Swallowscope: A smartphone based device for the assessment of swallowing ability

Abstract

Dysphagia can cause serious challenges to both physical and mental health. Aspiration due to dysphagia is a major health risk that could cause pneumonia, and even death. As a result, monitoring and managing dysphagia is of utmost importance. This study investigates the development of a smartphone-based device and a feasible real-time swallowing sound processing algorithm for the automatic screening for swallowing ability.The videofluoroscopic swallow study (VFSS), which is considered the gold standard for the diagnosis of dysphagia, is not widely available, expensive and causes exposure to radiation. The screening tests used for dysphagia need to be carried out by trained staff and the evaluations are often nonquantifiable. The Swallowscope we developed is a wearable device based on mobile health, and uses the swallowing sound to quantitatively evaluate swallowing ability. As swallowing sound can be captured continuously and during activities of daily life with minimal intervention, it is an ideal approach to monitor swallowing activities, and its continuous monitoring has a better probability of capturing aspirations and risky swallow patterns.This paper describes the real-time smartphone based algorithm and the application we developed to monitor swallowing activities and evaluates the recognition accuracy by comparing them with VFSS evidence.

AI-based Detection of Aspiration for Video-endoscopy with Visual Aids in Meaningful Frames to Interpret the Model Outcome

“…Therefore, the final explanation provided by the system is effective and acceptable. This goes beyond most existing approaches for this task (except the VFSS approach [25]), since they only provide predictions or classifications without providing proper interpretable information for the diagnostician [28,35,37,42,43,62,63]. Since this lack of transparency conflicts with EU GDPR, as it prohibits decision solely based on automated processing [44,64], a subsequent FEES or VFSS would become necessary anyway before critical decisions like abstinence from food, insertion of a nasogastric tube, or even re-intubation and tracheotomy could be made.…”

“…In general, detection of (impaired) swallowing based on auscultation is the subject of research in many studies [33][34][35]. Furthermore, there are studies investigating the combination of pressure build-up (lingual/palatal/pharyngeal) in combination with AI [36,37], sometimes additionally with the combination of VFSS data [38]; again, promising results can be obtained [39]. Combinations of various biometric data are also used for AI-based dysphagia diagnosis [40].…”

Smartphone-Based Real-time Assessment of Swallowing Ability From the Swallowing Sound

“…In the current stage where we focused more on the RSST and command swallows of 3 ml of water, we wanted to increase the recall: the true positive rate, to make sure the Swallowscope’s categorisation of not risky could be accepted with high confidence. Algorithm provided in this paper has 2 improvements over our previously proposed algorithm in [19] : (a) the number of sections in RSST and water use 2 different values because in RSST some sound components are not always audible due to dry nature of the swallows and (b) we introduced zero crossing detection for the better elimination of speech components. These enhancements have resulted in good detection rates for both water and dry swallows.…”

“…The Swallowscope, which is illustrated in the Fig. 1 , is the wearable device that we introduced earlier for the convenient monitoring of swallowing activities at bedside or during activities of daily life [19] . It is based on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$m$ \end{document} Health and uses the swallowing sound to evaluate swallowing ability in realtime.…”

Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review (Preprint)

“…This used an AI program on a mobile application and the sound of the user's swallowing [19]. The invention can prevent the deterioration of diseases and provide subsequent data to the doctor after medical intervention.…”