ArticleArchives of physical medicine and rehabilitation2019
Detection of Swallow Kinematic Events From Acoustic High-Resolution Cervical Auscultation Signals in Patients With Stroke.
Article in Archives of physical medicine and rehabilitation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04468191 (Quantifying Fatigue of the Respiratory and Swallowing Musculature in Patients With Amyotrophic Lateral Sclerosis), which is not on this map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Quantifying Fatigue of the Respiratory and Swallowing Musculature in Patients With Amyotrophic Lateral Sclerosis
Who cites it
20 citing papers in PubMed.
- Using Machine Learning for the Automated Segmentation and Detection of Swallows Obtained by Digital Cervical Auscultation in Preterm Neonates.Dysphagia · 2026Article
- Conformal Swallowing Accelerometry: Reimagining the Acquisition and Characterization of Swallowing Mechano-Acoustic Signals.Sensors (Basel, Switzerland) · 2025Article
- Acoustic and Perceptual Profiles of Swallowing Sounds in Preterm Neonates: A Cross-Sectional Study Cohort.Dysphagia · 2025Article
- Elevating Patient Care With Deep Learning: High-Resolution Cervical Auscultation Signals for Swallowing Kinematic Analysis in Nasogastric Tube Patients.IEEE journal of translational engineering in health and medicine · 2024Article
- Autonomous Swallow Segment Extraction Using Deep Learning in Neck-Sensor Vibratory Signals From Patients With Dysphagia.IEEE journal of biomedical and health informatics · 2023Article
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- Improving Non-Invasive Aspiration Detection With Auxiliary Classifier Wasserstein Generative Adversarial Networks.IEEE journal of biomedical and health informatics · 2022Article
- Characterizing Swallows From People With Neurodegenerative Diseases Using High-Resolution Cervical Auscultation Signals and Temporal and Spatial Swallow Kinematic Measurements.Journal of speech, language, and hearing research : JSLHR · 2021Article
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- Article
- Tracking Hyoid Bone Displacement During Swallowing Without Videofluoroscopy Using Machine Learning of Vibratory Signals.Dysphagia · 2021Article
- Estimation of laryngeal closure duration during swallowing without invasive X-rays.Future generations computer systems : FGCS · 2021Article
- Upper Esophageal Sphincter Opening Segmentation With Convolutional Recurrent Neural Networks in High Resolution Cervical Auscultation.IEEE journal of biomedical and health informatics · 2021Article
- Automatic Estimation of Laryngeal Vestibule Closure Duration Using High- Resolution Cervical Auscultation Signals.Perspectives of the ASHA special interest groups · 2020Article
- The Long-Term Effects of COVID-19 on Dysphagia Evaluation and Treatment.Archives of physical medicine and rehabilitation · 2020Article
- High-Resolution Cervical Auscultation and Data Science: New Tools to Address an Old Problem.American journal of speech-language pathology · 2020Article
- The Association of High Resolution Cervical Auscultation Signal Features With Hyoid Bone Displacement During Swallowing.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2019Article
- High-Resolution Cervical Auscultation Signal Features Reflect Vertical and Horizontal Displacements of the Hyoid Bone During Swallowing.IEEE journal of translational engineering in health and medicine · 2019Article
- Advanced Machine Learning Tools to Monitor Biomarkers of Dysphagia: A Wearable Sensor Proof-of-Concept Study.Digital biomarkersArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objectiveTo examine whether there were any associations between high-resolution cervical auscultation (HRCA) acoustic signals recorded by a contact microphone and swallowing kinematic events during pharyngeal swallow as assessed by a videofluoroscopic (VF) examination.
designProspective pilot study.
settingUniversity teaching hospital, university research laboratories.
participantsPatients (N=35) with stroke who have suspected dysphagia (26 men + 9 women; age = 65.8±11.2).
methodsVF recordings of 100 liquid swallows from 35 stroke patients were analyzed, and a variety of HRCA signal features to characterize each swallow were calculated.
main outcome measuresPercent of signal feature maxima (peak) occurring within 0.1 seconds of swallow kinematic event identified from VF recording.
resultsMaxima of HRCA signal features, such as standard deviation, skewness, kurtosis, centroid frequency, bandwidth, and wave entropy, were associated with hyoid elevation, laryngeal vestibule closure, and upper esophageal sphincter opening, and the contact of the base of the tongue and posterior pharyngeal wall.
conclusionsAlthough the kinematic source of HRCA acoustic signals has yet to be fully elucidated, these results indicate a strong relationship between these HRCA signals and several swallow kinematic events. There is a potential for HRCA to be developed for diagnostic and rehabilitative clinical management of dysphagia.
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