How closely do machine ratings of duration of UES opening during videofluoroscopy approximate clinician ratings using temporal kinematic analyses and the MBSImP?
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Summary
High resolution cervical auscultation (HRCA) is a non-invasive, sensor-based dysphagia screening method that uses signal processing and machine learning to characterize swallowing and evidence is provided of HRCA’s feasibility in detecting DUESO without VF images.
- Type
- article
- Published
- 2020-09-21
- Cited by
- 25
- References
- 56
- Access
- Open access
- OpenAlex
- https://openalex.org/W3087576084
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:221805449
Keywords
Swallowing, Dysphagia, Kinematics, Support vector machine, Medicine
References
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- The association of high resolution cervical auscultation signal features with hyoid bone displacement during swallowing
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- Upper esophageal sphincter
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- Discrete-Time Signal Pro-cessing
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- A Comparative Analysis of DBSCAN, K-Means, and Quadratic Variation Algorithms for Automatic Identification of Swallows from Swallowing Accelerometry Signals
- Videofluoroscopic predictors of aspiration in patients with oropharyngeal dysphagia
- Voice-quality Abnormalities as a Sign of Dysphagia: Validation against Acoustic and Videofluoroscopic Data
- Physiological Factors Related to Aspiration Risk: A Systematic Review
- Perception of wet vocal quality in identifying penetration/aspiration during swallowing.
- Effects of the Mendelsohn Maneuver on Extent of Hyoid Movement and UES Opening Post-Stroke
- Validation of the Yale Swallow Protocol: A Prospective Double-Blinded Videofluoroscopic Study
- Functional anatomy and physiology of the upper esophageal sphincter.
- Test-retest variability in normal swallowing
- Upper Esophageal Sphincter Opening During Swallow in Stroke Survivors
- Kinematic and temporal factors associated with penetration-aspiration in liquid swallowing
- The Effect of Voluntary Pharyngeal Swallowing Maneuvers on Esophageal Swallowing Physiology
Cited by
- Tracking Hyoid Bone Displacement During Swallowing Without Videofluoroscopy Using Machine Learning of Vibratory Signals
- High-Resolution Cervical Auscultation and Data Science: New Tools to Address an Old Problem.
- A preliminary investigation of whether HRCA signals can differentiate between swallows from healthy people and swallows from people with neurodegenerative diseases
- A Review of Hidden Markov Models and Recurrent Neural Networks for Event Detection and Localization in Biomedical Signals
- On the robustness of high-resolution cervical auscultation-based detection of upper esophageal sphincter opening duration in diverse populations
- Establishing reference values for temporal kinematic swallow events across the lifespan in healthy community dwelling adults using high-resolution cervical auscultation
- Characterizing Swallows From People With Neurodegenerative Diseases Using High-Resolution Cervical Auscultation Signals and Temporal and Spatial Swallow Kinematic Measurements.
- Characterizing Effortful Swallows from Healthy Community Dwelling Adults Across the Lifespan Using High-Resolution Cervical Auscultation Signals and MBSImP Scores: A Preliminary Study
- A Preliminary Investigation of Similarities of High Resolution Cervical Auscultation Signals Between Thin Liquid Barium and Water Swallows
- Temporal Sequence of Laryngeal Vestibule Closure and Reopening is Associated with Airway Protection
- Autonomous swallow segment extraction using deep learning in neck-sensor vibratory signals from patients with dysphagia
- Analysis of electrophysiological and mechanical dimensions of swallowing by non-invasive biosignals
- Non-Invasive Sensor-Based Estimation of Anterior-Posterior Upper Esophageal Sphincter Opening Maximal Distension
- Factors Influencing Laryngeal Vestibular Closure in Healthy Adults.
- Towards a comprehensive bedside swallow screening protocol using cross-domain transformation and high-resolution cervical auscultation
- Dysphagia screening with sEMG, accelerometry and speech: Multimodal machine and deep learning approaches
- A Machine Learning Pipeline for Automated Bolus Segmentation and Area Measurement in Swallowing Videofluoroscopy Images of an Infant Pig Model
- Enhancing the assessment of deglutition function in preterm infants with mechano-acoustic analysis and machine learning: a narrative review
- Assessing the Performance and Reliability of Deep Learning Autosegmentation in Videofluoroscopic Swallowing Studies: A Systematic Review and Meta-analysis.
- AIM in Otolaryngology and Head & Neck Surgery
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