ADEPTNESS: Alzheimer’s disease patient management system using pervasive sensors - early prototype and preliminary results

Tajim Md Niamat Ullah Akhund; Md Julkar Nayeen Mahi; A. N.M. Hasnat Tanvir; Mufti Mahmud; M. Shamim Kaiser

doi:10.1007/978-3-030-05587-5_39

ADEPTNESS: Alzheimer’s disease patient management system using pervasive sensors - early prototype and preliminary results

Tajim Md Niamat Ullah Akhund
, Md Julkar Nayeen Mahi
, A. N.M. Hasnat Tanvir
, Mufti Mahmud
, M. Shamim Kaiser^*

^*Corresponding author for this work

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

48 Scopus citations

Abstract

Alzheimer’s is a catastrophic neuro-degenerative state in the elderly which reduces thinking skills and thereby hamper daily activity. Thus the management may be helpful for people with such condition. This work presents sensor based management system for Alzheimer’s patient. The main objective of this work is to report an early prototype of an eventual wearable system that can assist in managing the health of such patients and notify the caregivers in case of necessity. A brief case study is presented which showed that the proposed prototype can detect agitated and clam states of patients. As the ultimately developed assistive system will be packaged as a wearable device, the case study also investigated the usability of wearable devices on different age groups of Alzheimer’s patients. In addition, electro dermal activity for 4 patient of age group 55–60 and 60-7s years were also explored to assess the health condition of the patients.

Original language	English
Title of host publication	Brain Informatics - International Conference, BI 2018, Proceedings
Editors	Yang Yang, Vicky Yamamoto, Shouyi Wang, Erick Jones, Jianzhong Su, Tom Mitchell, Leon Iasemidis
Publisher	Springer Verlag
Pages	413-422
Number of pages	10
ISBN (Print)	9783030055868
DOIs	https://doi.org/10.1007/978-3-030-05587-5_39
State	Published - 2018
Externally published	Yes
Event	International Conference on Brain Informatics, BI 2018 - Arlington, United States Duration: 7 Dec 2018 → 9 Dec 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11309 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Brain Informatics, BI 2018
Country/Territory	United States
City	Arlington
Period	7/12/18 → 9/12/18

Bibliographical note

Publisher Copyright:
© 2018, Springer Nature Switzerland AG.

Keywords

Healthcare
Machine learning
Neurodegeneration
Sensor
Wearable devices

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-05587-5_39

Cite this

Niamat Ullah Akhund, T. M., Mahi, M. J. N., Hasnat Tanvir, A. N. M., Mahmud, M., & Kaiser, M. S. (2018). ADEPTNESS: Alzheimer’s disease patient management system using pervasive sensors - early prototype and preliminary results. In Y. Yang, V. Yamamoto, S. Wang, E. Jones, J. Su, T. Mitchell, & L. Iasemidis (Eds.), Brain Informatics - International Conference, BI 2018, Proceedings (pp. 413-422). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11309 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-05587-5_39

Niamat Ullah Akhund, Tajim Md ; Mahi, Md Julkar Nayeen ; Hasnat Tanvir, A. N.M. et al. / ADEPTNESS : Alzheimer’s disease patient management system using pervasive sensors - early prototype and preliminary results. Brain Informatics - International Conference, BI 2018, Proceedings. editor / Yang Yang ; Vicky Yamamoto ; Shouyi Wang ; Erick Jones ; Jianzhong Su ; Tom Mitchell ; Leon Iasemidis. Springer Verlag, 2018. pp. 413-422 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{36ea1abcbe434ba788715ee48f2d76e3,

title = "ADEPTNESS: Alzheimer{\textquoteright}s disease patient management system using pervasive sensors - early prototype and preliminary results",

abstract = "Alzheimer{\textquoteright}s is a catastrophic neuro-degenerative state in the elderly which reduces thinking skills and thereby hamper daily activity. Thus the management may be helpful for people with such condition. This work presents sensor based management system for Alzheimer{\textquoteright}s patient. The main objective of this work is to report an early prototype of an eventual wearable system that can assist in managing the health of such patients and notify the caregivers in case of necessity. A brief case study is presented which showed that the proposed prototype can detect agitated and clam states of patients. As the ultimately developed assistive system will be packaged as a wearable device, the case study also investigated the usability of wearable devices on different age groups of Alzheimer{\textquoteright}s patients. In addition, electro dermal activity for 4 patient of age group 55–60 and 60-7s years were also explored to assess the health condition of the patients.",

keywords = "Healthcare, Machine learning, Neurodegeneration, Sensor, Wearable devices",

author = "\{Niamat Ullah Akhund\}, \{Tajim Md\} and Mahi, \{Md Julkar Nayeen\} and \{Hasnat Tanvir\}, \{A. N.M.\} and Mufti Mahmud and Kaiser, \{M. Shamim\}",

