EMG-based Interactive Control Scheme for Stage Lighting

Abstract

Aiming at improving the low interactivity of conventional stage lighting control, a gesture-based interactive control scheme for stage lighting is proposed in this paper, which uses electromyogram (EMG) signals to recognize the performers’ gestures and converts them into control signals to transform the stage lighting effects subsequently. Gesture recognition, it involves the acquisition, preprocessing, feature extraction, and classification of the EMG signal. Considering the real-time performance and accuracy among the common algorithms such as support vector machine (SVM), k-nearest neighbor (KNN), linear discriminant analysis (LDA), backpropagation (BP) neural network, KNN is adopted as the classification tool. The lighting effect between gestures and stage lights is designed and realized to ensure that stage lighting interactively transforms with gesture changes. The experiment results show the feasibility and convenience of the proposed control scheme.