Technical challenges related to implementation of a formula one real time data acquisition and analysis system in a paediatric intensive care unit
Most existing, expert monitoring systems do not provide the real time continuous analysis of the monitored physiological data that is necessary to detect transient or combined vital sign indicators nor do they provide long term storage of the data for retrospective analyses. In this paper we examine...
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| Veröffentlicht in: | Journal of clinical monitoring and computing 2018-06, Vol.32 (3), p.559-569 |
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| description | Most existing, expert monitoring systems do not provide the real time continuous analysis of the monitored physiological data that is necessary to detect transient or combined vital sign indicators nor do they provide long term storage of the data for retrospective analyses. In this paper we examine the feasibility of implementing a long term data storage system which has the ability to incorporate real-time data analytics, the system design, report the main technical issues encountered, the solutions implemented and the statistics of the data recorded. McLaren Electronic Systems expertise used to continually monitor and analyse the data from F1 racing cars in real time was utilised to implement a similar real-time data recording platform system adapted with real time analytics to suit the requirements of the intensive care environment. We encountered many technical (hardware and software) implementation challenges. However there were many advantages of the system once it was operational. They include: (1) The ability to store the data for long periods of time enabling access to historical physiological data. (2) The ability to alter the time axis to contract or expand periods of interest. (3) The ability to store and review ECG morphology retrospectively. (4) Detailed post event (cardiac/respiratory arrest or other clinically significant deteriorations in patients) data can be reviewed clinically as opposed to trend data providing valuable clinical insight. Informed mortality and morbidity reviews can be conducted. (5) Storage of waveform data capture to use for algorithm development for adaptive early warning systems. Recording data from bed-side monitors in intensive care/wards is feasible. It is possible to set up real time data recording and long term storage systems. These systems in future can be improved with additional patient specific metrics which predict the status of a patient thus paving the way for real time predictive monitoring. |
| doi_str_mv | 10.1007/s10877-017-0047-6 |
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These systems in future can be improved with additional patient specific metrics which predict the status of a patient thus paving the way for real time predictive monitoring.</description><identifier>ISSN: 1387-1307</identifier><identifier>EISSN: 1573-2614</identifier><identifier>DOI: 10.1007/s10877-017-0047-6</identifier><identifier>PMID: 28752472</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Adaptive algorithms ; Adaptive systems ; Adolescent ; Algorithms ; Analytics ; Anesthesiology ; Child ; Child, Preschool ; Computer Systems ; Computers ; Critical Care ; Critical Care Medicine ; Data analysis ; Data capture ; Data recording ; Data storage ; Early warning systems ; Electrocardiography ; Electronic systems ; Feasibility studies ; Health Sciences ; Humans ; Infant ; Infant, Newborn ; Intensive ; Intensive care ; Intensive Care Units, Pediatric ; Length of Stay ; Long term ; Medicine ; Medicine & Public Health ; Monitoring, Physiologic - instrumentation ; Original Research ; Pediatrics - methods ; Physiology ; Race cars ; Racing ; Real time ; Retrospective Studies ; Risk Assessment ; Software ; Statistics for Life Sciences ; Storage systems ; Systems design</subject><ispartof>Journal of clinical monitoring and computing, 2018-06, Vol.32 (3), p.559-569</ispartof><rights>The Author(s) 2017</rights><rights>Journal of Clinical Monitoring and Computing is a copyright of Springer, (2017). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c523t-dbe67e43ddd162eb1a316475be978c811a4d14b8f564e835152758bc3a3faff13</citedby><cites>FETCH-LOGICAL-c523t-dbe67e43ddd162eb1a316475be978c811a4d14b8f564e835152758bc3a3faff13</cites><orcidid>0000-0002-2224-6816</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10877-017-0047-6$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10877-017-0047-6$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28752472$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Matam, B. Rajeswari</creatorcontrib><creatorcontrib>Duncan, Heather</creatorcontrib><title>Technical challenges related to implementation of a formula one real time data acquisition and analysis system in a paediatric intensive care unit</title><title>Journal of clinical monitoring and computing</title><addtitle>J Clin Monit Comput</addtitle><addtitle>J Clin Monit Comput</addtitle><description>Most