Validity of biosignal processing system based on haar transform in IoT application

Yoonsu Shin, Jongseo Lee, Songkuk Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In the Internet of Things (IoT) era, people are very interested in wearable devices such as smart watches. These devices measure individual physiological time series such as blood pressure, heart rate, and EEG. With this functionality, people can check the status of their own health. This healthcare service usually sends individual physiological time series to remote clusters for calculation. A remote healthcare service is particularly necessary for patients suffering from chronic and urgent diseases such as cardiovascular disease. It is also necessary to predict urgent signals for proper treatment. One method to predict urgent signals is by clustering physiological time series and comparing the new physiological time series with the previous time series in a cluster. It means searching the time series similar to risk features. In other words, the detection and comparison of features in time series are important. Therefore, in this study, we propose a biosignal processing system based on the Haar transform of time series in IoT applications. We discuss the validity of this system according to various perspectives. The Haar transform of a time series reflects the trend of the time series; thus, we can recognize the trend of the time series more easily. In addition, we can reduce the storage size of the time series. This is especially helpful because the volume of a time series is massive in the IoT era. Although the reduction of information in a time series can distort the similarity accuracy, it does not distort it significantly.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering, BIBE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages206-211
Number of pages6
ISBN (Electronic)9781538613245
DOIs
Publication statusPublished - 2017 Jul 1
Event17th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2017 - Herndon, United States
Duration: 2017 Oct 232017 Oct 25

Publication series

NameProceedings - 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering, BIBE 2017
Volume2018-January

Other

Other17th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2017
CountryUnited States
CityHerndon
Period17/10/2317/10/25

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Biomedical Engineering
  • Modelling and Simulation
  • Signal Processing
  • Health Informatics

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