Real Time Spatiotemporal Biological Stress Level Checking

We are going to investigate and design a healthcare navigation system that consists of sensor devices for human's vital sign, a mobile terminal for transferring the vital data to the cloud, and a cloud computing environment for intelligential processing of the vital data. In this paper, we pres...

Full description

Saved in:
Bibliographic Details
Published inProceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA) p. 1
Main Authors Uchimura, Marina, Eguchi, Yuki, Kawasaki, Minami, Yoshii, Naoko, Umeda, Tomohiro, Takata, Masami, Joe, Kazuki
Format Conference Proceeding
LanguageEnglish
Published Athens The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp) 01.01.2012
Online AccessGet full text

Cover

Loading…
More Information
Summary:We are going to investigate and design a healthcare navigation system that consists of sensor devices for human's vital sign, a mobile terminal for transferring the vital data to the cloud, and a cloud computing environment for intelligential processing of the vital data. In this paper, we present a tool for the mobile terminal, i.e. a smartphone, which displays user's biological stress levels. Although the tool is a part of our healthcare navigation system, it does not require the computation resource of the cloud because the stress levels, LF/HF, are enough computable on the processor of the current smartphone in real time. LF/HF is an index of sympathetic nervous activity calculated with the heart rate data obtained from heartbeat sensors. The LF/HF values are displayed in a form of bar graph at user's current location on the Google map of the smartphone. The location information is easily obtained from the GPS of the smartphone. Using the tool, the user can see his/her current stress levels as bar graph on the Google map in real-time. Namely, the tool provides users with their spatiotemporal biological stress levels in real time. [PUBLICATION ABSTRACT]