High-Discrimination Multi-level Electrotactile Feedback via Compound Perception Descriptors and Efficient Calibration

Existing electrotactile systems face challenges in reliably distinguishing multiple levels using a single channel. This limitation reduces their practicality in real-world applications. This study introduces a new framework to address these challenges. Four predefined levels were designed using compound perception descriptors based on intensity, frequency, and sensation quality. Each level ensures at least two distinct perceptual dimensions. Additionally, a rapid calibration method was developed, combining preset parameters with a GUI-guided adjustment process. Furthermore, subjective evaluations were conducted to assess urgency, annoyance, valence, and arousal for the four levels, providing insights for application-specific designs. The calibration process was efficient, with an average completion time of 7.2 min. Final tests demonstrated a classification accuracy of 96.1%, confirming the system’s ability to reliably distinguish the four levels. This framework provides a simple and effective solution for single-channel multi-level electrotactile feedback. The approach has potential applications in medical devices, virtual reality systems, and other human-computer interaction fields.