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

Area of Science:

• Cardiology
• Respiratory Medicine
• Biomedical Engineering

Background:

• Detecting respiratory effort and classifying sleep apnea often relies on specialized equipment.
• Electrocardiography (ECG) signals contain potential information about respiratory events.

Purpose of the Study:

• To assess if a transformed ECG signal can detect inspiratory bursts from chest wall electromyography (EMG).
• To evaluate the utility of transformed ECG signals for apnea classification compared to respiratory inductance plethysmography (RIP).

Main Methods:

• Part 1: Retrospective review of 250 adult ECGs to assess inspiratory burst visualization in transformed ECGs versus chest wall EMG.
• Part 2: 445 studies were used to select 40 for apnea classification using transformed ECGs and RIP by a blinded scorer, with kappa analysis for agreement.

Main Results:

• Inspiratory bursts were visualized in transformed ECGs in 83% of studies, compared to 71% for chest wall EMG (P < .001).
• Transformed ECG signal classification showed 88.5% agreement with RIP, with a kappa statistic of 0.81 (95% CI 0.76 to 0.86).

Conclusions:

• Transformed ECG signals can reveal inspiratory bursts in a significant proportion of patients.
• This transformed ECG signal shows potential for detecting respiratory effort and classifying sleep apnea.