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<p>Dysphagia presents a serious risk of aspiration that requires continuous monitoring. This study introduces standardized 2&#xa0;s voice segments for aspiration detection, derived from physiological constraints observed during clinical video-fluoroscopic swallowing study (VFSS) examinations. This prospective cohort study collected voice data from 198 participants aged ≥ 40 years. Of the 128 normal participants (healthy controls and VFSS-normal, penetration-aspiration scale (PAS) 1) and 70 with aspiration-risk (PAS ≥ 5) participants, the duration analysis revealed that the VFSS participants (overall mean: 2.22–2.48&#xa0;s) produced significantly shorter phonations than healthy controls (6.19 ± 1.70&#xa0;s) (<i>p</i> &lt; 0.001), which justified the 2&#xa0;s standardization. The aspiration-risk threshold was set at PAS ≥ 5 as material on the vocal cords significantly alters voice quality. Post-swallowing recordings were preprocessed into mel-spectrograms via short-time Fourier transform to extract time-frequency features. We developed three models based on MobileNetV3 (male, female, integrated) using the EfficientAT framework with 10-fold cross-validation. The integrated model demonstrated optimal performance with an area under the curve (AUC) of 0.8090 and 82.77% sensitivity. The male-specific model achieved an AUC of 0.7586 and 91.88% sensitivity, whereas the female model reached an AUC of 0.7376 and 61.11% sensitivity. This physiologically grounded approach shows promise for telemedicine-based aspiration screening.</p><p><b>Trial registration:</b> This study was approved by the institutional review board of Seoul National University Bundang Hospital (approval number B-2109-707-303) and registered in the ClinicalTrials.gov database (NCT05149976). </p>

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Post-swallowing voice-based aspiration screening in dysphagia using a deep learning approach: insights from audio segmentation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月21日

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  • Jung-Min Kim,
  • Min-Seop Kim,
  • Sun-Young Choi,
  • Hyun-Jin Kim,
  • Ju Seok Ryu

摘要

Dysphagia presents a serious risk of aspiration that requires continuous monitoring. This study introduces standardized 2 s voice segments for aspiration detection, derived from physiological constraints observed during clinical video-fluoroscopic swallowing study (VFSS) examinations. This prospective cohort study collected voice data from 198 participants aged ≥ 40 years. Of the 128 normal participants (healthy controls and VFSS-normal, penetration-aspiration scale (PAS) 1) and 70 with aspiration-risk (PAS ≥ 5) participants, the duration analysis revealed that the VFSS participants (overall mean: 2.22–2.48 s) produced significantly shorter phonations than healthy controls (6.19 ± 1.70 s) (p < 0.001), which justified the 2 s standardization. The aspiration-risk threshold was set at PAS ≥ 5 as material on the vocal cords significantly alters voice quality. Post-swallowing recordings were preprocessed into mel-spectrograms via short-time Fourier transform to extract time-frequency features. We developed three models based on MobileNetV3 (male, female, integrated) using the EfficientAT framework with 10-fold cross-validation. The integrated model demonstrated optimal performance with an area under the curve (AUC) of 0.8090 and 82.77% sensitivity. The male-specific model achieved an AUC of 0.7586 and 91.88% sensitivity, whereas the female model reached an AUC of 0.7376 and 61.11% sensitivity. This physiologically grounded approach shows promise for telemedicine-based aspiration screening.

Trial registration: This study was approved by the institutional review board of Seoul National University Bundang Hospital (approval number B-2109-707-303) and registered in the ClinicalTrials.gov database (NCT05149976).