Multimodal Wearable Sensor System for Continuous Peripheral Circulation Monitoring in Postoperative Flap Care

Postoperative monitoring of transplanted flaps is critical, as undetected vascular compromise can rapidly lead to flap necrosis and devastating clinical outcomes. Timely detection and particularly differentiation of arterial and venous occlusion are key to improving flap survival. However, current clinical practice relies largely on intermittent, experience-dependent assessments, which cannot provide continuous and objective evaluation of flap perfusion. Here, we report a multimodal wearable sensor that enables continuous monitoring of complementary physiological signals reflecting blood perfusion, body fluid volume accumulation, and microvascular thermal response in postoperative flap management. Using a gradual arterial and venous occlusion rabbit flap model, the system is validated for continuous capture of physiologically relevant vascular changes. Through multimodal feature fusion and machine-learning modeling, it enables reliable differentiation between arterial and venous crises, as well as quantitative assessment of occlusion severity. This multimodal wearable sensing platform supports continuous and automated evaluation of postoperative flap status and could offer a scalable strategy for peripheral circulation assessment in postoperative monitoring.