<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-27T22:10:21Z</responseDate><request verb="GetRecord" identifier="oai:uvadoc.uva.es:10324/65955" metadataPrefix="marc">https://uvadoc.uva.es/oai/request</request><GetRecord><record><header><identifier>oai:uvadoc.uva.es:10324/65955</identifier><datestamp>2024-04-17T12:15:29Z</datestamp><setSpec>com_10324_1157</setSpec><setSpec>com_10324_931</setSpec><setSpec>com_10324_894</setSpec><setSpec>col_10324_1298</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dcterms="http://purl.org/dc/terms/" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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<subfield code="a">Vuksanovic, Branislav</subfield>
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<subfield code="a">Arias, Roi</subfield>
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<subfield code="a">Machimbarrena Gutiérrez, María de la O</subfield>
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<subfield code="a">Al-Mosawi, Mohamed</subfield>
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<subfield code="c">2019</subfield>
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<subfield code="a">Patients and staff in hospitals, including intensive care units (ICUs) can be exposed to high levels of acoustic noise. In many cases those levels can be significantly above the levels recommended by the World Health Organisation (WHO), affecting both patients and staff working on those units.  A first step towards reducing the ICU noise is to monitor and analyse noise levels in the ICU. In most studies performed to date,  the  analysis  of  noise  and  noise  levels  has  been  done  manually,  via  human &#xd;
interpretation of raw recorded results. This paper uses singular spectrum analysis (SSA)  to  process  and  analyse  sound  pressure  levels  (SPLs)  recorded  in  ICUs  in hospitals in Spain using a dedicated data logging system. SSA algorithm decomposes time-series,  in  this  case  SPL  time-series  measured  over  a period  of  time,  into  a number of components. Those components can then be analysed and interpreted individually or merged with some other components with similar characteristics to be analysed as a group. This approach reveals some interesting characteristics of the SPL time-series and could potentially help in predicting as well as preventing the high SPLs in the coming periods.</subfield>
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<subfield code="a">Conference Proceedings; 48th International Congress and Exhibition on Noise Control Engineering, INTER-NOISE 2019</subfield>
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<subfield code="a">ISBN: 978-848798531-7</subfield>
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<subfield code="a">https://uvadoc.uva.es/handle/10324/65955</subfield>
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<subfield code="a">Monitoring and analysis of noise levels in intensive care units using SSA method</subfield>
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