existing, expert monitoring systems do not provide the real time continuous analysis of the monitored physiological data that is necessary to detect transient or combined vital sign indicators nor do they provide long term storage of the data for retrospective analyses. In this paper we examine the feasibility of implementing a long term data storage system which has the ability to incorporate real-time data analytics, the system design, report the main technical issues encountered, the solutions implemented and the statistics of the data recorded. McLaren Electronic Systems expertise used to continually monitor and analyse the data from F1 racing cars in real time was utilised to implement a similar real-time data recording platform system adapted with real time analytics to suit the requirements of the intensive care environment. We encountered many technical (hardware and software) implementation challenges. However there were many advantages of the system once it was operational. They include: (1) The ability to store the data for long periods of time enabling access to historical physiological data. (2) The ability to alter the time axis to contract or expand periods of interest. (3) The ability to store and review ECG morphology retrospectively. (4) Detailed post event (cardiac/respiratory arrest or other clinically significant deteriorations in patients) data can be reviewed clinically as opposed to trend data providing valuable clinical insight. Informed mortality and morbidity reviews can be conducted. (5) Storage of waveform data capture to use for algorithm development for adaptive early warning systems. Recording data from bed-side monitors in intensive care/wards is feasible. It is possible to set up real time data recording and long term storage systems. These systems in future can be improved with additional patient specific metrics which predict the status of a patient thus paving the way for real time predictive monitoring.</description><subject>Adaptive algorithms</subject><subject>Adaptive systems</subject><subject>Adolescent</subject><subject>Algorithms</subject><subject>Analytics</subject><subject>Anesthesiology</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Computer Systems</subject><subject>Computers</subject><subject>Critical Care</subject><subject>Critical Care Medicine</subject><subject>Data analysis</subject><subject>Data capture</subject><subject>Data recording</subject><subject>Data storage</subject><subject>Early warning systems</subject><subject>Electrocardiography</subject><subject>Electronic systems</subject><subject>Feasibility studies</subject><subject>Health Sciences</subject><subject>Humans</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Intensive</subject><subject>Intensive care</subject><subject>Intensive Care Units, Pediatric</subject><subject>Length of Stay</subject><subject>Long term</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Monitoring, Physiologic - instrumentation</subject><subject>Original Research</subject><subject>Pediatrics - methods</subject><subject>Physiology</subject><subject>Race cars</subject><subject>Racing</subject><subject>Real time</subject><subject>Retrospective Studies</subject><subject>Risk Assessment</subject><subject>Software</subject><subject>Statistics for Life Sciences</subject><subject>Storage systems</subject><subject>Systems design</subject><issn>1387-1307</issn><issn>1573-2614</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kctu3SAQhq2qVZOmfYBuKqRuunEDxhi8qVRFvUmRsknXaAzjHCIMJ4AjndfIE5eTk6YXKYsRl_nmZ4a_ad4y-pFRKk8zo0rKlrIatJft8Kw5ZkLythtY_7zuuZIt41QeNa9yvqaUjoqzl81Rp6ToetkdN3eXaDbBGfDEbMB7DFeYSUIPBS0pkbhl63HBUKC4GEicCZA5pmX1QGLAitbS4hYkFgoQMDery-6ehWBrgN9ll0ne5YILcfWabAGtg5KcqeeCIbtbJAYSkjW48rp5MYPP-OZhPWl-fv1yefa9Pb_49uPs83lrRMdLayccJPbcWsuGDicGnA29FBOOUhnFGPSW9ZOaxdCj4oKJTgo1GQ58hnlm_KT5dNDdrtOC1tQZE3i9TW6BtNMRnP43E9xGX8VbLcaec8WrwIcHgRRvVsxFLy4b9B4CxjVrNna9GEVtq6Lv_0Ov45rq32TdUT4Mg1RyrBQ7UCbFnBPOj80wqveO64Pjujqu947rvfK7v6d4rPhtcQW6A5Brqrqb_jz9tOovc066Jg</recordid><startdate>20180601</startdate><enddate>20180601</enddate><creator>Matam, B. Rajeswari</creator><creator>Duncan, Heather</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7SC</scope><scope>7SP</scope><scope>7U5</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>KB0</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-2224-6816</orcidid></search><sort><creationdate>20180601</creationdate><title>Technical challenges related to implementation of a formula one real time data acquisition and analysis system in a paediatric intensive care unit</title><author>Matam, B. Rajeswari ; Duncan, Heather</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c523t-dbe67e43ddd162eb1a316475be978c811a4d14b8f564e835152758bc3a3faff13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adaptive algorithms</topic><topic>Adaptive systems</topic><topic>Adolescent</topic><topic>Algorithms</topic><topic>Analytics</topic><topic>Anesthesiology</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Computer