Method of respiratory rate measurement using a unique wearable platform and an adaptive optical-based approach
| Autor: | Malini Olivo, Aza Taha, Thanawin Trakoolwilaiwan, Gurpreet Singh, Augustine Tee |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Automated
Technology Respiratory rate Real-time computing Wearable computer Critical Care and Intensive Care Medicine Standard deviation Set (abstract data type) 03 medical and health sciences 0302 clinical medicine Manual counts Medicine General wards Breathing pattern Measure (data warehouse) Adaptive algorithm business.industry Research lcsh:Medical emergencies. Critical care. Intensive care. First aid 030208 emergency & critical care medicine lcsh:RC86-88.9 Triage Confidence interval 030228 respiratory system business |
| Zdroj: | Intensive Care Medicine Experimental Intensive Care Medicine Experimental, Vol 8, Iss 1, Pp 1-10 (2020) |
| ISSN: | 2197-425X |
| Popis: | Background An efficient and accurate method of respiratory rate measurement is still missing in hospital general wards and triage. The goal of this study is to propose a method of respiratory rate measurement that has a potential to be used in general wards, triage, and different hospital settings with comparable performance. We propose a method of respiratory rate measurement that combines a unique wearable platform with an adaptive and optical approach. The optical approach is based on a direct-contact optical diffuse reflectance phenomenon. An adaptive algorithm is developed that computes the first respiratory rate and uses it to select a band. The band then chooses a set of unique optimized parameters in the algorithm to calculate and improve the respiratory rate. We developed a study to compare the proposed method against reference manual counts from 82 patients diagnosed with respiratory diseases. Results We found good agreement between the proposed method of respiratory rate measurement and reference manual counts. The performance of the proposed method highlighted deviations with a 95% confidence interval (C.I.) of − 3.34 and 3.67 breaths per minute (bpm) and a mean bias and standard deviation (STD) of 0.05 bpm and 2.56 bpm, respectively. Conclusions The performance of the proposed method of respiratory rate measurement is comparable with current manual counting and other respiratory rate devices reported. The method has additional advantages that include ease-of-use, quick setup time, and being mobile for wider clinical use. The proposed method has the potential as a tool to measure respiratory rates in a number of use cases. |
| Databáze: | OpenAIRE |
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