Surface EMG vs. High-Density EMG: Tradeoff Between Performance and Usability for Head Orientation Prediction in VR Application

Head orientation prediction is one of the solutions to reduce end-to-end latency on Virtual Reality (VR) systems and important since it can alleviate negative effects like motion sickness. This study compared head models from two different electromyography (EMG) systems: surface EMG (sEMG) High-Density (HD-EMG). The deep learning method was used train model, results showed that model with input pre-processed sEMG + IMU sensor outperformed HD-EMG sensor. However, decreasing performance compensated by its comfort ease use electrode. tradeoff between usability should be a consideration for users who want choose purposes. Comparison state-of-the-art methods proved sEMG-based offers better in predictions when change their directions, which quantified calculating dt peaks. In other words, our suitable VR applications, require user perform high-intensity or abrupt movements, such as FPS games exercise/sports games.