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Method and device for acquiring heart rate variation characteristic parameter

A technology of heart rate variability and characteristic parameters, applied in the field of signal processing, can solve the problems that characteristic parameters cannot reflect the position relationship of the main peak, and cannot accurately reflect the shape of heart rate variability, and achieve accurate physiological and psychological significance, good metric evaluation. Effect

Inactive Publication Date: 2011-10-19
李红锦
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Problems solved by technology

Therefore, this method only focuses on the frequency position of the main peak, but does not distinguish the frequency positions of other secondary peaks, so that the calculated characteristic parameters cannot reflect the positional relationship between the main peak and other secondary peaks, and thus cannot accurately reflect Morphology of Heart Rate Variability

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  • Method and device for acquiring heart rate variation characteristic parameter
  • Method and device for acquiring heart rate variation characteristic parameter
  • Method and device for acquiring heart rate variation characteristic parameter

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Embodiment 1

[0035] see figure 1 , which is a flowchart of an embodiment of a method for obtaining heart rate variability characteristic parameters of the present invention, the method includes the following steps:

[0036] Step 101: Calculate and obtain the heart rate variability signal in the time domain according to the physiological signal of the human body;

[0037] For example, any method in the prior art may be used to collect necessary human physiological signals, and then the heart rate variability signal in the time domain is calculated according to the collected human physiological signals. Wherein, the physiological parameter of the human body may be a pulse wave signal of the human body, and may also be an electrocardiographic signal of the human body.

[0038] For example, the execution process of this step will be described in detail below by taking the pulse wave signal of the human body as an example and obtaining the heart rate variability signal in the time domain from ...

Embodiment 2

[0062] In some cases, the distribution of the power spectrum subsequence is concentrated in the very low frequency (VLF, Very Low Frequency) part. Since the very low frequency part is at the edge of the entire power spectrum subsequence, its concentrated distribution is not a true peak distribution and does not represent heart rate variability. The periodic changes of the form, therefore, the characteristic parameters at this time need to be corrected. The difference between this embodiment and Embodiment 1 lies in: judging whether the distribution of the power spectrum subsequence is concentrated in the extremely low frequency part, and if so, further correcting the dedimensionalized characteristic parameters. see Figure 6 , which is a flow chart of another embodiment of a method for obtaining characteristic parameters of heart rate variability in the present invention. Specifically include the following steps:

[0063] Step 601: Calculate and obtain the heart rate variabi...

Embodiment 3

[0077] The preferred implementation scheme for acquiring characteristic parameters is described in detail below. see Figure 7 , which is a flowchart of an embodiment of a method for obtaining heart rate variability characteristic parameters of the present invention, including the following steps:

[0078] Step 701: Using an infrared photoelectric sensor to collect pulse wave signals from the subject;

[0079] In addition, ECG signals can also be collected from the subject.

[0080] Step 702: Determine the reference zero point of the pulse wave signal;

[0081] For example, collect the pulse wave signal for 5 seconds as a reference signal, and extract several peak points T from the reference signal 1，2，…，n and several valley points B 1，2，…，n , calculate the average T of all peak points Avg and the mean B of all valley points Avg , take T Avg and B Avg The median value (T Avg +B Avg ) / 2 as the reference zero point P for calculating the heartbeat interval 0 .

[0082...

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Abstract

The embodiment of the invention discloses a method and device for acquiring a heart rate variation characteristic parameter. The method comprises the following steps of: calculating and obtaining a heart rate variation signal in a time domain according to a human physiological signal; carrying out time-frequency conversion on the heart rate variation signal in the time domain, and selecting a power spectrum subsequence reflecting heart rate variation from a converted power spectrum sequence according to a frequency characteristic of the heart rate variation; accumulating power values at frequency points upwards from a lowest frequency point of the power spectrum subsequence, and accumulating power values at frequency points downwards from a highest frequency point to obtain a first frequency point when the ratio of the accumulated power value to the total power value is more than a low frequency search ratio and a second frequency point when the ratio of the accumulated power value to the total power value is more than a high frequency search ratio; and obtaining the difference between the second frequency point and the first frequency point to obtain the frequency band width of the power spectrum subsequence, and the frequency band width is the characteristic parameter. According to the embodiment of the invention, the characteristic parameter can reflect periodic variation of the heart rate variation and also can reflect a position relationship between a main peak value and a secondary peak value.

Description

technical field [0001] The invention relates to the technical field of signal processing, in particular to a method and device for acquiring heart rate variability characteristic parameters. Background technique [0002] Heart Rate Variability (HRV) signal refers to the instantaneous change of heart rate between consecutive heartbeats. At present, when analyzing heart rate variability, time-domain analysis and frequency-domain analysis are mainly used to obtain characteristic parameters reflecting the shape of heart rate variability, and the two methods can obtain different characteristic parameters respectively. [0003] In the 134th issue of the journal "Swiss Medical Weekly" in 2004, an article "Heart rate variability: a noninvasive electrocardio graphic method to measure the automatic nervous system" was published, in which the time domain analysis method and the frequency domain analysis method were analyzed. introduced. Among them, the time-domain analysis method is ...

Claims

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Application Information

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IPC IPC(8): A61B5/024
Inventor 李闯唐峰李孜博
Owner 李红锦
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