Extending touch-less interaction with smart glasses by implementing EMG module

Abstract

In this paper we propose to use temporal muscle contraction to perform certain actions. Method: The set of muscle contractions corresponding to one of three actions including “single-click”, “double-click” “click-n-hold” and “non-action” were recorded. After recording certain amount of signals, the set of five parameters was calculated. These parameters served as an input matrix for the neural network. Two-layer feedforward neural network with one hidden layer of 200 neurons was applied to classify gestures based on the input matrix. Results: The network was trained using the dataset consisted of 43 samples and then tested on the 34 samples dataset. All gestures from the test set were correctly classified.