Mental health and sensing

Abdul Kawsar Tushar; Ashad Kabir; Syed Ishtiaque Ahmed

doi:10.1007/978-3-030-54932-9_11

Mental health and sensing

Abdul Kawsar Tushar, Ashad Kabir, Syed Ishtiaque Ahmed

University of Toronto

Research output: Book chapter/Published conference paper › Chapter (peer-reviewed) › peer-review

4 Citations (Scopus)

Abstract

Mental health is a global epidemic, affecting close to half a billion people worldwide. Chronic shortage of resources hamper detection and recovery of affected people. Effective sensing technologies can help fight the epidemic through early detection, prediction, and resulting proper treatment. Existing and novel technologies for sensing mental health state could address the aforementioned concerns by activating granular tracking of physiological, behavioral, and social signals pertaining to problems in mental health. Our paper focuses on the available methods of sensing mental health problems through direct and indirect measures. We see how active and passive sensing by technologies as well as reporting from relevant sources can contribute toward these detection methods. We also see available methods of therapeutic treatment available through digital means. We highlight a few key intervention technologies that are being developed by researchers to fight against mental illness issues.

Original language	English
Title of host publication	Signal processing techniques for computational health informatics
Editors	Md Atiqur Rahman Ahad, Mosabber Uddin Ahmed
Place of Publication	Cham, Switzerland
Publisher	Springer
Chapter	11
Pages	247-260
Number of pages	14
ISBN (Electronic)	9783030549329
ISBN (Print)	9783030549312
DOIs	https://doi.org/10.1007/978-3-030-54932-9_11
Publication status	Published - 2021

Publication series

Name	Intelligent Systems Reference Library
Volume	192
ISSN (Print)	1868-4394
ISSN (Electronic)	1868-4408

Access to Document

10.1007/978-3-030-54932-9_11

https://arxiv.org/pdf/2009.12488.pdf

Cite this

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title = "Mental health and sensing",

abstract = "Mental health is a global epidemic, affecting close to half a billion people worldwide. Chronic shortage of resources hamper detection and recovery of affected people. Effective sensing technologies can help fight the epidemic through early detection, prediction, and resulting proper treatment. Existing and novel technologies for sensing mental health state could address the aforementioned concerns by activating granular tracking of physiological, behavioral, and social signals pertaining to problems in mental health. Our paper focuses on the available methods of sensing mental health problems through direct and indirect measures. We see how active and passive sensing by technologies as well as reporting from relevant sources can contribute toward these detection methods. We also see available methods of therapeutic treatment available through digital means. We highlight a few key intervention technologies that are being developed by researchers to fight against mental illness issues.",

keywords = "Mental health, Wearables, Sensing",

author = "Tushar, {Abdul Kawsar} and Ashad Kabir and Ahmed, {Syed Ishtiaque}",

note = "Includes bibliographical references.",

year = "2021",

doi = "10.1007/978-3-030-54932-9_11",

language = "English",

isbn = "9783030549312",

series = " Intelligent Systems Reference Library",

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booktitle = "Signal processing techniques for computational health informatics",

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Mental health and sensing. / Tushar, Abdul Kawsar; Kabir, Ashad; Ahmed, Syed Ishtiaque.
Signal processing techniques for computational health informatics. ed. / Md Atiqur Rahman Ahad; Mosabber Uddin Ahmed. Cham, Switzerland: Springer, 2021. p. 247-260 ( Intelligent Systems Reference Library; Vol. 192).

Research output: Book chapter/Published conference paper › Chapter (peer-reviewed) › peer-review

TY - CHAP

T1 - Mental health and sensing

AU - Tushar, Abdul Kawsar

AU - Kabir, Ashad

AU - Ahmed, Syed Ishtiaque

N1 - Includes bibliographical references.

PY - 2021

Y1 - 2021

N2 - Mental health is a global epidemic, affecting close to half a billion people worldwide. Chronic shortage of resources hamper detection and recovery of affected people. Effective sensing technologies can help fight the epidemic through early detection, prediction, and resulting proper treatment. Existing and novel technologies for sensing mental health state could address the aforementioned concerns by activating granular tracking of physiological, behavioral, and social signals pertaining to problems in mental health. Our paper focuses on the available methods of sensing mental health problems through direct and indirect measures. We see how active and passive sensing by technologies as well as reporting from relevant sources can contribute toward these detection methods. We also see available methods of therapeutic treatment available through digital means. We highlight a few key intervention technologies that are being developed by researchers to fight against mental illness issues.

AB - Mental health is a global epidemic, affecting close to half a billion people worldwide. Chronic shortage of resources hamper detection and recovery of affected people. Effective sensing technologies can help fight the epidemic through early detection, prediction, and resulting proper treatment. Existing and novel technologies for sensing mental health state could address the aforementioned concerns by activating granular tracking of physiological, behavioral, and social signals pertaining to problems in mental health. Our paper focuses on the available methods of sensing mental health problems through direct and indirect measures. We see how active and passive sensing by technologies as well as reporting from relevant sources can contribute toward these detection methods. We also see available methods of therapeutic treatment available through digital means. We highlight a few key intervention technologies that are being developed by researchers to fight against mental illness issues.

KW - Mental health

KW - Wearables

KW - Sensing

UR - https://link.springer.com/book/10.1007/978-3-030-54932-9

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DO - 10.1007/978-3-030-54932-9_11

M3 - Chapter (peer-reviewed)

SN - 9783030549312

T3 - Intelligent Systems Reference Library

SP - 247

EP - 260

BT - Signal processing techniques for computational health informatics

A2 - Ahad, Md Atiqur Rahman

A2 - Ahmed, Mosabber Uddin

PB - Springer

CY - Cham, Switzerland

ER -

Mental health and sensing

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University of Toronto

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Mental health and sensing

Abstract

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University of Toronto

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