Smart Health Assistant for Dysphagia and Stroke: A Novel Machine Learning-Infused Solution
##plugins.themes.bootstrap3.article.sidebar##
Download : 33 times
##plugins.themes.bootstrap3.article.main##
Nami Susan Kurian
Kalaivani S
M. Jasmine Ananthi
S.Subhashini
G.Monika
Baby Shamini P
M.S.Sylvia Blossom
Abstract
There is a rise in health care solutions with the intervention of innovative technologies that helps to address critical health issues. This proposed smart health monitoring device represents a novel approach to mitigating the risks associated with dysphagia and stroke by utilizing machine learning techniques to analyze three crucial biological signals such as pressure on tongue, SPO2 (oxygen saturation) in blood and heart rate. One notable aspect of the device is its capacity to provide users with real-time health monitoring, offering them valuable empowerment. Patients can check their vital sign values at any location and time of the day. A predefined threshold value acts as a crucial benchmark, and if the measured output deviates from this baseline, an automatic alert is triggered. This alert signals a potential risk of stroke, prompting immediate attention. In the event of a threshold breach, the device initiates communication with healthcare providers. An automated message is sent to the hospital, ensuring that medical professionals are promptly informed about the patient's critical health condition. The data analysis is carried over the machine learning algorithm for the accurate results.
##plugins.themes.bootstrap3.article.details##

This work is licensed under a Creative Commons Attribution 4.0 International License.