Paper Info
Title
Heart rate variability based stress index service model using bio-sensor
Abstract
As infinite competition and materialism have become severe in the current society, stress management has emerged as a main topic. There are many causes that create stress, including external factors and personal events. Also, stress has different levels, depending on an individuals’ subjective analysis. Stress has high correlations with cardiovascular disorders and mental illness. In particular, long-term stress leads to lowered immunity, which makes people more exposed to various diseases, and brings personal and social costs. With the rapid development of the IoT, it has been easy to analyze and manage stress with the use of sensors and communications technology relating to the human body and its surroundings. This study proposes a heart-rate variability-based stress index service using a biosensor. The proposed method collects a variety of information in dual physical environments (such as temperature, humidity, and brightness) from IoT devices, and analyzes it in real-time. The discomfort index and wind chill temperature index offered by the Korea Meteorological Administration, and the temperature, humidity, noise, and brightness collected from a biosensor are the most clear factors to digitize the physical environments of stress. Also, a smart health platform analyzes different heart rates depending on individual conditions, and monitors current status. For a heart rate, the frequency of the R-R value and low frequency (LF) are analyzed. For R-R value, a maximum value detection algorithm is applied. For LF analysis, Fourier transform is used. Generally, fast Fourier transform is unable to analyze the relation between time and frequency. Accordingly, applied is a short time Fourier transform in which window size is limited in a graph so as to express an effect made by changing time effectively. A stress index is comprised of discomfort level, wind chill temperature, noise, brightness, and heart rate. The notification of risk is given to the user by signal lights indicating stability, warning, or danger. The stress index service enables a user to check the stress index in real-time over a smart health platform at any place and at any time. Therefore, it serves as a tool to notify one’s acquaintances of a risk when one faces an emergent situation or is about to be at risk.
Year
DOI
Venue
2018
10.1007/s10586-017-0879-3
Cluster Computing
Keywords
Field
DocType
Heart rate, Stress index, Healthcare, Life behavior, Chronic diseases, Mobile application
Heart rate variability,Wind chill,Computer science,Stress management,Short-time Fourier transform,Fourier transform,Real-time computing,Fast Fourier transform,Service model,Brightness
Journal
Volume
Issue
ISSN
21
1
1573-7543
Citations 
PageRank 
References 
6
0.44
14
Authors
2
Name
Order
Citations
PageRank
Yoo Hyun1675.13
Kyung-Yong Chung2115480.87