Evolution and trends in tremor diagnosis and differential diagnosis-a bibliometric study

Tremor is one of the most common motor symptom across movement disorders, and its precise diagnosis has become increasingly critical. However, existing studies remain fragmented. They often focus on specific disease manifestations or isolated diagnostic techniques, but lack systematic analysis. A comprehensive review is therefore needed to consolidate insights and guide future diagnostic advancements.

We systematically searched the Web of Science Core Collection (WoSCC) and ClinicalTrials.gov (January 2016-August 2025), identifying 1,145 publications and 47 trials. Bibliometric networks were then visualized and analyzed using CiteSpace, VOSviewer, and the R package "bibliometrix."

Annual publication volume increased steadily, while citations rose from 2016 and peaked in 2021. The United States led in publications, whereas Germany held the highest betweenness centrality. Yale University ranked first in publication output, and University College London had the greatest betweenness centrality. Louis, Elan D was the most influential author, leading in publication count, citation frequency, and betweenness centrality. Parkinsonism and Related Disorders was the most productive journal. Clinical trials predominantly focused on essential tremor (ET) and majorly employed device-based methodologies. Research centered on four themes including quantitative tremor assessment and digital health technologies, neurophysiological evaluation, neuroimaging, and pathophysiology and biomarkers, with machine learning (ML) and deep learning (DL) emerging as key frontiers.

This study comprehensively maps the research landscape in tremor diagnosis and differential diagnosis over the past decade. On this basis, it identifies current limitations, and predicts emerging research frontiers, thereby offering valuable insights and guidance for future scientific investigation.