Wearable Soft Ionic Tactile Controller for Virtual Reality: Decoupling Normal and Shear Forces without Motion Artifacts.

When soft wearable electronic devices are deployed on the body, body motion-induced artifacts pose a major challenge for accurately decoupling concurrent stimuli such as normal, shear forces, and elongational strain. This study introduces an ion-based multimodal sensor architecture augmented by machine learning algorithms to effectively differentiate the stimuli and compensate for motion-induced signal artifacts. By integrating a tailored sensor design with advanced algorithmic processing, the sensor reliably detects intentional forces across a broad range (normal force = 1.5-4 N, and 21 discrete shearing positions), while suppressing interference caused by skin strain. We fabricated a customized wireless wrist-mounted device to control the presentation screen in virtual reality conference. This approach maintains a high accuracy of 98.6%, even under 10% tensile strain applied to the wrist. The resulting robust, real-time force sensing capability is critical for wearable VR/AR controllers and other human-machine interfaces that demand precise interaction unaffected by motion artifacts.