Adult product user physiological state recognition method based on multi-sensor data acquisition
By using multi-sensor data acquisition and analysis technology, combined with muscle coordination pattern analysis and classification models, the problems of physiological signal contamination and insufficient specificity in adult products have been solved, achieving highly accurate and privacy-preserving physiological state recognition and enhancing the personalized interaction capabilities of the device.
Patent Information
- Application Number
- CN202610227477.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-02-26
- Publication Date
- 2026-06-02
AI Technical Summary
Existing technologies for adult products suffer from problems such as physiological signals being susceptible to motion artifacts, low signal-to-noise ratio, insufficient specificity, and privacy protection issues, making it impossible to accurately identify the user's physiological state in highly dynamic environments.
A multi-sensor data acquisition method was adopted, combining a multi-channel surface electromyography sensor array, an inertial measurement unit and a pressure sensor. Through dynamic analysis of muscle coordination patterns and non-negative matrix factorization, muscle coordinators and their activation coefficients were extracted to construct a personalized muscle coordinator library. A hierarchical hybrid classification model was then used to identify physiological states.
It achieves high robustness and high accuracy in recognizing users' physiological states in complex usage environments, enhances personalized needs and privacy protection, and ensures adaptive adjustment of device operating modes.