Motion Recognition for Forearm Using EMG Frequency Distribution.

EMG-based wrist gesture recognition using a convolutional neural network

Background: Deep learning has revolutionized artificial intelligence and has transformed many fields. It allows processing high-dimensional data (such as signals or images) without the need for feature engineering. The aim of this research is to develop a deep learning-based system to decode motor intent from electromyogram (EMG) signals. Methods: A myoelectric system based on convolutional ne...

Recent Advances in EMG Pattern Recognition for Prosthetic Control

Speech recognition using EMG; mime speech recognition

The cellular phone offers significant benefits but causes several social problems. One such problem is phone use in places where people should not speak, such as trains and libraries. A communication style that would not require voiced speech has the potential to solve this problem. Speech recognition based on electromyography (EMG), which we call "Mime Speech Recognition" is proposed. It not o...

Application of Quaternion Neural Network to EMG-Based Estimation of Forearm Motion

This paper presents the Application of Quaternion Neural Network (QNN) to Electromyography (EMG) based Estimation of Forearm Motion. Motion of human body can be modeled as a set of rotations in three-dimensional space by various joints. The aim of this research is to show the efficiency of QNN in estimation from EMG. We are trying to learn, estimate and simulate combined motion using QNN as wel...

A Novel Pedestrian Dead Reckoning Solution Using Motion Recognition Algorithm with Wearable EMG Sensors

Navigation applications and location-based services are currently becoming standard features in smart phones with built-in GPS receivers. However, a ubiquitous navigation solution which locates a mobile user anytime anywhere is still not available, especially in Global Navigation Satellite System (GNSS) degraded and denied environments. Different motion sensors and angular sensors have been ado...