A multi-modal sensor infrastructure for healthcare in a residential environment

Pete Woznowski; Xenofon Fafoutis; Terence Song; Sion Hannuna; Massimo Camplani; Lili Tao; Adeline Paiement; Evangelos Mellios; Mo Haghighi; Ni Zhu; Geoffrey Hilton; Dima Damen (Aldamen); Tilo Burghardt; Majid Mirmehdi; Robert Piechocki; Dritan Kaleshi; Ian Craddock

doi:10.1109/ICCW.2015.7247190

A multi-modal sensor infrastructure for healthcare in a residential environment

Pete Woznowski, Xenofon Fafoutis, Terence Song, Sion Hannuna, Massimo Camplani, Lili Tao, Adeline Paiement, Evangelos Mellios, Mo Haghighi, Ni Zhu, Geoffrey Hilton, Dima Damen (Aldamen), Tilo Burghardt, Majid Mirmehdi, Robert Piechocki, Dritan Kaleshi, Ian Craddock

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

52 Citations (Scopus)

729 Downloads (Pure)

Abstract

Ambient Assisted Living (AAL) systems based on sensor technologies are seen as key enablers to an ageing society. However, most approaches in this space do not provide a truly generic ambient space - one that is not only capable of assisting people with diverse medical conditions, but can also recognise the habits of healthy habitants, as well as those with developing medical conditions. The recognition of Activities of Daily Living (ADL) is key to the understanding and provisioning of appropriate and efficient care. However, ADL recognition is particularly difficult to achieve in multi-resident spaces; especially with single-mode (albeit carefully crafted) solutions, which only have limited capabilities. To address these limitations we propose a multi-modal system architecture for AAL remote healthcare monitoring in the home, gathering information from multiple, diverse (sensor) data sources. In this paper we report on developments made to-date in various technical areas with respect to critical issues such as cost, power consumption, scalability, interoperability and privacy.

Original language	English
Title of host publication	2015 IEEE International Conference on Communication Workshop, ICCW 2015
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	271-277
Number of pages	7
ISBN (Print)	9781467363051
DOIs	https://doi.org/10.1109/ICCW.2015.7247190
Publication status	Published - 14 Sep 2015
Event	IEEE International Conference on Communication Workshop, ICCW 2015 - London, United Kingdom Duration: 8 Jun 2015 → 12 Jun 2015

Publication series

Name	ICCW
ISSN (Electronic)	2164-7038

Conference

Conference	IEEE International Conference on Communication Workshop, ICCW 2015
Country/Territory	United Kingdom
City	London
Period	8/06/15 → 12/06/15

Structured keywords

Digital Health
SPHERE

Keywords

Ambient Assisted Living
Ambient Intelligence
eHealth
Internet of Things

Access to Document

10.1109/ICCW.2015.7247190

Full-text PDF (accepted author manuscript)
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Accepted author manuscript, 2.89 MB

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Woznowski, P., Fafoutis, X., Song, T., Hannuna, S., Camplani, M., Tao, L., Paiement, A., Mellios, E., Haghighi, M., Zhu, N., Hilton, G., Damen (Aldamen), D., Burghardt, T., Mirmehdi, M., Piechocki, R., Kaleshi, D., & Craddock, I. (2015). A multi-modal sensor infrastructure for healthcare in a residential environment. In 2015 IEEE International Conference on Communication Workshop, ICCW 2015 (pp. 271-277). [7247190] (ICCW). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICCW.2015.7247190

@inproceedings{c229ce4f908e487ab75a838a94dd580c,

title = "A multi-modal sensor infrastructure for healthcare in a residential environment",

abstract = "Ambient Assisted Living (AAL) systems based on sensor technologies are seen as key enablers to an ageing society. However, most approaches in this space do not provide a truly generic ambient space - one that is not only capable of assisting people with diverse medical conditions, but can also recognise the habits of healthy habitants, as well as those with developing medical conditions. The recognition of Activities of Daily Living (ADL) is key to the understanding and provisioning of appropriate and efficient care. However, ADL recognition is particularly difficult to achieve in multi-resident spaces; especially with single-mode (albeit carefully crafted) solutions, which only have limited capabilities. To address these limitations we propose a multi-modal system architecture for AAL remote healthcare monitoring in the home, gathering information from multiple, diverse (sensor) data sources. In this paper we report on developments made to-date in various technical areas with respect to critical issues such as cost, power consumption, scalability, interoperability and privacy.",

keywords = "Ambient Assisted Living, Ambient Intelligence, eHealth, Internet of Things",

author = "Pete Woznowski and Xenofon Fafoutis and Terence Song and Sion Hannuna and Massimo Camplani and Lili Tao and Adeline Paiement and Evangelos Mellios and Mo Haghighi and Ni Zhu and Geoffrey Hilton and {Damen (Aldamen)}, Dima and Tilo Burghardt and Majid Mirmehdi and Robert Piechocki and Dritan Kaleshi and Ian Craddock",