Systems</topic><topic>Computers</topic><topic>Critical Care</topic><topic>Critical Care Medicine</topic><topic>Data analysis</topic><topic>Data capture</topic><topic>Data recording</topic><topic>Data storage</topic><topic>Early warning systems</topic><topic>Electrocardiography</topic><topic>Electronic systems</topic><topic>Feasibility studies</topic><topic>Health Sciences</topic><topic>Humans</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>Intensive</topic><topic>Intensive care</topic><topic>Intensive Care Units, Pediatric</topic><topic>Length of Stay</topic><topic>Long term</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Monitoring, Physiologic - instrumentation</topic><topic>Original Research</topic><topic>Pediatrics - methods</topic><topic>Physiology</topic><topic>Race cars</topic><topic>Racing</topic><topic>Real time</topic><topic>Retrospective Studies</topic><topic>Risk Assessment</topic><topic>Software</topic><topic>Statistics for Life Sciences</topic><topic>Storage systems</topic><topic>Systems design</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Matam, B. 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Rajeswari</au><au>Duncan, Heather</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Technical challenges related to implementation of a formula one real time data acquisition and analysis system in a paediatric intensive care unit</atitle><jtitle>Journal of clinical monitoring and computing</jtitle><stitle>J Clin Monit Comput</stitle><addtitle>J Clin Monit Comput</addtitle><date>2018-06-01</date><risdate>2018</risdate><volume>32</volume><issue>3</issue><spage>559</spage><epage>569</epage><pages>559-569</pages><issn>1387-1307</issn><eissn>1573-2614</eissn><abstract>Most existing, expert monitoring systems do not provide the real time continuous analysis of the monitored physiological data that is necessary to detect transient or combined vital sign indicators nor do they provide long term storage of the data for retrospective analyses. In this paper we examine the feasibility of implementing a long term data storage system which has the ability to incorporate real-time data analytics, the system design, report the main technical issues encountered, the solutions implemented and the statistics of the data recorded. McLaren Electronic Systems expertise used to continually monitor and analyse the data from F1 racing cars in real time was utilised to implement a similar real-time data recording platform system adapted with real time analytics to suit the requirements of the intensive care environment. We encountered many technical (hardware and software) implementation challenges. However there were many advantages of the system once it was operational. They include: (1) The ability to store the data for long periods of time enabling access to historical physiological data. (2) The ability to alter the time axis to contract or expand periods of interest. (3) The ability to store and review ECG morphology retrospectively. (4) Detailed post event (cardiac/respiratory arrest or other clinically significant deteriorations in patients) data can be reviewed clinically as opposed to trend data providing valuable clinical insight. Informed mortality and morbidity reviews can be conducted. (5) Storage of waveform data capture to use for algorithm development for adaptive early warning systems. Recording data from bed-side monitors in intensive care/wards is feasible. It is possible to set up real time data recording and long term storage systems. These systems in future can be improved with additional patient specific metrics which predict the status of a patient thus paving the way for real time predictive monitoring.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>28752472</pmid><doi>10.1007/s10877-017-0047-6</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-2224-6816</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of clinical monitoring and computing, 2018-06, Vol.32 (3), p.559-569 |
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| language | eng |
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| source | MEDLINE; SpringerNature Journals |
| subjects | Adaptive algorithms Adaptive systems Adolescent Algorithms Analytics Anesthesiology Child Child, Preschool Computer Systems Computers Critical Care Critical Care Medicine Data analysis Data capture Data recording Data storage Early warning systems Electrocardiography Electronic systems Feasibility studies Health Sciences Humans Infant Infant, Newborn Intensive Intensive care Intensive Care Units, Pediatric Length of Stay Long term Medicine Medicine & Public Health Monitoring, Physiologic - instrumentation Original Research Pediatrics - methods Physiology Race cars Racing Real time Retrospective Studies Risk Assessment Software Statistics for Life Sciences Storage systems Systems design |
| title | Technical challenges related to implementation of a formula one real time data acquisition and analysis system in a paediatric intensive care unit |
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