ArticleJournal of medical systems2018
Blood Sugar Level Indication Through Chewing and Swallowing from Acoustic MEMS Sensor and Deep Learning Algorithm for Diabetic Management.
Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 81 citations in OpenAlex.
- Thought on Food: A Systematic Review of Current Approaches and Challenges for Food Intake Detection.Sensors (Basel, Switzerland) · 2022Pooled it
- A fully integrated, standalone stretchable device platform with in-sensor adaptive machine learning for rehabilitation.Nature communications · 2023Article
- Mechano-acoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch.Nature biomedical engineering · 2020Article
- Silicon-Based Sensors for Biomedical Applications: A Review.Sensors (Basel, Switzerland) · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetes, a metabolic disorder due to high blood glycemic index in the human body. The glycemic index varies in the human of improper diet and eating pattern such as junk foods, variation in the quantity of food, swallowing of food without chewing and stress. However, the diagnose of increase or decrease in the glycemic index is a challenging task. Similarly, the regulation of glycemic index without regular exercise is a major problem in day to day life. In this paper, we propose a novel SCS method to regulate glycemic index without exercise through changing the eating method. The proposed SCS eating method consists of Size of the food, Chewing style and Swallow time (SCS) of the food to regulate glycemic index. Furthermore, the proposed SCS method evaluate and validate through the acoustic signal acquired and processed with deep learning algorithm to analyze the chewing pattern of food to formulate a standard procedure for eating style and to reduce the glycemic level. The validation of diabetes done by measurement of blood glycemic through AccuChek Instant S Glucometer. Furthermore, the SCS method of eating style from 50 diabetes persons reduces the blood glucose level drastically by 85% after following the proposed method of eating style.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.