Application of Cardio-Forecasting for Evaluation of Human-Operator Performance

Area of Science:

• Biomedical Engineering
• Occupational Health
• Signal Processing

Background:

• Monitoring human-operator states is crucial for workplace safety and productivity.
• Existing methods may not accurately predict individual exhaustion limits.
• Tailored monitoring is needed for diverse production environments and operators.

Purpose of the Study:

• To develop and demonstrate cardio-forecasting technology for predicting individual working capacity limits.
• To highlight the unique capabilities of this technology in personalized fatigue prediction.
• To create a practical tool for assessing operator criticality.

Main Methods:

• Spectral analysis of human phonocardiograms to isolate heart contraction frequency components.
• Modeling and trend analysis of the amplitude of specific frequency components.
• Determining trend model coefficients that correlate with operator fatigue.
• Developing a software application for Android smartphones.

Main Results:

• A novel methodology for predicting individual exhaustion points based on phonocardiogram analysis.
• Identification of key frequency components and their amplitude trends indicative of fatigue.
• Quantification of operator's remaining working time until capacity exhaustion.
• Successful development of a prototype software application for real-time monitoring.

Conclusions:

• Cardio-forecasting technology offers a unique, personalized approach to predicting worker fatigue.
• Phonocardiogram spectral analysis provides a reliable, non-invasive method for assessing operator's physiological state.
• The developed software application has the potential to enhance occupational safety and efficiency.