Respiratory rate estimation during triage of children in hospitals
Accurate assessment of a child’s health is critical for appropriate allocation of medical resources and timely delivery of healthcare in Emergency Departments. The accurate measurement of vital signs is a key step in the determination of the severity of illness and respiratory rate is currently the...
| Main Authors: | , , , |
|---|---|
| Format: | Journal article |
| Language: | English |
| Published: |
Taylor and Francis
2015
|
| _version_ | 1797053574337789952 |
|---|---|
| author | Shah, SA Fleming, S Thompson, M Tarassenko, L |
| author_facet | Shah, SA Fleming, S Thompson, M Tarassenko, L |
| author_sort | Shah, SA |
| collection | OXFORD |
| description | Accurate assessment of a child’s health is critical for appropriate allocation of medical resources and timely delivery of healthcare in Emergency Departments. The accurate measurement of vital signs is a key step in the determination of the severity of illness and respiratory rate is currently the most difficult vital sign to measure accurately. Several previous studies have attempted to extract respiratory rate from photoplethysmogram (PPG) recordings. However, the majority have been conducted in controlled settings using PPG recordings from healthy subjects. In many studies, manual selection of clean sections of PPG recordings was undertaken before assessing the accuracy of the signal processing algorithms developed. Such selection procedures are not appropriate in clinical settings. A major limitation of AR modelling, previously applied to respiratory rate estimation, is an appropriate selection of model order. This study developed a novel algorithm that automatically estimates respiratory rate from a median spectrum constructed applying multiple AR models to processed PPG segments acquired with pulse oximetry using a finger probe. Good-quality sections were identified using a dynamic template-matching technique to assess PPG signal quality. The algorithm was validated on 205 children presenting to the Emergency Department at the John Radcliffe Hospital, Oxford, UK, with reference respiratory rates up to 50 breaths per minute estimated by paediatric nurses. At the time of writing, the authors are not aware of any other study that has validated respiratory rate estimation using data collected from over 200 children in hospitals during routine triage. |
| first_indexed | 2024-03-06T18:45:33Z |
| format | Journal article |
| id | oxford-uuid:0e62f196-a0f7-413c-a89f-db74e5fffa06 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:45:33Z |
| publishDate | 2015 |
| publisher | Taylor and Francis |
| record_format | dspace |
| spelling | oxford-uuid:0e62f196-a0f7-413c-a89f-db74e5fffa062022-03-26T09:45:38ZRespiratory rate estimation during triage of children in hospitalsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:0e62f196-a0f7-413c-a89f-db74e5fffa06EnglishSymplectic Elements at OxfordTaylor and Francis2015Shah, SAFleming, SThompson, MTarassenko, LAccurate assessment of a child’s health is critical for appropriate allocation of medical resources and timely delivery of healthcare in Emergency Departments. The accurate measurement of vital signs is a key step in the determination of the severity of illness and respiratory rate is currently the most difficult vital sign to measure accurately. Several previous studies have attempted to extract respiratory rate from photoplethysmogram (PPG) recordings. However, the majority have been conducted in controlled settings using PPG recordings from healthy subjects. In many studies, manual selection of clean sections of PPG recordings was undertaken before assessing the accuracy of the signal processing algorithms developed. Such selection procedures are not appropriate in clinical settings. A major limitation of AR modelling, previously applied to respiratory rate estimation, is an appropriate selection of model order. This study developed a novel algorithm that automatically estimates respiratory rate from a median spectrum constructed applying multiple AR models to processed PPG segments acquired with pulse oximetry using a finger probe. Good-quality sections were identified using a dynamic template-matching technique to assess PPG signal quality. The algorithm was validated on 205 children presenting to the Emergency Department at the John Radcliffe Hospital, Oxford, UK, with reference respiratory rates up to 50 breaths per minute estimated by paediatric nurses. At the time of writing, the authors are not aware of any other study that has validated respiratory rate estimation using data collected from over 200 children in hospitals during routine triage. |
| spellingShingle | Shah, SA Fleming, S Thompson, M Tarassenko, L Respiratory rate estimation during triage of children in hospitals |
| title | Respiratory rate estimation during triage of children in hospitals |
| title_full | Respiratory rate estimation during triage of children in hospitals |
| title_fullStr | Respiratory rate estimation during triage of children in hospitals |
| title_full_unstemmed | Respiratory rate estimation during triage of children in hospitals |
| title_short | Respiratory rate estimation during triage of children in hospitals |
| title_sort | respiratory rate estimation during triage of children in hospitals |
| work_keys_str_mv | AT shahsa respiratoryrateestimationduringtriageofchildreninhospitals AT flemings respiratoryrateestimationduringtriageofchildreninhospitals AT thompsonm respiratoryrateestimationduringtriageofchildreninhospitals AT tarassenkol respiratoryrateestimationduringtriageofchildreninhospitals |