Machine Learning and Stress Assessment: A Review

Syed Faraz; Syed Saad Azhar Ali; Syed Hasan Adil

doi:10.1109/ICEEST.2018.8643313

Machine Learning and Stress Assessment: A Review

Syed Faraz, Syed Saad Azhar Ali, Syed Hasan Adil

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

6 Scopus citations

Abstract

Stress assessment has been considered essentials in the early stages because stress-related abnormalities tend to increase the risk of strokes, heart attacks, depression, and hypertension. This may also induce suicidal thought within the victims of this neurological state. The CAD (Computer Aided Diagnosis) have been a way forward for both medical experts and people with complications. The recent development of Machine learning revolution has proved to be substantial for medical diagnosis and prediction. This approach can further be used with neurological tools. The initial status of the brain activities would act as a window into the brain; which can be used as an insight. With the influence of machine learning more generalized way of discriminating stress activities with other normal activities can be possible.

Original language	English
Title of host publication	2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538682494
DOIs	https://doi.org/10.1109/ICEEST.2018.8643313
State	Published - 2 Jul 2018
Externally published	Yes

Publication series

Name	2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Machine Learning
Stress-Assessment

ASJC Scopus subject areas

General Engineering

UN SDGs

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

Access to Document

10.1109/ICEEST.2018.8643313

Cite this

Faraz, S., Ali, S. S. A., & Adil, S. H. (2018). Machine Learning and Stress Assessment: A Review. In 2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018 Article 8643313 (2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICEEST.2018.8643313

Faraz, Syed ; Ali, Syed Saad Azhar ; Adil, Syed Hasan. / Machine Learning and Stress Assessment : A Review. 2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018).

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month = jul,

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doi = "10.1109/ICEEST.2018.8643313",

language = "English",

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Faraz, S, Ali, SSA & Adil, SH 2018, Machine Learning and Stress Assessment: A Review. in 2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018., 8643313, 2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICEEST.2018.8643313

Machine Learning and Stress Assessment: A Review. / Faraz, Syed; Ali, Syed Saad Azhar; Adil, Syed Hasan.
2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8643313 (2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018).

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

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AB - Stress assessment has been considered essentials in the early stages because stress-related abnormalities tend to increase the risk of strokes, heart attacks, depression, and hypertension. This may also induce suicidal thought within the victims of this neurological state. The CAD (Computer Aided Diagnosis) have been a way forward for both medical experts and people with complications. The recent development of Machine learning revolution has proved to be substantial for medical diagnosis and prediction. This approach can further be used with neurological tools. The initial status of the brain activities would act as a window into the brain; which can be used as an insight. With the influence of machine learning more generalized way of discriminating stress activities with other normal activities can be possible.

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Faraz S, Ali SSA, Adil SH. Machine Learning and Stress Assessment: A Review. In 2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8643313. (2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology, ICEEST 2018). doi: 10.1109/ICEEST.2018.8643313

Machine Learning and Stress Assessment: A Review

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this