Fast pulse wave period cutting algorithm

Abstract

The invention discloses a fast pulse wave period cutting algorithm. The algorithm comprises the following steps of 1, signal preprocessing, wherein moving average filtering preprocessing is conducted on an original pulse wave signal; step 2, trend detection and candidate section determination: determining a starting moment of a rising branch of each period based on local trend detection after signal smoothing, and forming a period candidate section; step 3, boundary refinement and dynamic adjustment: local extreme value detection and slope comparison are adopted to carry out boundary refinement on the candidate sections, and period starting and ending points are dynamically adjusted; 4, performing time normalization processing: performing time normalization processing on the periodic signals obtained by cutting; according to the method, on the premise that the operation speed and the real-time performance are guaranteed, accurate pulse wave period cutting is achieved; the boundary refinement strategy can effectively reduce the missing cutting phenomenon and ensure the data integrity; the system is simple in structure and can be conveniently realized in a low-power-consumption or embedded system.

Description

Technical Field

[0001] The present invention relates to the technical field of physiological signal processing, in particular to a rapid pulse wave cycle cutting algorithm. Background Art

[0002] Currently available public literature lacks a unified and standardized pulse wave signal segmentation technique. However, in the field of physiological signal processing, moving average filtering and trend detection are widely used for preliminary signal segmentation. These traditional methods are favored for their simplicity and high computational speed. However, when signal boundaries are not clear and distinct, these methods often lead to inaccurate segmentation, resulting in missed segments, which can negatively impact data integrity and subsequent analysis. Summary of the Invention

[0003] The purpose of the present invention is to provide a fast pulse wave cycle cutting algorithm to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solution: a rapid pulse wave cycle cutting algorithm, comprising the following steps:

[0005] Step 1: Signal preprocessing: Perform moving average filtering on the original pulse wave signal;

[0006] Step 2: Trend detection and candidate segment determination: Based on the local trend detection after signal smoothing, the starting time of the rising branch of each cycle is determined to form the candidate segment of the cycle;

[0007] Step 3: Boundary refinement and dynamic adjustment: Use local extreme value detection and slope comparison to refine the boundaries of candidate segments and dynamically adjust the cycle start and end points;

[0008] Step 4: Time normalization processing: Perform time normalization processing on the periodic signal obtained by cutting.

[0009] Preferably, after the moving average filtering preprocessing in step 1, a preliminary smoothed signal is obtained.

[0010] Preferably, the boundary refinement step in step three is to achieve dynamic adjustment based on the detection of local extreme values of the signal in the candidate segment and the comparison of slopes of adjacent sampling points.

[0011] Preferably, the step four specifically includes comparing the local extreme values and slopes of the signal within the candidate segment, and dynamically adjusting the start and end positions of the cycle; normalizing the data of each cycle, and unifying the start time of each cycle.

[0012] Compared with the prior art, the present invention has the following beneficial effects:

[0013] The present invention realizes relatively accurate pulse wave cycle cutting while ensuring operation speed and real-time performance; the boundary refinement strategy can effectively reduce missed cutting and ensure data integrity; the structure is simple and easy to implement in low-power or embedded systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0015] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0016] See also Figure 1 The present invention provides a rapid pulse wave cycle cutting algorithm, comprising the following steps:

[0017] Step 1: Signal preprocessing: Perform moving average filtering on the original pulse wave signal to obtain a preliminary smoothed signal;

[0018] Step 2: Trend detection and candidate segment determination: Based on the local trend detection after signal smoothing, the starting time of the rising branch of each cycle is determined to form the candidate segment of the cycle;

[0019] Step 3: Boundary refinement and dynamic adjustment: Local extreme value detection and slope comparison are used to refine the boundaries of the candidate segments and dynamically adjust the cycle start and end points. The boundary refinement step is based on the detection of local extreme values of the signal within the candidate segment and the comparison of the slopes of adjacent sampling points to achieve dynamic adjustment.

[0020] Step 4: Time normalization: Perform time normalization on the periodic signal obtained by cutting. Specifically, within the candidate segment, compare the local extreme values and slopes of the signal, and dynamically adjust the start and end positions of the cycle; normalize the data of each cycle to unify the start time of each cycle.

[0021] A fast pulse wave cycle cutting algorithm is suitable for real-time pulse wave monitoring and online data preprocessing scenarios.

[0022] Example 1:

[0023] Preprocessing and candidate segment extraction:

[0024] Perform moving average filtering on the original signal to detect local trend changes, determine the starting time of the rising branch of each cycle, and form the candidate cycle segments.

[0025] Example 2:

[0026] Boundary refinement and time normalization:

[0027] In the candidate segment, the local extreme values and slopes of the signal are compared, and the start and end positions of the cycle are dynamically adjusted;

[0028] Normalize the data of each cycle and unify the starting time of each cycle.

[0029] During specific use, users can select an appropriate filter window size based on the characteristics of the actual pulse wave signal to balance signal smoothness and detail retention. During the trend detection phase, the algorithm can automatically identify the rising edge of the pulse wave, effectively distinguishing the starting points of different cycles and reducing misjudgments. During the boundary refinement process, combined with local extreme value detection and slope information, the algorithm can accurately define the boundaries of each pulse wave cycle, further improving cutting accuracy. Time normalization processing ensures the temporal consistency of all periodic signals, facilitating subsequent analysis and comparison. In practical applications, the algorithm has demonstrated high stability and accuracy, providing strong support for in-depth analysis of pulse wave signals.

[0030] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A fast pulse wave cycle cutting algorithm, characterized by: The following steps are involved: Step 1: Signal preprocessing: Perform moving average filtering on the original pulse wave signal; Step 2: Trend detection and candidate segment determination: Based on the local trend detection after signal smoothing, the starting time of the rising branch of each cycle is determined to form the candidate segment of the cycle; Step 3: Boundary refinement and dynamic adjustment: Use local extreme value detection and slope comparison to refine the boundaries of candidate segments and dynamically adjust the cycle start and end points; Step 4: Time normalization processing: Perform time normalization processing on the periodic signal obtained by cutting.

2. A rapid pulse wave cycle cutting algorithm according to claim 1, characterized in that: After the moving average filtering preprocessing in step 1, a preliminary smoothed signal is obtained.

3. The rapid pulse wave cycle cutting algorithm according to claim 1, characterized in that: The boundary refinement step in step three is to achieve dynamic adjustment based on the detection of local extreme values of the signal in the candidate segment and the comparison of slopes of adjacent sampling points.

4. The rapid pulse wave cycle cutting algorithm according to claim 1, characterized in that: Specifically, the fourth step is to compare the local extreme values and slopes of the signal within the candidate segment, and dynamically adjust the start and end positions of the cycle; and normalize the data of each cycle to unify the start time of each cycle.

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