Objective This study proposes a fatigue detection method for police extreme training based on electrical impedance imaging technology to prevent muscle damage caused by overstrain during intense physical training.Methods First, based on the mechanism of human anaerobic exercise, lactic acid was identified as a key indicator of muscle fatigue, demonstrating that measuring muscle lactic acid effectively reflects localized fatigue. Second, a numerical simulation model of the human calf was established, and the internal tissue structure of the calf was analyzed to determine the stages of lactic acid diffusion and change. Then, the reconstruction performance of electrical impedance tomography (EIT) in visualizing lactic acid diffusion was compared under three different regularization algorithms, and the most suitable regularization method for subsequent experiments was selected. Finally, a controlled experiment simulating lactate diffusion was conducted to verify the imaging capability of the TK-Noser regularization algorithm in complex imaging fields.Results Simulation results indicate that both the TK-Noser and TV regularization algorithms achieve superior imaging performance, effectively suppressing artifacts in the visualization of lactic acid diffusion inside muscle tissue. The average ICC/RMSE values reached 0.754/0.303 and 0.772/0.320, respectively, while the average SSIM/PSNR values were 0.677/61 dB and 0.488/60 dB, respectively. In the lactate diffusion experiment, the average ICC/SSIM of the EIT reconstruction results based on the TK-Noser regularization algorithm reached 0.701 and 0.572, respectively. Additionally, compared with the TV regularization algorithm, the TK-Noser algorithm better preserved the shape and structural integrity of the imaging target, with an SSIM value 21.2% higher than that of the TV regularization results. This enhancement ensures the stability of the experimental results and significantly improves the capability of electrical impedance imaging technology in monitoring lactate diffusion within complex fields.Conclusion The proposed method offers real-time convenience and non-invasiveness, making it a promising approach for dynamic monitoring of muscle lactate levels in police officers during extreme physical training.