Visualization Analysis of Research Status and Hotspots of Computerized Respiratory Sound Analysis Based on CiteSpace

  • Yan Wang Department of Respiratory and Critical Care Medicine, Beijing Jishuitan Hospital, Capital Medical University, Beijing 100035, China
  • Yu Xu Department of Respiratory and Critical Care Medicine, Beijing Jishuitan Hospital, Capital Medical University, Beijing 100035, China
  • Yali Fan Department of Respiratory and Critical Care Medicine, Beijing Jishuitan Hospital, Capital Medical University, Beijing 100035, China
  • Yang Zhang Department of Respiratory and Critical Care Medicine, Beijing Jishuitan Hospital, Capital Medical University, Beijing 100035, China
  • Zixuan Qi Department of Respiratory and Critical Care Medicine, Beijing Jishuitan Hospital, Capital Medical University, Beijing 100035, China
  • Yang Cheng Department of Respiratory and Critical Care Medicine, Beijing Jishuitan Hospital, Capital Medical University, Beijing 100035, China
Keywords: Respiratory sounds, Sound analysis, Computer, CiteSpace

Abstract

Objective: To explore the research landscape and hotspots of Computerized Respiratory Sound Analysis (CORSA) and provide a reference for future in-depth studies. Methods: Literature related to CORSA published up to August 27, 2020, was retrieved from the Web of Science Core Collection. CiteSpace 5.6.R3 was used to perform co-authorship analysis, institutional collaboration analysis, keyword co-occurrence analysis, and co-citation analysis. Results: A total of 1,897 publications were included. Co-authorship analysis identified several influential contributors, including Zahra Moussavi, Kenneth Sundaraj, and H. Pasterkamp. Major research institutions included the University of Manitoba, the University of Queensland, and Aristotle University of Thessaloniki. Keyword co-occurrence analysis indicated that “respiratory sound,” “lung sound,” “asthma,” “children,” and “classification” were major research themes. The most frequently co-cited articles were published by Arati Gurung (2011), Mohammed Bahoura (2009), and H. Pasterkamp (1997). Highly cited journals included Chest, the American Journal of Respiratory and Critical Care Medicine, and IEEE Transactions on Biomedical Engineering. Conclusion: CORSA research is primarily driven by European and North American scholars and institutions, with China still in an early stage of development. Current hotspots include respiratory sound acquisition and processing, feature extraction methods such as Mel-frequency cepstral coefficients (MFCCs), and classification techniques based on machine learning and deep learning. CORSA is suitable for diverse populations and is widely applied in respiratory diseases, especially bronchial asthma. Its non-invasive nature offers particular advantages for infants and pregnant women. Although CORSA demonstrates strong clinical potential, its clinical translation remains limited. Advancing clinical applications and bridging the gap between research and practice will be key directions for future development. The prominence of top-tier respiratory and engineering journals among citations suggests that CORSA is an emerging and influential research frontier.

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Published
2025-12-16