Noninvasive Wearable Device for Monitoring and Assisting Asthma Patients

Abstract

Asthma is a chronic condition that affects the air passages in the lungs, causing symptoms such as cough, wheeze, shortness of breath, and chest tightness, which can be triggered by various factors including viral infections, dust, smoke, pollen, and soaps. It can affect patients’ daily lives in many harsh, debilitating ways, severe cases can lead to emergency health care, hospitalization, and even death. Although asthma can’t be cured, good management with inhaled medications can control the disease and enable people with asthma to lead a normal, active life. One of the ways in which asthma management becomes easier is the prediction of severity of asthma exacerbations in a patient. This model utilizes sensors and data collected from IoT devices and smartphones to predict asthma risk and severity. The model is trained on a dataset of asthma patients and takes into account various factors such as symptoms, triggers, and objective test results. The model is integrated with a non-invasive wearable device through bluetooth. The device itself adopts the latest IoT technologies to collect data about the patient’s whereabouts, their triggers as well as the condition of their disease. As the wearable device collects information from the sensor, this data is stored in the web application, where it can be compared to the previously collected readings to predict the severity of the asthma patient. The web application provides an interface between the patient and the data collected for prediction. This system significantly benefits asthma patients by providing a way to manage their condition better.