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

doi:10.1109/IMBIOC.2019.8777806

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

University of Glasgow
Queen Mary University of London
United Arab Emirates University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

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 language	English
Title of host publication	IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538673959
DOIs	https://doi.org/10.1109/IMBIOC.2019.8777806
State	Published - May 2019
Externally published	Yes
Event	2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019 - Nanjing, China Duration: 6 May 2019 → 8 May 2019

Publication series

Name	IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings

Conference

Conference	2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019
Country/Territory	China
City	Nanjing
Period	6/05/19 → 8/05/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

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

Access to Document

10.1109/IMBIOC.2019.8777806

Cite this

Rizwan, A., Zoha, A., Alomainy, A., Ali, N. A., Imran, M. A., & Abbasi, Q. H. (2019). Skin Conductance as Proxy for the Identification of Hydration Level in Human Body. In IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings Article 8777806 (IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IMBIOC.2019.8777806

Rizwan, A. ; Zoha, A. ; Alomainy, A. et al. / Skin Conductance as Proxy for the Identification of Hydration Level in Human Body. IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings).

@inproceedings{880ce2b3bb2c484b958eb0bb79373a99,

title = "Skin Conductance as Proxy for the Identification of Hydration Level in Human Body",

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.",

keywords = "Bio-Sensors Data, Classification, EDA, GSR, Hydration Level, Machine Learning, SCL, SCR",

author = "A. Rizwan and A. Zoha and A. Alomainy and Ali, \{N. A.\} and Imran, \{M. A.\} and Abbasi, \{Q. H.\}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019 ; Conference date: 06-05-2019 Through 08-05-2019",

year = "2019",

month = may,

doi = "10.1109/IMBIOC.2019.8777806",

language = "English",

series = "IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings",

address = "United States",

}

Rizwan, A, Zoha, A, Alomainy, A, Ali, NA, Imran, MA & Abbasi, QH 2019, Skin Conductance as Proxy for the Identification of Hydration Level in Human Body. in IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings., 8777806, IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019, Nanjing, China, 6/05/19. https://doi.org/10.1109/IMBIOC.2019.8777806

Skin Conductance as Proxy for the Identification of Hydration Level in Human Body. / Rizwan, A.; Zoha, A.; Alomainy, A. et al.
IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8777806 (IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Skin Conductance as Proxy for the Identification of Hydration Level in Human Body

AU - Rizwan, A.

AU - Zoha, A.

AU - Alomainy, A.

AU - Ali, N. A.

AU - Imran, M. A.

AU - Abbasi, Q. H.

PY - 2019/5

Y1 - 2019/5

N2 - 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.

AB - 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.

KW - Bio-Sensors Data

KW - Classification

KW - EDA

KW - GSR

KW - Hydration Level

KW - Machine Learning

KW - SCL

KW - SCR

UR - https://www.scopus.com/pages/publications/85070489244

U2 - 10.1109/IMBIOC.2019.8777806

DO - 10.1109/IMBIOC.2019.8777806

M3 - Conference contribution

AN - SCOPUS:85070489244

T3 - IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings

BT - IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2019

Y2 - 6 May 2019 through 8 May 2019

ER -

Rizwan A, Zoha A, Alomainy A, Ali NA, Imran MA, Abbasi QH. Skin Conductance as Proxy for the Identification of Hydration Level in Human Body. In IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8777806. (IEEE MTT-S 2019 International Microwave Biomedical Conference, IMBioC 2019 - Proceedings). doi: 10.1109/IMBIOC.2019.8777806

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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