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<p>For management of chronic respiratory diseases, unobtrusive longitudinal monitoring of cough has been proposed. Such a monitoring system was developed using a classifier trained on an initial observation period. After this initial period, a personalized system is available being optimized for the patient and the particular acoustic environment. Long-term deployment of the system requires that the extracted features and learned model characterizing the coughs (and its environment) are time-invariant. This is studied by an example using annotation of two largely different epochs. The results suggest that time-invariance of the cough sound is sufficiently guaranteed for practical deployment, but that changing acoustic environmental conditions may be a factor to reckon with. Cues for detecting changing situations are discussed.</p>

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Classification for long-term monitoring of cough

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月12日

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  • Albertus C. den Brinker,
  • Ronald Rietman,
  • Okke Ouweltjes,
  • Matthijs van Marion,
  • Susannah Thackray-Nocera,
  • Michael G. Crooks,
  • Alyn H. Morice

摘要

For management of chronic respiratory diseases, unobtrusive longitudinal monitoring of cough has been proposed. Such a monitoring system was developed using a classifier trained on an initial observation period. After this initial period, a personalized system is available being optimized for the patient and the particular acoustic environment. Long-term deployment of the system requires that the extracted features and learned model characterizing the coughs (and its environment) are time-invariant. This is studied by an example using annotation of two largely different epochs. The results suggest that time-invariance of the cough sound is sufficiently guaranteed for practical deployment, but that changing acoustic environmental conditions may be a factor to reckon with. Cues for detecting changing situations are discussed.