This study aims to provide an in-depth understanding of assistive technology (AT) research development by investigating relationships between related keywords and concepts and uncovering how trends change over time. This study employed network analysis to identify the relationships between frequently cited papers and keywords in the AT literature and concept-linking analysis to uncover the key concepts and classifies them into clusters determining the changing trends in AT research. The network analysis results on author keywords co-occurrence and citation indicate that the development trend of AT is primarily observed in medicine and is related to medical devices used in rehabilitation or available for disabled and people for well-being improvement. Meanwhile, the concept linking analysis identifies seven groups of key AT concepts, including technical issues, education, health and disability, policy, user/people, and ways/medium. We also depict the yearly changes of the key concepts in AT research development. This research extracts the strongest key concepts, the most productive authors and countries, and the connecting relationship between authors and literature within the big data. It provides a comprehensive view of temporal patterns of AT developments and their development in terms of human–computer interactions.