A novel angle extremum maximum method for recognition of pulse wave feature points.

Area of Science:

• Biomedical Signal Processing
• Physiological Measurement
• Medical Diagnostics

Background:

• Pulse wave analysis is vital for understanding physiological states and disease correlations.
• Accurate identification of pulse wave feature points is essential for reliable diagnostic interpretations.

Purpose of the Study:

• To investigate the efficacy of angle mapping for precise feature point recognition in pulse waves.
• To develop a robust method for identifying subtle or obscured feature points.

Main Methods:

• Utilized a mathematical approach employing an angle curve with a parameter 'k' applied to pulse wave data.
• Employed numerical calculations and mathematical modeling to analyze the influence of parameter 'k' and pulse wave amplitude.
• Defined feature points as positions of maximum angle extremum values, determined by optimizing parameter 'k'.

Main Results:

• Successfully recognized unobvious feature points using the 'angle extremum maximum method'.
• Presented recognition results and corresponding angle values, comparing them with traditional methods.
• Discussed the determination of an appropriate angle threshold value for feature point identification.

Conclusions:

• The proposed angle mapping method enables accurate and efficient feature point identification in pulse waves.
• This technique demonstrates superior applicability to pulse waves exhibiting noise or indistinct feature points.