Leveraging Central Sleep Apnea Events to Validate the Measurement of Lung Volume Changes Using Thoracic Bio-Impedance

Area of Science:

• Respiratory physiology
• Biomedical engineering
• Sleep medicine

Background:

• Sleep disordered breathing poses significant health risks.
• Current diagnostic methods for sleep apnea are often complex and error-prone.
• Thoracic electrical bio-impedance (BioZ) shows potential as a non-invasive diagnostic tool, but its ability to reflect lung volume changes requires validation.

Purpose of the Study:

• To determine if thoracic electrical bio-impedance (BioZ) variations accurately reflect lung volume changes during sleep.
• To investigate the relationship between BioZ signals and lung volume dynamics during central sleep apnea (CSA) events.
• To assess the influence of body mass index (BMI), gender, and sleeping position on BioZ measurements.

Main Methods:

• Analysis of BioZ signals from 92 sleep studies using linear regression to quantify signal slope and linearity (R2).
• Comparison of BioZ signals during central sleep apnea (CSA) events versus normal breathing segments.
• Application of a linear mixed-effects model to evaluate the impact of BMI, gender, and sleeping position.

Main Results:

• Significant differences in BioZ signals were observed between CSA and normal breathing segments (Welch's ANOVA).
• CSA events were more frequently associated with negative BioZ signal slopes (Chi-squared analysis).
• No significant impact of BMI or gender was found, but the supine sleeping position was linked to more pronounced negative linear trends in BioZ signals.

Conclusions:

• Thoracic electrical bio-impedance (BioZ) is capable of capturing lung volume variations during sleep.
• Sleeping position, specifically the supine posture, significantly influences the clarity and detectability of lung volume changes in BioZ signals.
• BioZ offers a promising avenue for improved diagnostics in sleep disordered breathing.