Waveforms from Multiple Pulse Wave Acquisition Sites

The pulse wave is one of the critical biological signals reflecting cardiovascular system functions. By acquiring pulse wave signals from different anatomical locations (such as wrist, neck, and ankle), researchers can obtain comprehensive cardiovascular information. Code implementation often involves sensor interface programming and signal preprocessing algorithms.

Significance of Multi-Point Acquisition: Comparative Analysis: Waveforms vary across different measurement sites. For example, carotid artery waveforms closely represent original cardiac pulsations, while radial artery waveforms show modifications after vascular transmission. Multi-point comparison enables assessment of vascular elasticity and hemodynamic characteristics through algorithms like cross-correlation analysis. Vascular Modeling: Waveform data from multiple sites facilitates building accurate vascular models to simulate pulse wave propagation through vascular networks. This can be implemented using finite element methods or transfer function modeling to study pathological changes like arteriosclerosis. Signal Validation: Beginners can understand pulse wave attenuation and reflection phenomena by comparing waveforms from different locations, while simultaneously verifying data acquisition system reliability through consistency checks.

Applications of Waveform Characteristics: Amplitude and Temporal Parameters: Feature point amplitudes (e.g., main wave, dicrotic wave) and time intervals reflect vascular status, extractable via peak detection algorithms. Waveform Morphology: Smoothness and symmetry characteristics correlate with vascular health, analyzable through curvature analysis and morphological filtering techniques. Propagation Velocity: Time differences between multi-site waveforms enable pulse wave velocity (PWV) calculation using time-delay estimation methods, providing vascular stiffness assessment.

For beginners, starting with dual-point acquisition (e.g., radial artery and fingertip) and progressively analyzing waveform differences serves as an effective pathway to master pulse wave analysis techniques. Initial code implementation could focus on basic signal alignment and feature extraction functions.