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doi = "10.1109/ICCW.2015.7247190",

language = "English",

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series = "ICCW",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "271--277",

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address = "United States",

note = "IEEE International Conference on Communication Workshop, ICCW 2015 ; Conference date: 08-06-2015 Through 12-06-2015",

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Woznowski, P, Fafoutis, X, Song, T, Hannuna, S, Camplani, M, Tao, L, Paiement, A, Mellios, E, Haghighi, M, Zhu, N, Hilton, G , Damen (Aldamen), D , Burghardt, T , Mirmehdi, M , Piechocki, R, Kaleshi, D & Craddock, I 2015, A multi-modal sensor infrastructure for healthcare in a residential environment. in 2015 IEEE International Conference on Communication Workshop, ICCW 2015., 7247190, ICCW, Institute of Electrical and Electronics Engineers (IEEE), pp. 271-277, IEEE International Conference on Communication Workshop, ICCW 2015, London, United Kingdom, 8/06/15. https://doi.org/10.1109/ICCW.2015.7247190

A multi-modal sensor infrastructure for healthcare in a residential environment. / Woznowski, Pete; Fafoutis, Xenofon; Song, Terence et al.

2015 IEEE International Conference on Communication Workshop, ICCW 2015. Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 271-277 7247190 (ICCW).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - A multi-modal sensor infrastructure for healthcare in a residential environment

AU - Woznowski, Pete

AU - Fafoutis, Xenofon

AU - Song, Terence

AU - Hannuna, Sion

AU - Camplani, Massimo

AU - Tao, Lili

AU - Paiement, Adeline

AU - Mellios, Evangelos

AU - Haghighi, Mo

AU - Zhu, Ni

AU - Hilton, Geoffrey

AU - Damen (Aldamen), Dima

AU - Burghardt, Tilo

AU - Mirmehdi, Majid

AU - Piechocki, Robert

AU - Kaleshi, Dritan

AU - Craddock, Ian

PY - 2015/9/14

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N2 - Ambient Assisted Living (AAL) systems based on sensor technologies are seen as key enablers to an ageing society. However, most approaches in this space do not provide a truly generic ambient space - one that is not only capable of assisting people with diverse medical conditions, but can also recognise the habits of healthy habitants, as well as those with developing medical conditions. The recognition of Activities of Daily Living (ADL) is key to the understanding and provisioning of appropriate and efficient care. However, ADL recognition is particularly difficult to achieve in multi-resident spaces; especially with single-mode (albeit carefully crafted) solutions, which only have limited capabilities. To address these limitations we propose a multi-modal system architecture for AAL remote healthcare monitoring in the home, gathering information from multiple, diverse (sensor) data sources. In this paper we report on developments made to-date in various technical areas with respect to critical issues such as cost, power consumption, scalability, interoperability and privacy.

AB - Ambient Assisted Living (AAL) systems based on sensor technologies are seen as key enablers to an ageing society. However, most approaches in this space do not provide a truly generic ambient space - one that is not only capable of assisting people with diverse medical conditions, but can also recognise the habits of healthy habitants, as well as those with developing medical conditions. The recognition of Activities of Daily Living (ADL) is key to the understanding and provisioning of appropriate and efficient care. However, ADL recognition is particularly difficult to achieve in multi-resident spaces; especially with single-mode (albeit carefully crafted) solutions, which only have limited capabilities. To address these limitations we propose a multi-modal system architecture for AAL remote healthcare monitoring in the home, gathering information from multiple, diverse (sensor) data sources. In this paper we report on developments made to-date in various technical areas with respect to critical issues such as cost, power consumption, scalability, interoperability and privacy.

KW - Ambient Assisted Living

KW - Ambient Intelligence

KW - eHealth

KW - Internet of Things

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DO - 10.1109/ICCW.2015.7247190

M3 - Conference Contribution (Conference Proceeding)

AN - SCOPUS:84947758787

SN - 9781467363051

T3 - ICCW

SP - 271

EP - 277

BT - 2015 IEEE International Conference on Communication Workshop, ICCW 2015

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - IEEE International Conference on Communication Workshop, ICCW 2015

Y2 - 8 June 2015 through 12 June 2015

ER -

A multi-modal sensor infrastructure for healthcare in a residential environment

Abstract

Publication series

Conference

Structured keywords

Keywords

Access to Document

Handle.net

Other files and links

Fingerprint

SPHERE (EPSRC IRC)

Cite this

A multi-modal sensor infrastructure for healthcare in a residential environment

Abstract

Publication series

Conference

Structured keywords

Keywords

Access to Document

Handle.net

Other files and links

Fingerprint

Projects

SPHERE (EPSRC IRC)

Cite this