Rehabilitation assistive technology transfer in the AI era: network dynamics and public health impacts in the Yangtze River Delta, China

Against the backdrop of rapid global advances in artificial intelligence (AI), growing concerns surrounding public health and stressful environmental conditions, this study examines the Yangtze River Delta (YRD) of China by using social network analysis, a geographical detector model, and a coupling coordination model to investigate the spatiotemporal evolution and factors associated with rehabilitation assistive technology transfer networks before and after the COVID-19 pandemic (2016-2023). The results reveal that the YRD's technology transfer network has continued to expand, transforming from a "single-center" structure dominated by Shanghai to a "multicenter" network jointly anchored by Shanghai, Hangzhou, and Suzhou. The results of the coupling coordination analysis indicate that the synergistic relationship between public health systems and technology transfer networks improved during the pandemic. In contrast, the synergistic potential of AI technology innovation has yet to be fully unleashed. The geographical detector results show that economic development, technological innovation, and financial development are the core drivers of technology transfer. Moreover, interactions between public health or AI inventive capacity and other determinants exhibit pronounced "bifactor enhancement" effects. This study offers a new perspective on the sustainable development of the rehabilitation assistive devices industry within the context of AI integration and environmental pressures.