Real-time health monitoring via ECG analysis

In this paper we describe the range of use cases of medical wearable IoT devices for monitoring health state in real-time. We propose approaches for analysis the dynamic analogous but digitized electrocardiogram in combination with other personal data like age, gender, medical card and some sensors like GPS and accelerometer by neural network or some other machine learning method. It should be trained on classified dataset and then be adjusted for specific person to monitor and classify in real-time his or her health state whether he or she is healthy or if some abnormality detected. This paper is the declaration of our research and its development which is at the data gathering and preparation stage

Postural orthostatic tachycardia syndrome (POTS): An evaluation of daily barriers in the home environment

This study focuses on the relationship between Postural Orthostatic Tachycardia Syndrome (POTS) and the home environment. Since starting this study, numbers on how many people have POTS have risen from 2015 from an estimated 500,000 people in the United States to between 1 million to 3 million people (Caceres, 2022; Sheldon, 2015). While new research has been conducted on the impact of POTS on daily life, there is a lack of specific understanding of the experience of those living with the condition and the impact of the home environment. The purpose of this study was to identify how the home environment influences individuals living with POTS physiological and cognitive responses. The study also addresses how the inclusion of environmental adaptations affect those relationships. A mixed-methods exploratory methodology was used with two phases, which included a Phase I Survey and a Phase II Focus Group. Conclusions based on this paper were used to develop a fact sheet for the general public to better understand the experience of living with POTS at home