Multi-scale bioimpedance flexible sensing with causal hierarchical machine learning for fish vitality evaluation under adversity stress

It is expected that waterless low-temperature stressful environments will induce stress responses in fish and affect their vitality. In this study, we developed a laser-activated, stretchable, highly conductive liquid metal (LM) based flexible sensor system for fish multi-scale bioimpedance detection. It has excellent conformability, electrical conductivity, bending and cyclic tensile stability. Meanwhile, test result showed that wireless power supply is a potential solution for realizing safe power supply for devices inside waterless low-temperature packages. In addition, a hierarchical regression model (GC-HRM) based on Granger causality was established. The result showed that tissue bioimpedance can induce changes in individual bioimpedance with unidirectional Granger causality. The R2 of the linear regression (LR), support vector regression (SVR) and artificial neural network (ANN) models under single-scale individual bioimpedance were 0.85, 0.90 and 0.78, respectively. By adding the multi-scale bioimpedance features, the R2 of the LR, SVR and ANN models were improved to 0.95, 1.00 and 0.98, respectively.