratio and insensitivity to fine finger movements, so we cons...

Novel Wearable HD-EMG Sensor With Shift-Robust Gesture Recognition Using Deep Learning.

IEEE transactions on biomedical circuits and systems
In this work, we present a hardware-software solution to improve the robustness of hand gesture recognition to confounding factors in myoelectric control. The solution includes a novel, full-circumference, flexible, 64-channel high-density electromyo...

Joint Reconfiguration after Failure for Performing Emblematic Gestures in Humanoid Receptionist Robot.

Sensors (Basel, Switzerland)
This study proposed a strategy for a quick fault recovery response when an actuator failure problem occurred while a humanoid robot with 7-DOF anthropomorphic arms was performing a task with upper body motion. The objective of this study was to devel...

Deep Learning Technology to Recognize American Sign Language Alphabet.

Sensors (Basel, Switzerland)
Historically, individuals with hearing impairments have faced neglect, lacking the necessary tools to facilitate effective communication. However, advancements in modern technology have paved the way for the development of various tools and software ...

A Unified Multimodal Interface for the RELAX High-Payload Collaborative Robot.

Sensors (Basel, Switzerland)
This manuscript introduces a mobile cobot equipped with a custom-designed high payload arm called RELAX combined with a novel unified multimodal interface that facilitates Human-Robot Collaboration (HRC) tasks requiring high-level interaction forces ...

A Novel Event-Driven Spiking Convolutional Neural Network for Electromyography Pattern Recognition.

IEEE transactions on bio-medical engineering
Electromyography (EMG) pattern recognition is an important technology for prosthesis control and human-computer interaction etc. However, the practical application of EMG pattern recognition is hampered by poor accuracy and robustness due to electrod...

Transformer-based hand gesture recognition from instantaneous to fused neural decomposition of high-density EMG signals.

Scientific reports
Designing efficient and labor-saving prosthetic hands requires powerful hand gesture recognition algorithms that can achieve high accuracy with limited complexity and latency. In this context, the paper proposes a Compact Transformer-based Hand Gestu...

Liquid Metal Flexible EMG Gel Electrodes for Gesture Recognition.

Biosensors
Gesture recognition has been playing an increasingly important role in the field of intelligent control and human-computer interaction. Gesture recognition technology based on electromyography (EMG) with high accuracy has been widely applied. However...

Enhancing Human-Robot Collaboration through a Multi-Module Interaction Framework with Sensor Fusion: Object Recognition, Verbal Communication, User of Interest Detection, Gesture and Gaze Recognition.

Sensors (Basel, Switzerland)
With the increasing presence of robots in our daily lives, it is crucial to design interaction interfaces that are natural, easy to use and meaningful for robotic tasks. This is important not only to enhance the user experience but also to increase t...

Improving the Accuracy of Spiking Neural Networks for Radar Gesture Recognition Through Preprocessing.

IEEE transactions on neural networks and learning systems
Event-based neural networks are currently being explored as efficient solutions for performing AI tasks at the extreme edge. To fully exploit their potential, event-based neural networks coupled to adequate preprocessing must be investigated. Within ...