Robot control using electromyography (EMG) signals of the wrist

Artificial Neural Network to Detect Human Hand Gestures for a Robotic Arm Control

Assistive technology is critical to improving daily life of those with muscular issues such as Cerebral Palsy and Duchenne Muscular Dystrophy by augmenting their activities of daily living (ADL). Robotic manipulators are one solution for helping with ADL; however, intuitive, accurate interfaces for higher degrees of freedom (DOF) robotic arms are still lacking. An intuitive control system based on artificial neural network (ANN) classification of real-time surface electromyography (sEMG) signals from the user's forearm to detect nine hand gestures and control the movement of the 6 DOF robotic arm is proposed in this paper. The regular machine learning classifiers with the highest classification accuracies were ensemble-bagged trees at 90.3% and cubic SVM at 89.6%, with linear SVM being 84.8%. However, the classifier chosen was a scaled conjugate gradient backpropagation neural network model, with a classification accuracy of 85%, due to accuracy and usability in a Simulink model. The trained ANN model was incorporated into the control system for the robotic arm and tested in virtual environment. Preliminary testing of the robotic arm shows that the forward kinematic control system works well for most hand poses. Future improvements will include more processing of the sEMG signals and training on sEMG data from multiple subjects for a generalized ANN model.

Body ownership and agency altered by an electromyographically controlled robotic arm

Understanding how we consciously experience our bodies is a fundamental issue in cognitive neuroscience. Two fundamental components of this are the sense of body ownership (the experience of the body as one's own) and the sense of agency (the feeling of control over one's bodily actions). These constructs have been used to investigate the incorporation of prostheses. To date, however, no evidence has been provided showing whether representations of ownership and agency in amputees are altered when operating a robotic prosthesis. Here we investigated a robotic arm using myoelectric control, for which the user varied the joint position continuously, in a rubber hand illusion task. Fifteen able-bodied participants and three trans-radial amputees were instructed to contract their wrist flexors/extensors alternately, and to watch the robotic arm move. The sense of ownership in both groups was extended to the robotic arm when the wrists of the real and robotic arm were flexed/extended synchronously, with the effect being smaller when they moved in opposite directions. Both groups also experienced a sense of agency over the robotic arm. These results suggest that these experimental settings induced successful incorporation of the prosthesis, at least for the amputees who took part in the present study.