Currently, research on gesture recognition systems has been on the rise due to the
capabilities these systems provide to the field of human–machine interaction, however …

In recent years, hand gesture recognition (HGR) technologies that use electromyography
(EMG) signals have been of considerable interest in developing human–machine interfaces …

Inertial Measurement Units (IMUs) are small, low-cost sensors that can measure
accelerations and angular velocities, making them valuable tools for a variety of …

We present IMU2CLIP, a novel pre-training approach to align Inertial Measurement Unit
(IMU) motion sensor recordings with video and text, by projecting them into the joint …

Hand gesture recognition systems (HGR) based on electromyography signals (EMGs) and
inertial measurement unit signals (IMUs) have been studied for different applications in …

Currently, sEMG-based pattern recognition is a crucial and promising control method for
prosthetic limbs. A 1D convolutional recurrent neural network classification model for …

This article introduces a novel approach for building a robust Automatic Gesture Recognition
system based on Surface Electromyographic (sEMG) signals, acquired at the forearm level …

Wearable surface electromyography (sEMG) signal-acquisition devices have considerable
potential for medical applications. Signals obtained from sEMG armbands can be used to …

We present IMU2CLIP, a novel pre-training approach to align Inertial Measurement Unit
(IMU) motion sensor recordings with text and video, by projecting them into the joint …

Abstract Human Activity Recognition (HAR) plays a crucial role in various applications (eg,
medical treatment, video surveillance and sports monitoring). Transfer learning is a …