Autonomic Nervous System (ANS) maintains body's homeostasis by regulating heart rate and other vital functions. Heart Rate Variability (HRV) analysis is a non-invasive method used to assess ANS activity by measuring variations between consecutive heartbeats. Poincare plot, a widely used HRV analysis tool, visualizes the relationship between successive heartbeats. However, conventional Poincare plot analysis primarily relies on static statistical descriptors, such as SD1 and SD2, which measure short-term and long-term variability but fail to capture the dynamic progression of heartbeat intervals. This paper introduces motion path analysis of the Poincare plot, a novel approach that tracks how heartbeat intervals evolve over time. By following the sequential movement of data points, this method reveals both short-term and long-term HRV trends. Our study demonstrates that motion path analysis detects subtle changes in heart rate patterns under different physiological conditions, such as rest and stress (e.g. head-up tilt tests). This technique offers a more comprehensive understanding of ANS activity by visualizing point-to-point transitions influenced by sympathetic and parasympathetic responses. Motion path analysis offers a new way to visualize and interpret the complex temporal fluctuations of ANS and has potential applications in clinical research, providing deeper insight into autonomic regulation in health and disease.
Competing Interest StatementThe authors have declared no competing interest.
Funding StatementThis study did not receive any funding
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Institutional Ethics Committee, Institute of Postgraduate Medical Education & Research, Kolkata, India. Ethical clearance was granted
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