University of Surrey

Test tubes in the lab Research in the ATI Dance Research

The development of a quantitative observation system for the early warning of violent behaviours within a secure environment.

Glorney, E, Wells, K, Yuan, H, Hilton, A and Perkins, D The development of a quantitative observation system for the early warning of violent behaviours within a secure environment. In: Conference of the International Society for Research on Aggression, 2014-07-15 - 2014-07-19, Atlanta, Georgia, USA.

Full text not available from this repository.

Abstract

A high frequency of violent harmful behaviour occurs within forensic mental health services. The highest level of secure hospital cares for patients who are most at risk of harm to themselves and/or others. In the UK, monitoring and management risk of harm typically involves close proximity observation and monitoring by designated staff, which can result in patients experiencing invasion of privacy and holds potential to escalate harmful behaviour. For aggression monitoring, computer vision based surveillance approaches have been used in the US Prison system (e.g. Ellis, 1999) and between groups of actors in a study designed to simulate a prison yard (Chang, Krahnstoever, Lim & Yu, 2010) but the real-world application of intelligent computer vision systems to alerting aggressive behaviour that overcome issues of data privacy and identity is yet to be explored. The aim of this study is to develop the first anonymised approach to measurement of aggressive behaviour based around 3D camera technology, with a view to developing an action recognition approach to generate alerts for aggressive/harmful behaviour. The observation system was installed in a ward of a high secure hospital in the UK and provided pseudo-continuous 3D observation of a known closed-set of at-risk patients. Individual antecedent behaviours to an aggressive incident were analysed for developing automatic early alerts to aggression. This approach offers scope as a resource for building long-term observational models of behaviour that could inform future care planning as well as monitoring clinical effectiveness and so enhancing an understanding of violent and risk-related behaviours. Keywords: behavioural monitoring; 3D camera technology; risk management

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
NameEmailORCID
Glorney, Ee.glorney@surrey.ac.ukUNSPECIFIED
Wells, KUNSPECIFIEDUNSPECIFIED
Yuan, HUNSPECIFIEDUNSPECIFIED
Hilton, AUNSPECIFIEDUNSPECIFIED
Perkins, DUNSPECIFIEDUNSPECIFIED
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 10:12
Last Modified : 17 May 2017 10:12
URI: http://epubs.surrey.ac.uk/id/eprint/826860

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800