note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Switzerland AG.; International Conference on Brain Informatics, BI 2018 ; Conference date: 07-12-2018 Through 09-12-2018",

year = "2018",

doi = "10.1007/978-3-030-05587-5\_39",

language = "English",

isbn = "9783030055868",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "413--422",

editor = "Yang Yang and Vicky Yamamoto and Shouyi Wang and Erick Jones and Jianzhong Su and Tom Mitchell and Leon Iasemidis",

booktitle = "Brain Informatics - International Conference, BI 2018, Proceedings",

address = "Germany",

}

Niamat Ullah Akhund, TM, Mahi, MJN, Hasnat Tanvir, ANM, Mahmud, M & Kaiser, MS 2018, ADEPTNESS: Alzheimer’s disease patient management system using pervasive sensors - early prototype and preliminary results. in Y Yang, V Yamamoto, S Wang, E Jones, J Su, T Mitchell & L Iasemidis (eds), Brain Informatics - International Conference, BI 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11309 LNAI, Springer Verlag, pp. 413-422, International Conference on Brain Informatics, BI 2018, Arlington, United States, 7/12/18. https://doi.org/10.1007/978-3-030-05587-5_39

ADEPTNESS: Alzheimer’s disease patient management system using pervasive sensors - early prototype and preliminary results. / Niamat Ullah Akhund, Tajim Md; Mahi, Md Julkar Nayeen; Hasnat Tanvir, A. N.M. et al.
Brain Informatics - International Conference, BI 2018, Proceedings. ed. / Yang Yang; Vicky Yamamoto; Shouyi Wang; Erick Jones; Jianzhong Su; Tom Mitchell; Leon Iasemidis. Springer Verlag, 2018. p. 413-422 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11309 LNAI).

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

TY - GEN

T1 - ADEPTNESS

T2 - International Conference on Brain Informatics, BI 2018

AU - Niamat Ullah Akhund, Tajim Md

AU - Mahi, Md Julkar Nayeen

AU - Hasnat Tanvir, A. N.M.

AU - Mahmud, Mufti

AU - Kaiser, M. Shamim

PY - 2018

Y1 - 2018

N2 - Alzheimer’s is a catastrophic neuro-degenerative state in the elderly which reduces thinking skills and thereby hamper daily activity. Thus the management may be helpful for people with such condition. This work presents sensor based management system for Alzheimer’s patient. The main objective of this work is to report an early prototype of an eventual wearable system that can assist in managing the health of such patients and notify the caregivers in case of necessity. A brief case study is presented which showed that the proposed prototype can detect agitated and clam states of patients. As the ultimately developed assistive system will be packaged as a wearable device, the case study also investigated the usability of wearable devices on different age groups of Alzheimer’s patients. In addition, electro dermal activity for 4 patient of age group 55–60 and 60-7s years were also explored to assess the health condition of the patients.

AB - Alzheimer’s is a catastrophic neuro-degenerative state in the elderly which reduces thinking skills and thereby hamper daily activity. Thus the management may be helpful for people with such condition. This work presents sensor based management system for Alzheimer’s patient. The main objective of this work is to report an early prototype of an eventual wearable system that can assist in managing the health of such patients and notify the caregivers in case of necessity. A brief case study is presented which showed that the proposed prototype can detect agitated and clam states of patients. As the ultimately developed assistive system will be packaged as a wearable device, the case study also investigated the usability of wearable devices on different age groups of Alzheimer’s patients. In addition, electro dermal activity for 4 patient of age group 55–60 and 60-7s years were also explored to assess the health condition of the patients.

KW - Healthcare

KW - Machine learning

KW - Neurodegeneration

KW - Sensor

KW - Wearable devices

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DO - 10.1007/978-3-030-05587-5_39

M3 - Conference contribution

AN - SCOPUS:85058534044

SN - 9783030055868

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 413

EP - 422

BT - Brain Informatics - International Conference, BI 2018, Proceedings

A2 - Yang, Yang

A2 - Yamamoto, Vicky

A2 - Wang, Shouyi

A2 - Jones, Erick

A2 - Su, Jianzhong

A2 - Mitchell, Tom

A2 - Iasemidis, Leon

PB - Springer Verlag

Y2 - 7 December 2018 through 9 December 2018

ER -

Niamat Ullah Akhund TM, Mahi MJN, Hasnat Tanvir ANM, Mahmud M, Kaiser MS. ADEPTNESS: Alzheimer’s disease patient management system using pervasive sensors - early prototype and preliminary results. In Yang Y, Yamamoto V, Wang S, Jones E, Su J, Mitchell T, Iasemidis L, editors, Brain Informatics - International Conference, BI 2018, Proceedings. Springer Verlag. 2018. p. 413-422. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-05587-5_39

ADEPTNESS: Alzheimer’s disease patient management system using pervasive sensors - early prototype and preliminary results

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this