Abstract
The respiration rate (RR) is a vital sign in physiological measurement and clinical diagnosis. RR can be measured using stretchable and wearable strain gauge sensors which detect the respiratory movements in the abdomen or thorax areas caused by volumetric changes. In different body locations, the accuracy of RR detection might differ due to different respiratory movement amplitudes. Few studies have quantitatively investigated the effect of the measurement location on the accuracy of new sensors in RR detection. Using a stretchable and wearable inkjet-printed strain gauge (IPSG) sensor, RR was measured from five body locations (umbilicus, upper abdomen, xiphoid process, upper thorax, and diagonal) on 30 healthy test subjects while sitting on an armless chair. At each location, reference RR was simultaneously detected by the e-Health sensor, and the measurement was repeated twice. Subjects were asked about the comfortableness of locations. Based on Levene’s test, ANOVA was performed to investigate if there is a significant difference in RR between sensors, measurement locations, and two repeated measurements. Bland–Altman analysis was applied to the RR measurements at different locations. The effects of measurement site and measurement trials on RR difference between sensors were also investigated. There was no significant difference between IPSG and reference sensors, between any locations, and between the two measurements (all p > 0.05). As to the RR deviation between IPSG and reference sensors, there was no significant difference between any locations, or between two measurements (all p > 0.05). All the 30 subjects agreed that diagonal and upper thorax positions were the most uncomfortable and most comfortable locations for measurement, respectively. The IPSG sensor could accurately detect RR at five different locations with good repeatability. Upper thorax was the most comfortable location.
| Original language | English |
|---|---|
| Pages (from-to) | 453-462 |
| Number of pages | 10 |
| Journal | Journal of Clinical Monitoring and Computing |
| Volume | 35 |
| Issue number | 3 |
| Early online date | 22 Feb 2020 |
| DOIs | |
| Publication status | Published - May 2021 |
Bibliographical note
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Funder
Royal Academy of Engineering for Funding this project under Grant Ref. IAPP1R2\100204.Keywords
- Clinical evaluation
- Inkjet printing
- PDMS
- Respiratory rate
- Wearable sensors
ASJC Scopus subject areas
- Health Informatics
- Critical Care and Intensive Care Medicine
- Anesthesiology and Pain Medicine