Skin Conductance as Proxy for the Identification of Hydration Level in Human Body

A. Rizwan, A. Zoha, A. Alomainy, N. A. Ali, M. A. Imran, Q. H. Abbasi

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

4 Citations (Scopus)

Abstract

The skin dehydration level can be used to infer serious health conditions in patients since diseases like cardiovascular abnormality, diabetes and cancer symptoms do exhibit correlation with skin disorders. Therefore a systematic analysis of human skin hydration levels is critical for multiple health care applications. Motivated by this, in this study we proposed a unique approach of measuring body hydration levels against different body postures using skin conductance electrical activity. In this paper, we report the collection, processing and analysis techniques used in the analysis of skin conductance data. Subsequently in order to predict body hydration levels we employed state-of-the-art machine learning models using the skin conductance data and achieved 81.82% and 73.91% recognition accuracy for the data of standing and sitting postures, respectively using KNN model.

Original languageEnglish
Title of host publicationIEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538673959
DOIs
Publication statusPublished - May 2019
Externally publishedYes
Event2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019 - Nanjing, China
Duration: May 6 2019May 8 2019

Publication series

NameIEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings

Conference

Conference2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019
Country/TerritoryChina
CityNanjing
Period5/6/195/8/19

Keywords

  • Bio-Sensors Data
  • Classification
  • EDA
  • GSR
  • Hydration Level
  • Machine Learning
  • SCL
  • SCR

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Health Informatics
  • Instrumentation
  • Human-Computer Interaction
  • Biomedical Engineering

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