AIMC Topic: Deglutition
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Effect of artificial intelligence-based video-game system on dysphagia in patients with stroke: A randomized controlled trial.
Clinical nutrition (Edinburgh, Scotland)
Dec 25, 2024
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.)
Nov 19, 2024
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
Nov 13, 2024
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
Oct 6, 2024
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)
Sep 12, 2024
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
Aug 31, 2024
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...
Identification of Respiratory Pauses during Swallowing by Unconstrained Measuring Using Millimeter Wave Radar.
Sensors (Basel, Switzerland)
Jun 9, 2024
Breathing temporarily pauses during swallowing, and the occurrence of inspiration before and after these pauses may increase the likelihood of aspiration, a serious health problem in older adults. Therefore, the automatic detection of these pauses wi...
Automatic Tracking of Hyoid Bone Displacement and Rotation Relative to Cervical Vertebrae in Videofluoroscopic Swallow Studies Using Deep Learning.
Journal of imaging informatics in medicine
Feb 21, 2024
The hyoid bone displacement and rotation are critical kinematic events of the swallowing process in the assessment of videofluoroscopic swallow studies (VFSS). However, the quantitative analysis of such events requires frame-by-frame manual annotatio...
Application of deep learning technology for temporal analysis of videofluoroscopic swallowing studies.
Scientific reports
Oct 16, 2023
Temporal parameters during swallowing are analyzed for objective and quantitative evaluation of videofluoroscopic swallowing studies (VFSS). Manual analysis by clinicians is time-consuming, complicated and prone to human error during interpretation; ...
Detection of aspiration from images of a videofluoroscopic swallowing study adopting deep learning.
Oral radiology
Feb 8, 2023
OBJECTIVES: A videofluoroscopic swallowing study (VFSS) is conducted to detect aspiration. However, aspiration occurs within a short time and is difficult to detect. If deep learning can detect aspirations with high accuracy, clinicians can focus on ...
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