Name
Abstract | ||
|---|---|---|
A method for deriving respiratory rate from an armband, which records three-channel electrocardiogram (ECG) using three pairs of dry (no hydrogel) electrodes, is presented. The armband device is especially convenient for long-term (months-years) monitoring because it does not use obstructive leads nor hydrogels/adhesives, which cause skin irritation even after few days. An ECG-derived respiration (EDR) based on respiration-related modulation of QRS slopes and R-wave angle approach was used. Moreover, we modified the EDR algorithm to lower the computational cost. Respiratory rates were estimated with the armband-ECG and the reference plethysmography-based respiration signals from 15 subjects who underwent breathing experiment consisting of five stages of controlled breathing (at 0.1, 0.2, 0.3, 0.4, and 0.5 Hz) and one stage of spontaneous breathing. The respiratory rates from the armband obtained a relative error with respect to the reference (respiratory rate estimated from the plethysmography-based respiration signal) that was not higher than 2.26% in median nor interquartile range (IQR) for all stages of fixed and spontaneous breathing, and not higher than 3.57% in median nor IQR in the case when the low computational cost algorithm was applied. These results demonstrate that respiration-related modulation of the ECG morphology are also present in the armband ECG device. Furthermore, these results suggest that respiration-related modulation can be exploited by the EDR method based on QRS slopes and R-wave angles to obtain respiratory rate, which may have a wide range of applications including monitoring patients with chronic respiratory diseases, epileptic seizures detection, stress assessment, and sleep studies, among others. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TBME.2020.3004730 | IEEE Transactions on Biomedical Engineering |
Keywords | DocType | Volume |
Algorithms,Electrocardiography,Humans,Respiration,Respiratory Rate,Signal Processing, Computer-Assisted,Wearable Electronic Devices | Journal | 68 |
Issue | ISSN | Citations |
3 | 0018-9294 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jesús Lázaro | 1 | 62 | 16.25 |
| Nataša Reljin | 2 | 13 | 4.28 |
| Raquel Bailón | 3 | 176 | 31.28 |
| Eduardo Gil | 4 | 61 | 19.54 |
| Yeon-Sik Noh | 5 | 8 | 6.09 |
| P Laguna | 6 | 255 | 74.15 |
| Ki Chon | 7 | 0 | 0.34 |