Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Jul 15;15(7):991-998.
doi: 10.5664/jcsm.7880.

Use of a Transformed ECG Signal to Detect Respiratory Effort During Apnea

Affiliations
Free PMC article

Use of a Transformed ECG Signal to Detect Respiratory Effort During Apnea

Richard B Berry et al. J Clin Sleep Med. .
Free PMC article

Abstract

Study objectives: To evaluate the ability of a transformed electrocardiography (ECG) signal recorded using standard electrode placement to detect inspiratory bursts from underlying surface chest wall electromyography (EMG) activity and the utility of the transformed signal for apnea classification compared to uncalibrated respiratory inductance plethysmography (RIP).

Methods: Part 1: 250 consecutive adult studies without regard to respiratory events were retrospectively reviewed. The ECG signal was transformed with high pass filtering and viewed with increased sensitivity and channel clipping to determine the fraction of studies with inspiratory burst visualization as compared to chest wall EMG (right thorax). Part 2: 445 consecutive studies were reviewed to select 40 with ≥ 10 obstructive and ≥ 10 mixed or central apneas (clinical scoring). Five obstructive and 5 central or mixed apneas were randomly selected from each study. A blinded scorer classified the apneas using either RIP or a transformed ECG signal using high pass filtering and QRS blanking. The agreement between the two classifications was determined by kappa analysis.

Results: Part 1: Inspiratory burst visualization was noted in the transformed ECG signals and chest wall EMG signals in 83% and 71% of the studies (P < .001). Part 2: The percentage agreement between RIP and transformed ECG signal classification was 88.5%, the kappa statistic was 0.81 (95% CI 0.76 to 0.86) and interclass correlation was 0.84, showing good agreement.

Conclusions: A transformed ECG signal can exhibit inspiratory bursts in a high proportion of patients and is potentially useful for detecting respiratory effort and apnea classification.

Keywords: apnea; diaphragmatic EMG; respiratory effort.

Similar articles

See all similar articles

Cited by 2 articles

LinkOut - more resources

Feedback