AIMC Topic: Deglutition

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Deep learning-based video analysis for automatically detecting penetration and aspiration in videofluoroscopic swallowing study.

Scientific reports
The videofluoroscopic swallowing study (VFSS) is the gold standard for diagnosing dysphagia, but its interpretation is time-consuming and requires expertise. This study developed a deep learning model for automatically detecting penetration and aspir...

Use of Transfer Learning for the Automated Segmentation and Detection of Swallows via Digital Cervical Auscultation in Children.

Dysphagia
Digital cervical auscultation (CA) has high diagnostic test accuracy in the detection of aspiration in children. However, the clinical application of digital CA is limited because swallow sound recordings require manual segmentation by trained expert...

A Machine Learning Pipeline for Automated Bolus Segmentation and Area Measurement in Swallowing Videofluoroscopy Images of an Infant Pig Model.

Dysphagia
Feeding efficiency and safety are often driven by bolus volume, which is one of the most common clinical measures of assessing swallow performance. However, manual measurement of bolus area is time-consuming and suffers from high levels of inter-rate...

Artificial Intelligence in Videofluoroscopy Swallow Study Analysis: A Comprehensive Review.

Dysphagia
Videofluoroscopic Swallowing Study (VFSS) is considered the gold standard for diagnosing swallowing disorders, or dysphagia. However, the interpretation of VFSS is susceptible to human bias and subjectivity, resulting in significant inter- and intra-...

Effect of artificial intelligence-based video-game system on dysphagia in patients with stroke: A randomized controlled trial.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND AND AIMS: Post-stroke dysphagia is highly prevalent and causes complication. While video games have demonstrated potential to increase patient engagement in rehabilitation, their efficacy in stroke patients with dysphagia remains unclear. ...

Comprehensive review of dysphagia and technological advances in dysphagia food.

Food research international (Ottawa, Ont.)
As the global population ages, dysphagia is becoming increasingly common among the elderly, posing serious risks such as choking, aspiration pneumonia, and even death. Leveraging advanced technologies to develop specialized food products for those wi...

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
Patients with nasogastric (NG) tubes require careful monitoring due to the potential impact of the tube on their ability to swallow safely. This study aimed to investigate the utility of high-resolution cervical auscultation (HRCA) signals in assessi...

Comparison of measurement of integrated relaxation pressure by esophageal manometry with analysis of swallowing sounds with artificial intelligence in patients with achalasia.

Neurogastroenterology and motility
BACKGROUND: Esophageal motility disorders are mainly evaluated with high-resolution manometry (HRM) which is a time-consuming and uncomfortable procedure with potential adverse events. Acoustic characterization of the swallowing has the potential to ...

A Pneumatic Flexible Linear Actuator Inspired by Snake Swallowing.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Soft robots spark a revolution in human-machine interaction. However, developing high-performance soft actuators remains challenging due to trade-offs among output force, driving distance, control precision, safety, and compliance. Here, addressing t...

Deep learning approach for dysphagia detection by syllable-based speech analysis with daily conversations.

Scientific reports
Dysphagia, a disorder affecting the ability to swallow, has a high prevalence among the older adults and can lead to serious health complications. Therefore, early detection of dysphagia is important. This study evaluated the effectiveness of a newly...