Rocking chair adaptive rocking pacification method and system based on infant cry feature analysis
By combining sensor data fusion and multimodal feature learning with adaptive neural networks and collaborative learning to optimize rocker control, the problem of single perception dimension and insufficient analysis of multi-factor needs in existing baby rocker soothing technologies has been solved, achieving a personalized and intelligent rocker soothing effect.
Patent Information
- Application Number
- CN202610680479.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-18
- Publication Date
- 2026-07-17
AI Technical Summary
Existing baby rocker soothing technologies lack the ability to perceive and respond to the baby's real-time state and individual differences, making it difficult to accurately analyze the multi-factor needs and intentions behind complex cries. Furthermore, they lack a multi-drive unit collaborative optimization mechanism that considers environmental and positional variables, resulting in a mechanical and rigid soothing process with insufficient personalized adaptability and low comfort.
Data is collected by audio, posture and environmental sensors. The time-frequency and state features of crying are fused by a parallel residual network. Transfer learning and variational inference are used to generate demand feature vectors. Combined with hierarchical adaptive neural networks and dynamic programming algorithms, the parameters of the rocking soothing scene are optimized. The collaborative control of multiple driving units is achieved through a grouped collaborative learning network.
It achieves accurate identification of infants' needs and personalized feature modeling, dynamically generates optimal soothing scenarios, improves the adaptability and comfort of soothing strategies, increases the success rate and comfort of infant soothing, reduces the occurrence of excessive or ineffective soothing, and enhances the intelligence and responsiveness of the system.
Smart Images
Figure CN122411032A_ABST