scholarly journals The Association of High Resolution Cervical Auscultation Signal Features With Hyoid Bone Displacement During Swallowing

2019 ◽  
Vol 27 (9) ◽  
pp. 1810-1816 ◽  
Author(s):  
Qifan He ◽  
Subashan Perera ◽  
Yassin Khalifa ◽  
Zhenwei Zhang ◽  
Amanda S. Mahoney ◽  
...  
Keyword(s):  
High Resolution ◽  
Hyoid Bone ◽  
Cervical Auscultation ◽  
Signal Features

scholarly journals Characterizing Swallows From People With Neurodegenerative Diseases Using High-Resolution Cervical Auscultation Signals and Temporal and Spatial Swallow Kinematic Measurements

2021 ◽  
pp. 1-16
Author(s):  
Cara Donohue ◽  
Yassin Khalifa ◽  
Shitong Mao ◽  
Subashan Perera ◽  
Ervin Sejdić ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Neurodegenerative Diseases ◽  
Learning Algorithms ◽  
Healthy Adults ◽  
Machine Learning Algorithms ◽  
Cervical Auscultation ◽  
Laryngeal Vestibule ◽  
Temporal And Spatial ◽  
Kinematic Measures

Purpose The prevalence of dysphagia in patients with neurodegenerative diseases (ND) is alarmingly high and frequently results in morbidity and accelerated mortality due to subsequent adverse events (e.g., aspiration pneumonia). Swallowing in patients with ND should be continuously monitored due to the progressive disease nature. Access to instrumental swallow evaluations can be challenging, and limited studies have quantified changes in temporal/spatial swallow kinematic measures in patients with ND. High-resolution cervical auscultation (HRCA), a dysphagia screening method, has accurately differentiated between safe and unsafe swallows, identified swallow kinematic events (e.g., laryngeal vestibule closure [LVC]), and classified swallows between healthy adults and patients with ND. This study aimed to (a) compare temporal/spatial swallow kinematic measures between patients with ND and healthy adults and (b) investigate HRCA's ability to annotate swallow kinematic events in patients with ND. We hypothesized there would be significant differences in temporal/spatial swallow measurements between groups and that HRCA would accurately annotate swallow kinematic events in patients with ND. Method Participants underwent videofluoroscopic swallowing studies with concurrent HRCA. We used linear mixed models to compare temporal/spatial swallow measurements ( n = 170 ND patient swallows, n = 171 healthy adult swallows) and deep learning machine-learning algorithms to annotate specific temporal and spatial kinematic events in swallows from patients with ND. Results Differences ( p < .05) were found between groups for several temporal and spatial swallow kinematic measures. HRCA signal features were used as input to machine-learning algorithms and annotated upper esophageal sphincter (UES) opening, UES closure, LVC, laryngeal vestibule reopening, and hyoid bone displacement with 66.25%, 85%, 68.18%, 70.45%, and 44.6% accuracy, respectively, compared to human judges' measurements. Conclusion This study demonstrates HRCA's potential in characterizing swallow function in patients with ND and other patient populations.

scholarly journals High-Resolution Cervical Auscultation and Data Science: New Tools to Address an Old Problem

2020 ◽  
Vol 29 (2S) ◽  
pp. 992-1000 ◽  
Author(s):  
James L. Coyle ◽  
Ervin Sejdić
Keyword(s):  
High Resolution ◽  
Data Science ◽  
Wearable Sensors ◽  
Cervical Auscultation ◽  
Imaging Data ◽  
Swallowing Function ◽  
Clinical Method ◽  
Technological Advances ◽  
Electrical Engineers ◽  
Wearable Electronic

High-resolution cervical auscultation (HRCA) is an evolving clinical method for noninvasive screening of dysphagia that relies on data science, machine learning, and wearable sensors to investigate the characteristics of disordered swallowing function in people with dysphagia. HRCA has shown promising results in categorizing normal and disordered swallowing (i.e., screening) independent of human input, identifying a variety of swallowing physiological events as accurately as trained human judges. The system has been developed through a collaboration of data scientists, computer–electrical engineers, and speech-language pathologists. Its potential to automate dysphagia screening and contribute to evaluation lies in its noninvasive nature (wearable electronic sensors) and its growing ability to accurately replicate human judgments of swallowing data typically formed on the basis of videofluoroscopic imaging data. Potential contributions of HRCA when videofluoroscopic swallowing study may be unavailable, undesired, or not feasible for many patients in various settings are discussed, along with the development and capabilities of HRCA. The use of technological advances and wearable devices can extend the dysphagia clinician's reach and reinforce top-of-license practice for patients with swallowing disorders.

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