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 0.5Hz) 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.
Highlights
RESPIRATORY rate is a sensitive clinical marker in many pulmonary diseases [1], e.g., it is the first marker for acute respiratory dysfunction [2], and it is useful for detection of periodic breathing [3] which leads to a higher mortality in patients suffering from heart failure [4]
An ECG derived respiration (EDR) algorithm has been evaluated for respiratory rate estimation derived from a wearable armband ECG monitor
The armband device was developed in our lab at the University of Connecticut, and it records three-channel ECG signals using three pairs of dry electrodes
Summary
RESPIRATORY rate is a sensitive clinical marker in many pulmonary diseases [1], e.g., it is the first marker for acute respiratory dysfunction [2], and it is useful for detection of periodic breathing [3] which leads to a higher mortality in patients suffering from heart failure [4]. Multimodal analysis of respiratory rate and electrocardiogram (ECG) opens a wider range of applications including sleep studies [8], epileptic seizure detection [9], stress level assessment [10], and monitoring patients suffering from chronic respiratory diseases such as asthma [11] or chronic obstructive pulmonary disease (COPD). The chronic respiratory patients are affected by destabilizations (or “exacerbations”) which makes them to seek medical help and often lead to their hospitalization. These exacerbations are one of the main causes of mortality among patients with COPD and asthma [12], [13]. A wearable cardiorespiratory monitor would have a wide range of applications
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