The impact of enterprise digital transformation on employee health management: A study of physiological responses from biomechanics perspective

This paper discusses the impact of enterprise digital transformation on employee health management from the perspective of biomechanics, especially the change law of employee physiological response and the underlying mechanism under the new work mode and technology application. By introducing a theoretical framework of biomechanics, this study evaluates the specific impact of changes such as office automation, remote work and the use of smart devices on the physical load of employees, and uses computer modeling technology to predict the potential health risks under different working conditions. In this study, a hybrid model combining Probabilistic neural Network (PNN) and Gated Recurrent Unit (GRU) was used to deal with complex time-series data analysis tasks to improve the prediction accuracy of employee health status. Experimental results show that the proposed PNN-GRU model performs well in the task of health state recognition, especially in fatigue and pain detection, with the accuracy of 94.7% and 97.1% respectively, which is significantly better than other algorithms.