The flow sensor and the pressure sensor are used in coordination to detect the blockage in the blood vessel

The early and accurate identification of vascular occlusions plays a crucial role in preventing cardiovascular and cerebrovascular diseases. Conventional detection methods that rely on single sensors often face challenges in terms of sensitivity and specificity. This study introduces a multimodal detection approach based on the cooperative functioning of flow sensors and pressure sensors. By simultaneously acquiring hemodynamic parameters and local pressure gradient variations within blood vessels, and employing an adaptive weighted fusion algorithm, both the spatial position and extent of obstruction can be quantitatively assessed. In vitro simulation experiments indicate that this collaborative detection method achieves a 92.3% accuracy rate for identifying small occlusions (diameter< 2mm), which represents a 27.6% improvement compared to single-flow detection. By constructing a dual-parameter feature map of blood flow and pressure, this technique successfully differentiates physiological stenosis from pathological embolism, enhancing detection sensitivity to 0.89 mmHg/(mL/s). This research offers a novel sensing strategy for vascular interventional diagnostic and therapeutic devices, demonstrating potential clinical value in real-time monitoring and early warning systems.