title: Lightweight physiologic sensor performance during pre-hospital care delivered by ambulance clinicians.
abstract: The aim of this study was to explore the impact of motion generated by ambulance patient management on the performance of two lightweight physiologic sensors. Two physiologic sensors were applied to pre-hospital patients. The first was the Contec Medical Systems CMS50FW finger pulse oximeter, monitoring heart rate (HR) and blood oxygen saturation (SpO2). The second was the RESpeck respiratory rate (RR) sensor, which was wireless-enabled with a Bluetooth(®) Low Energy protocol. Sensor data were recorded from 16 pre-hospital patients, who were monitored for 21.2 ± 9.8 min, on average. Some form of error was identified on almost every HR and SpO2 trace. However, the mean proportion of each trace exhibiting error was <10 % (range <1-50 % for individual patients). There appeared to be no overt impact of the gross motion associated with road ambulance transit on the incidence of HR or SpO2 error. The RESpeck RR sensor delivered an average of 4.2 (±2.2) validated breaths per minute, but did not produce any validated breaths during the gross motion of ambulance transit as its pre-defined motion threshold was exceeded. However, this was many more data points than could be achieved using traditional manual assessment of RR. Error was identified on a majority of pre-hospital physiologic signals, which emphasised the need to ensure consistent sensor attachment in this unstable and unpredictable environment, and in developing intelligent methods of screening out such error.
authors: dot.rural Digital Economy Hub, King's College, University of Aberdeen, Aberdeen, Scotland, UK. a.mort@abdn.ac.uk.|The Centre for Rural Health, University of Aberdeen, Centre for Health Science, Old Perth Road, Inverness, Scotland, UK. a.mort@abdn.ac.uk.
authors: Alasdair J
authors: AJ
authors: Mort
authors: Scottish Ambulance Service, Gyle Square, Edinburgh, Scotland, UK.
authors: David
authors: D
authors: Fitzpatrick
authors: dot.rural Digital Economy Hub, King's College, University of Aberdeen, Aberdeen, Scotland, UK.|The Centre for Rural Health, University of Aberdeen, Centre for Health Science, Old Perth Road, Inverness, Scotland, UK.
authors: Philip M J
authors: PM
authors: Wilson
authors: dot.rural Digital Economy Hub, King's College, University of Aberdeen, Aberdeen, Scotland, UK.|Department of Computing Science, King's College, University of Aberdeen, Aberdeen, Scotland, UK.
authors: Chris
authors: C
authors: Mellish
authors: dot.rural Digital Economy Hub, King's College, University of Aberdeen, Aberdeen, Scotland, UK.
authors: Anne
authors: A
authors: Schneider
mesh_terms: D061725:Accelerometry / Q000295:instrumentation; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000552:Ambulances; D004562:Electrocardiography / Q000295:instrumentation*; D004632:Emergency Medical Services; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D008904:Miniaturization; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D009038:Motion; D010092:Oximetry / Q000295:instrumentation*; D015203:Reproducibility of Results; D012129:Respiratory Function Tests / Q000295:instrumentation*; D056152:Respiratory Rate; D012680:Sensitivity and Specificity; D014159:Transducers; D059015:Wireless Technology / Q000295:instrumentation
keywords: Ambulance clinicians; Motion artefact; Physiologic monitoring; Pre-hospital