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Volume 15 No. 07
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Accepted Papers

Scientific Investigations

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

Richard B. Berry, MD1; Scott Ryals, MD1; Marie Dibra, MD1; Mary H. Wagner, MD2
1Division of Pulmonary, Critical Care, and Sleep Medicine, University of Florida, Gainesville, Florida; 2Department of Pediatrics, University of Florida, Gainesville, Florida

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).


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.


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.


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.


Berry RB, Ryals S, Dibra M, Wagner MH. Use of a transformed ECG signal to detect respiratory effort during apnea. J Clin Sleep Med. 2019;15(7):991–998.

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