Advances in Nano Research

Volume 20, Number 6, 2026, pages 847-868

DOI: 10.12989/anr.2026.20.6.847

Modelling and prediction of food rheological behaviour in human esophagus channel with and without dysphagia effect: A machine learning approach

Ankit Pal , Sriharsha Mishra , Soumyashree Nayak , Naveen Kumar Akkasali , Gaurav Kumar , Rama Chandra Pradhan , Ashish Kumar Meher , Subrata Kumar Panda

Abstract

The esophagus, a vital component of the digestive system, plays a pivotal role in ensuring the seamless passage of food from the mouth to the stomach. Its optimal functioning is imperative for our daily well-being, and any impairment can lead to significant complications, particularly in the form of dysphagia. This research addresses the pressing need for tailored dietary interventions for individuals grappling with dysphagia by leveraging insights gained from the analysis of two distinct types of esophageal model: one representative of a healthy state and the other simulating diseased conditions like no peristalsis and narrowing down near the lower esophageal sphincter (LES). Our study focuses on analyzing some distinct food items that are frequently given to patients and determining the optimal order for the food items based on how easily they pass through the esophagus to alleviate the challenges faced by dysphagia patients. A sensitive analysis has also been carried out to identify the specific property of the food items more susceptible to the variations in the desired output value, specifically wall shear stress for patients with and without dysphagia.

Key Words

dysphagia; lower esophageal sphincter; peristalsis; sensitive analysis

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