An ECG-Based System for Respiratory Rate Estimation Tested on a Wearable Armband during Daily Life

Abstract

A pilot study on breathing rate (BR) estimation during daily life by using a wearable armband is presented. This wearable armband provides three electrocardiogram (ECG) channels, and BR was estimatedfrom them by using ECG derived respiration (EDR) techniques based on respiration-related QRS morphology modulations: QRS slopes and R-wave angle. Five healthy volunteers wore the armband during 24 hours, with the only instruction not to exercise. In addition, reference ECG signals were simultaneously recorded by a market-available 3-channel Holter monitor. The percentage of armband's accurate BR estimations (differing less than 5% from the Holter estimation) with respect to the total number of Holter's estimations was computed (P1). In addition, the percentage of accurate armband's BR estimations with respect to the total number of armband's estimations was also computed (P2). P1 ranged from 26.59% to 73.00% during non-bed time, and from 63.05% to 88.73% during bed time. P2 ranged from 60.89% to 94.57% during non-bed time, and from 81.65% to 97.38% during bed time. These results are promising and suggest that the armband may be useful for BR monitoring in some applications. However, an artifact detector specifically focused on detecting those segments which are usable for BR detection needs to be developed.