Nonlinear Statistical Analysis of Normal and Pathological Infant Cry Signals in Cepstrum Domain by Multifractal...

Area of Science:

• Biomedical Engineering
• Signal Processing
• Infant Health Monitoring

Background:

• Infant cry signals contain vital information about health status.
• Understanding the complex dynamics of infant cries is crucial for early detection of health issues.

Purpose of the Study:

• To investigate the multifractal behavior in the cepstrum of healthy and unhealthy infant cry signals.
• To compare the complexity and dynamics of infant cries under different health conditions.

Main Methods:

• Cepstrum representation of infant cry signals (both expiration and inspiration).
• Wavelet leader analysis to characterize multifractal properties.
• Student t-test for statistical comparison between healthy and unhealthy groups.

Main Results:

• Both healthy and unhealthy infant cries exhibit multifractal properties.
• Healthy infant cry signals demonstrate significantly higher complexity than unhealthy signals.
• Distinct distributions of multifractal characteristics were observed between healthy and unhealthy conditions.

Conclusions:

• Multifractal analysis of infant cries provides a novel method for health status evaluation.
• The findings enhance the understanding of infant cry dynamics and their relation to health.
• This approach can aid in the objective assessment of infant well-being.