This invention discloses a real-time monitoring method for gynecological patients based on
edge computing. To address the difficulties in real-time quantification of
vaginal bleeding and
lochia, and the increased cumulative error caused by interference from factors such as weighing vibrations,
humidity saturation, light shifts, and
occlusion, this invention collects the weight,
humidity, and surface
color data of the absorbent carrier within a preset update cycle, collects environmental parameter data, and reads the absorbent
carrier material parameter data to generate multimodal features. Based on these multimodal features, quality indicators are calculated, and a
quality assessment model generates
modal weight coefficients. In a lightweight temporal
Transformer network, the cross-
modal attention weights are gated and scaled according to these weight coefficients to obtain an aligned multimodal temporal representation. This representation is input into a physical constraint regression model, which outputs and updates the incremental volume of liquid entering the absorbent carrier, the incremental volume of
evaporation, and the volume retained within the absorbent carrier. The cumulative bleeding volume is calculated and accumulated under
mass conservation constraints, non-negativity constraints, and upper limit constraints on
absorption capacity. Furthermore, online calibration of fast-loop calibration and slow-loop update is performed in conjunction with the monitoring results, and parameters are reset during pad replacement events. This achieves real-time, stable, and robust quantitative monitoring of bleeding volume at the edge, while reducing long-term cumulative errors.