[Shock shape representation of sinus heart rate based on cloud model]

Area of Science:

• Cardiology
• Biomedical Engineering
• Signal Processing

Background:

• Assessing heart rate variability is crucial for understanding cardiac health.
• Premature ventricular beats can significantly alter heart rate dynamics.
• Existing methods for analyzing these changes may lack real-time applicability.

Purpose of the Study:

• To analyze the trend of sinus heart rate RR interval sequences following a single ventricular premature beat.
• To compare these trends with established parameters: turbulence onset (TO) and turbulence slope (TS).
• To develop and validate a novel algorithm for real-time detection of sinus rhythm changes.

Main Methods:

• Utilized a piecewise linearization method to extract linear characteristics from sinus rhythm data.
• Employed exponential smoothing for QRS wave detection and template matching for sinus rhythm identification.
• Validated the algorithm using signals from the MIT-BIH Arrhythmia Database in Matlab.

Main Results:

• The proposed method successfully detected the changing trend of sinus heart rate.
• Real-time detection of sinus rhythm changes was achieved.
• The algorithm demonstrated simplicity and ease of implementation.

Conclusions:

• The developed method provides an effective supplementary approach for analyzing heart rate dynamics post-ventricular premature beats.
• The algorithm facilitates real-time monitoring of sinus rhythm alterations.
• This technique offers a valuable tool for cardiac rhythm analysis.