| Literature DB >> 30126085 |
Christian Peter Subbe1, Sean Kinsella2.
Abstract
Respiratory Rate (RR) is the best marker to indicate deterioration but measurement are often inaccurate. The RespiraSense™ is a non-invasive, wireless, body worn, motion-tolerant and continuous respiratory rate monitor. We aimed to determine whether the performance of RespiraSense™ was equivalent to that of a gold standard measurement technique of capnography and the industry standard of manual counts. RespiraSense™ measures respiratory rate and transmit signals wirelessly to a tablet device. We measured respiratory rate in 24 emergency admissions to an Acute Medical Unit in the UK. Patients were observed for two hours. Manual counts were undertaken every 15 min and compared to measurements with capnography and RespiraSense™. Data from 17 patients admitted as medical emergencies was evaluated. For measurements obtained at rest a mean RR of 19.3 (SD 4.89) for manual measurements compared to mean RR of 20.2 (SD 4.54) for measurements obtained with capnography and mean RR of 19.8 (SD 4.52) with RespiraSense™. At rest, RespiraSense™ has a bias of 0.38 and limits of agreement of 1.0 to 1.8 bpm, when compared to the capnography derived RR. Measurements were within pre-defined limits of error at rest. Continuous measurement of RR with RespiraSense™ in patients admitted as acute emergencies is both feasible and reliable.Entities:
Keywords: monitoring; respiratory rate; sensor
Mesh:
Year: 2018 PMID: 30126085 PMCID: PMC6111745 DOI: 10.3390/s18082700
Source DB: PubMed Journal: Sensors (Basel) ISSN: 1424-8220 Impact factor: 3.576
Figure 1Schedule of events for this investigation.
Figure 2RespiraSense™ lobe and sensor (a) and position while undertaking monitoring (b).
Figure 3Recruitment into study with exclusions.
Figure 4Bland Altman plots of (a) Capnograph counts vs. RespiraSense in the first hour (at rest); (b) Manual respiratory rate counts vs. RespiraSense in the first hour (at rest); (c) Manual respiratory rate counts vs. RespiraSense in the second hour (while moving).
Figure 5Example of detection of movement artefacts.