Networked body sensing: enabling real-time decisions in health and defence applications

Ramona Rednic; John Kemp; Elena Gaura; James Brusey

Networked body sensing: enabling real-time decisions in health and defence applications

Ramona Rednic^*, John Kemp, Elena Gaura, James Brusey

^*Corresponding author for this work

School of Engineering

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

4 Citations (Scopus)

Abstract

This paper presents the application scenario, conceptual overview and implementation of a monitoring system targeted at monitoring EOD suit wearers during missions. The system's aim is to deliver prediction of heat stress risk in the operative and provide actuation of a cooling system integrated within the suit. Prior work established that such prediction requires real-time autonomous processing of skin temperature and body acceleration data, and thus a system implementation is presented based on two interacting subsystems that perform the required sensing and data processing. Posture classification is performed with an accuracy of 96.1%, and a heat stress prediction algorithm is demonstrated with an overall accuracy of 88.5% when predicting the occurrence of heat stress within the next 2 minutes.

Original language	English
Title of host publication	2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	17-23
Number of pages	7
ISBN (Electronic)	9789791421119, 9789791421126
ISBN (Print)	9781457716881
Publication status	Published - 2011
Event	2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011 - Jakarta, Indonesia Duration: 17 Dec 2011 → 18 Dec 2011

Other

Other	2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011
Country/Territory	Indonesia
City	Jakarta
Period	17/12/11 → 18/12/11

Cite this

@inproceedings{3878c9b21d9447beba024dd155156258,

title = "Networked body sensing: enabling real-time decisions in health and defence applications",

abstract = "This paper presents the application scenario, conceptual overview and implementation of a monitoring system targeted at monitoring EOD suit wearers during missions. The system's aim is to deliver prediction of heat stress risk in the operative and provide actuation of a cooling system integrated within the suit. Prior work established that such prediction requires real-time autonomous processing of skin temperature and body acceleration data, and thus a system implementation is presented based on two interacting subsystems that perform the required sensing and data processing. Posture classification is performed with an accuracy of 96.1\%, and a heat stress prediction algorithm is demonstrated with an overall accuracy of 88.5\% when predicting the occurrence of heat stress within the next 2 minutes.",

author = "Ramona Rednic and John Kemp and Elena Gaura and James Brusey",

year = "2011",

language = "English",

isbn = "9781457716881",

pages = "17--23",

booktitle = "2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011",

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

address = "United States",

note = "2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011 ; Conference date: 17-12-2011 Through 18-12-2011",

}

Rednic, R, Kemp, J, Gaura, E & Brusey, J 2011, Networked body sensing: enabling real-time decisions in health and defence applications. in 2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011., 6140736, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 17-23, 2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011, Jakarta, Indonesia, 17/12/11.

Networked body sensing: enabling real-time decisions in health and defence applications. / Rednic, Ramona; Kemp, John; Gaura, Elena et al.
2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2011. p. 17-23 6140736.

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

TY - GEN

T1 - Networked body sensing

T2 - 2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011

AU - Rednic, Ramona

AU - Kemp, John

AU - Gaura, Elena

AU - Brusey, James

PY - 2011

Y1 - 2011

N2 - This paper presents the application scenario, conceptual overview and implementation of a monitoring system targeted at monitoring EOD suit wearers during missions. The system's aim is to deliver prediction of heat stress risk in the operative and provide actuation of a cooling system integrated within the suit. Prior work established that such prediction requires real-time autonomous processing of skin temperature and body acceleration data, and thus a system implementation is presented based on two interacting subsystems that perform the required sensing and data processing. Posture classification is performed with an accuracy of 96.1%, and a heat stress prediction algorithm is demonstrated with an overall accuracy of 88.5% when predicting the occurrence of heat stress within the next 2 minutes.

AB - This paper presents the application scenario, conceptual overview and implementation of a monitoring system targeted at monitoring EOD suit wearers during missions. The system's aim is to deliver prediction of heat stress risk in the operative and provide actuation of a cooling system integrated within the suit. Prior work established that such prediction requires real-time autonomous processing of skin temperature and body acceleration data, and thus a system implementation is presented based on two interacting subsystems that perform the required sensing and data processing. Posture classification is performed with an accuracy of 96.1%, and a heat stress prediction algorithm is demonstrated with an overall accuracy of 88.5% when predicting the occurrence of heat stress within the next 2 minutes.

UR - https://www.scopus.com/pages/publications/84857344935

M3 - Conference proceeding contribution

AN - SCOPUS:84857344935

SN - 9781457716881

SP - 17

EP - 23

BT - 2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

Y2 - 17 December 2011 through 18 December 2011

ER -

Networked body sensing: enabling real-time decisions in health and defence applications

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