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The development of a neonatal vital signs database
Modern intelligent monitoring systems use digital computer technology to analyze and evaluate physiological vital signs. This analytical and evaluative process is performed by algorithms developed for this purpose. The degree of 'intelligence' of the monitoring system is dependent on the 'sensitivit...
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| Format: | Thesis |
| Language: | English |
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Department of Human Biology
2017
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| _version_ | 1867614243848716288 |
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| access_status_str | Open Access |
| author | Berelowitz, Jonathan |
| author2 | Poluta, Mladen |
| author_browse | Berelowitz, Jonathan Poluta, Mladen |
| author_facet | Poluta, Mladen Berelowitz, Jonathan |
| author_sort | Berelowitz, Jonathan |
| collection | Thesis |
| description | Modern intelligent monitoring systems use digital computer technology to analyze and evaluate physiological vital signs. This analytical and evaluative process is performed by algorithms developed for this purpose. The degree of 'intelligence' of the monitoring system is dependent on the 'sensitivity' and 'specificity' of these algorithms. In order to develop robust and clinically valid algorithms, a database of representative waveforms is required. The aim of this thesis was to create a neonatal vital signs database to be used for this purpose, by means of a computer-based central station. The computer was interfaced to a number of neonatal monitors (Neonatal ICU, Groote Schuur Hospital). The monitors were interrogated to obtain patient condition, ECG waveforms and respiration waveforms using the impedance technique. When possible, percentage oxygen saturation was also captured. The database contains 509 documented clinical records obtained from 35 patients and 20 records containing examples of technical alarm conditions and high frequency noise. Additional patient record data is included. Clinical events recorded include apnoea, bradycardia, periodic breathing tachycardia, tachypnoea and normal traces. These events were recorded against a variety of signal quality conditions that have been characterized in Appendix C. A prototype rate detection algorithm was checked using samples from the database. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/26607 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:48:57.312Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Department of Human Biology |
| publisherStr | Department of Human Biology |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/26607 The development of a neonatal vital signs database Berelowitz, Jonathan Poluta, Mladen Woods, David R Van der Elst, Clive Mann, Michael D Neonatology Databases, Factual Monitoring, Physiologic - in infancy and childhood Biomedical Science Modern intelligent monitoring systems use digital computer technology to analyze and evaluate physiological vital signs. This analytical and evaluative process is performed by algorithms developed for this purpose. The degree of 'intelligence' of the monitoring system is dependent on the 'sensitivity' and 'specificity' of these algorithms. In order to develop robust and clinically valid algorithms, a database of representative waveforms is required. The aim of this thesis was to create a neonatal vital signs database to be used for this purpose, by means of a computer-based central station. The computer was interfaced to a number of neonatal monitors (Neonatal ICU, Groote Schuur Hospital). The monitors were interrogated to obtain patient condition, ECG waveforms and respiration waveforms using the impedance technique. When possible, percentage oxygen saturation was also captured. The database contains 509 documented clinical records obtained from 35 patients and 20 records containing examples of technical alarm conditions and high frequency noise. Additional patient record data is included. Clinical events recorded include apnoea, bradycardia, periodic breathing tachycardia, tachypnoea and normal traces. These events were recorded against a variety of signal quality conditions that have been characterized in Appendix C. A prototype rate detection algorithm was checked using samples from the database. 2017-12-13T14:18:16Z 2017-12-13T14:18:16Z 1992 Master Thesis Masters MSc (Med) http://hdl.handle.net/11427/26607 eng application/pdf Department of Human Biology Faculty of Health Sciences University of Cape Town |
| spellingShingle | Neonatology Databases, Factual Monitoring, Physiologic - in infancy and childhood Biomedical Science Berelowitz, Jonathan The development of a neonatal vital signs database |
| thesis_degree_str | Master's |
| title | The development of a neonatal vital signs database |
| title_full | The development of a neonatal vital signs database |
| title_fullStr | The development of a neonatal vital signs database |
| title_full_unstemmed | The development of a neonatal vital signs database |
| title_short | The development of a neonatal vital signs database |
| title_sort | development of a neonatal vital signs database |
| topic | Neonatology Databases, Factual Monitoring, Physiologic - in infancy and childhood Biomedical Science |
| url | http://hdl.handle.net/11427/26607 |
| work_keys_str_mv | AT berelowitzjonathan thedevelopmentofaneonatalvitalsignsdatabase AT berelowitzjonathan developmentofaneonatalvitalsignsdatabase |