Validation of automated 5 mL thin liquid swallowing sound segmentation for estimating audio-derived pharyngeal clearance time

This study evaluates the reliability of using automatically segmented audio events to detect pharyngeal swallowing activity by comparing their onset and offset timings with physiological event markers derived from videofluoroscopic swallowing studies (VFSS). Swallowing sounds were recorded from 45 patients with suspected dysphagia during VFSS using a neck-worn electronic stethoscope (NWES). A segmentation algorithm was used to detect the audio onset and offset of swallowing. These were compared to VFSS-annotated events: bolus contact with the epiglottis (P-Start), upper esophageal sphincter (UES) opening (E-Start), and UES closure (E-End). Timing offsets and duration measures were analysed, and subgroup comparisons were performed based on the presence or absence of oral containment. The algorithm detected 80 of 84 swallows. Audio onset occurred after P-Start in 96% of cases and after E-Start in 67.5%. Audio offset occurred after E-End in 82.5% of swallows. The mean audio-derived pharyngeal clearance time (PCT) was 706.5 ± 294.8 ms, closely aligned with the VFSS-based pharyngeal duration of 790.0 ± 310.0 ms. PCT did not differ significantly between swallows with and without oral containment, suggesting robustness against pre-pharyngeal activities. The findings confirm that audio-based segmentation reliably captures the pharyngeal phase and estimates durations that align with VFSS-derived physiological events, supporting its use in non-invasive, bedside screening for swallowing efficiency.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-03-03
DOI
https://doi.org/10.1038/s41598-026-39699-7
Citations
1
Primary Topic
Dysphagia Assessment and Management
Type
article
Field-Weighted Citation Impact
52.87

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Validation of automated 5 mL thin liquid swallowing sound segmentation for estimating audio-derived pharyngeal clearance time

Dushyantha Jayatilake, Koichiro Matsuo, Yohei Teramoto, Tomoyuki Ueno et al.
1 citations
Scientific Reports
Dysphagia Assessment and Management
52.87
article

Validation of automated 5 mL thin liquid swallowing sound segmentation for estimating audio-derived pharyngeal clearance time

Dushyantha Jayatilake, Koichiro Matsuo, Yohei Teramoto, Tomoyuki Ueno, Kenji Suzuki
article en
1 citations

Abstract

This study evaluates the reliability of using automatically segmented audio events to detect pharyngeal swallowing activity by comparing their onset and offset timings with physiological event markers derived from videofluoroscopic swallowing studies (VFSS). Swallowing sounds were recorded from 45 patients with suspected dysphagia during VFSS using a neck-worn electronic stethoscope (NWES). A segmentation algorithm was used to detect the audio onset and offset of swallowing. These were compared to VFSS-annotated events: bolus contact with the epiglottis (P-Start), upper esophageal sphincter (UES) opening (E-Start), and UES closure (E-End). Timing offsets and duration measures were analysed, and subgroup comparisons were performed based on the presence or absence of oral containment. The algorithm detected 80 of 84 swallows. Audio onset occurred after P-Start in 96% of cases and after E-Start in 67.5%. Audio offset occurred after E-End in 82.5% of swallows. The mean audio-derived pharyngeal clearance time (PCT) was 706.5 ± 294.8 ms, closely aligned with the VFSS-based pharyngeal duration of 790.0 ± 310.0 ms. PCT did not differ significantly between swallows with and without oral containment, suggesting robustness against pre-pharyngeal activities. The findings confirm that audio-based segmentation reliably captures the pharyngeal phase and estimates durations that align with VFSS-derived physiological events, supporting its use in non-invasive, bedside screening for swallowing efficiency.

Scientific Reports
University of Tsukuba (JP), Nippon Sheet Glass (Japan) (JP), University of Zurich (CH), Tokyo College of Welfare (JP), University of Tsukuba Hospital (JP)
Ministry of Health, Labour and Welfare
Openalex Percentile: Top 0%
Dysphagia Assessment and Management
52.87
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.