PhysioEx: Visual Analysis of Physiological Event Streams

Kamaleswaran, R; Collins, C; James, A; McGregor, C

PhysioEx: Visual Analysis of Physiological Event Streams

Kamaleswaran, R Collins, C James, A McGregor, C

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Publisher:: WILEY
Publication Type:: Journal Article
Citation:: Computer Graphics Forum, 2016, 35, (3), pp. 331-340
Issue Date:: 2016-06-01

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Field	Value	Language
dc.contributor.author	Kamaleswaran, R
dc.contributor.author	Collins, C
dc.contributor.author	James, A
dc.contributor.author	McGregor, C https://orcid.org/0000-0002-0491-4403
dc.date.accessioned	2022-03-31T07:14:05Z
dc.date.available	2022-03-31T07:14:05Z
dc.date.issued	2016-06-01
dc.identifier.citation	Computer Graphics Forum, 2016, 35, (3), pp. 331-340
dc.identifier.issn	0167-7055
dc.identifier.issn	1467-8659
dc.identifier.uri	http://hdl.handle.net/10453/155795
dc.description.abstract	In this work, we introduce a novel visualization technique, the Temporal Intensity Map, which visually integrates data values over time to reveal the frequency, duration, and timing of significant features in streaming data. We combine the Temporal Intensity Map with several coordinated visualizations of detected events in data streams to create PhysioEx, a visual dashboard for multiple heterogeneous data streams. We have applied PhysioEx in a design study in the field of neonatal medicine, to support clinical researchers exploring physiologic data streams. We evaluated our method through consultations with domain experts. Results show that our tool provides deep insight capabilities, supports hypothesis generation, and can be well integrated into the workflow of clinical researchers.
dc.language	English
dc.publisher	WILEY
dc.relation.ispartof	Computer Graphics Forum
dc.relation.isbasedon	10.1111/cgf.12909
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing
dc.subject.classification	Software Engineering
dc.title	PhysioEx: Visual Analysis of Physiological Event Streams
dc.type	Journal Article
utslib.citation.volume	35
utslib.location.activity	Groningen, NETHERLANDS
utslib.for	0801 Artificial Intelligence and Image Processing
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2022-03-31T07:14:03Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	35
utslib.citation.issue	3

Abstract:

In this work, we introduce a novel visualization technique, the Temporal Intensity Map, which visually integrates data values over time to reveal the frequency, duration, and timing of significant features in streaming data. We combine the Temporal Intensity Map with several coordinated visualizations of detected events in data streams to create PhysioEx, a visual dashboard for multiple heterogeneous data streams. We have applied PhysioEx in a design study in the field of neonatal medicine, to support clinical researchers exploring physiologic data streams. We evaluated our method through consultations with domain experts. Results show that our tool provides deep insight capabilities, supports hypothesis generation, and can be well integrated into the workflow of clinical researchers.

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http://hdl.handle.net/10453/155795