Abstract
The application of cervical auscultation in dysphagia: a bibliometric analysis
  
DOI:10.3870/zgkf.2026.04.007
EN KeyWords: cervical auscultation  dysphagia  acoustics  visualization analysis  bibliometrics
Fund Project:中国博士后科学基金面上资助计划(2025M772153)
作者单位
孙莹 1.昆山市康复医院康复科,江苏苏州215313 
杨扬 2.山东大学附属山东省立第三医院康复科一病区 
施加加 1.昆山市康复医院康复科,江苏苏州215313 
鲁德志 3.上海交通大学医学院附属第九人民医院 
张萍萍 4.上海中医药大研究生院 
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PDF Download Counts: 79
EN Abstract:
  Objective: To analyze the current research status and emerging trends in the application of cervical auscultation for dysphagia.Methods: Relevant literature published between 1965 and 2024 was retrieved from the Web of Science Core Collection. Bibliometric and visual analyses of publication year, journals, authors, institutions, countries, and keywords were performed using VOSviewer and CiteSpace. Results: A total of 213 articles were included in the final analysis. The annual number of publications demonstrated a steady upward trend, with an average annual growth rate of 11.13%. Overall, 92 academic journals published research related to cervical auscultation, with primary research areas concentrated in medicine and engineering. Dysphagia was identified as the core journal in this field, and its number of publications (NP) reached 41, with 1,484 total citations (TC), an h-index of 19, a g-index of 29, and an m-index of 0.70. The United States accounted for more than half of the total global publications (51.64%) and exhibited the highest total citations (TC=1,143) and h-index (h-index=21), indicating substantial academic influence. Globally, 300 institutions contributed to research on cervical auscultation, among which the University of Pittsburgh ranked first (NP=74, TC=795, h-index=17, g-index=22, m-index=2.83). A total of 668 authors published related studies. Sejdic E, Coyle JL, Steele CM, and Chau T collectively accumulated more than 500 total citations, with Sejdic E demonstrating notable academic impact (h-index=19, g-index=27, m-index=1.19). In keyword analysis, "biomechanical measurement" appeared earliest, "automatic separation" emerged relatively later, while "machine learning" and "deep learning" appeared most recently, reflecting evolving research priorities. Conclusion: Global research interest in cervical auscultation continues to increase. Current studies mainly focus on the processing and analysis of acoustic signal characteristics, and with the integration of artificial intelligence-based methodologies, this field is entering a new stage of development.
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