TWI835335B - Interactive heart rate variability analysis parameter model and index generation system - Google Patents

Abstract

The invention discloses an interactive heart rate variability analysis parameter model and index generation system, and a customizable index and index interval according to the parameter combination. The interactive heart rate variability analysis parameter model and index generation system includes an input unit, a processing unit and a display unit. The input unit receives a physiological data related to a degree of change in heart rate. The processing unit is connected to the input unit. The processing unit executes an application program to generate an analytical parametric model with at least one median from the plurality of physiological data. The application calculates parameters from the physiological data, such as at least one of a standard deviation of the heartbeat distance (SDNN), a low frequency (LF), a high frequency (HF), or a very low frequency (VLF). The application uses the data of at least one of the heartbeat interval standard deviation, low frequency, high frequency and very low frequency to generate a corresponding complex index. Among them, the analytical parameter model is based on the physiological data of a specific population. The display unit is connected to the processing unit to display project indicators related to the parameters.

Description

Interactive heart rate variability analysis parameter model and indicator generation system

The present invention relates to the technical field of heart rate variability. It is an interactive heart rate variability analysis parameter model and index generation system to assist doctors (or experts) in establishing analysis parameter models of different countries or different races and to assist doctors (or experts) through clinical Ask about the autonomic nervous system-related indicators customized by the clinic.

Modern people's lives are too stressful. Long-term accumulation of stress will cause the body to release too much steroids and adrenaline, thus damaging the autonomic nervous system (ANS), causing an imbalance of the sympathetic and parasympathetic nerves in the system, leading to dizziness and chest tightness. Symptoms such as heart palpitations, headaches, irritability, excessive tension and anxiety are medically called "autonomic nervous system disorders"; autonomic nervous system disorders are used to describe physical symptoms that are difficult to explain by physiological reasons. According to the current medical definition, autonomic nervous system disorders Disorder is a mental illness with relatively mild symptoms. According to recent medical research, about 30% of the population in Europe and the United States and more than 20% of the population in Taiwan have suffered from the pain caused by autonomic nervous system disorder. It is currently a common term It is called "sub-health"; sub-health refers to the physical or psychological state that is in the fuzzy zone between health and disease. It is a dynamic change. If ignored, it may develop into a disease. If it is improved in time, it can be restored to a healthy state.

Traditionally, heart rate variability (HRV) analysis is a method of measuring the degree of changes in continuous heart rate. HRV measurement is a common method to evaluate whether the autonomic nervous system function is normal or not because it is non-invasive, fast and convenient. . This measurement method is also widely used in the assessment of psychological or physiological stress. The most commonly used calculation method is that each heart cycle (heart cycle) in the electrocardiogram (ECG) can be divided into the sum of multiple waves. namely P, Q, R, S and T. Another important feature of the electrocardiogram is the duration of the cardiac cycle. These are measured based on the length of the RR interval (i.e. the distance between consecutive R peaks) and are usually measured by measuring the individual heart ( The variables of heart rate (HR) and variability are summarized into a set of numbers, which are then further calculated and analyzed. The autonomic nervous system detector currently used clinically uses heart rate variability to analyze the state of autonomic nervous system balance.

The method and equipment for determining a fatigue index disclosed in the Republic of China Patent Publication No. TW202211868A mainly include receiving physiological signals; generating a plurality of heart rate variability parameters based on the physiological signals; and based on the plurality of heart rate variability parameters. Parameters can be used to determine the fatigue index, but it can only display the fatigue index, and does not allow experts to use relevant parameters to customize the index through this patent.

The Republic of China Patent Publication Announcement No. TWI670046B discloses a measuring device and method for both psychological stress index examination and blood pressure examination. When the measuring device enters the psychological pressure measurement mode, the pump unit performs variable-speed pressurization of the air bag unit, and when the pressure signal of the pressure sensing unit is determined to be a pulse signal, the microprocessor unit will control the pump unit to stop pressurizing and measure the pulse signal to calculate the psychological pressure. Stress index; and according to the psychological stress index, based on the data of each pulse interval within a period of time, calculate the ratio of the standard deviation of normal and normal RR intervals (SDNN) and the root mean square difference (RMSSD) of consecutive RR intervals, although It can simply judge the autonomic nervous system balance, but it cannot collect population data to generate an analysis parameter model for each age of the population. It can allow the subjects to know their comparative status at the same age and gender. For example, the subject's SDNN is at the median. above or below.

In view of this, the present invention provides an interactive heart rate variability analysis parameter model and index generation system to solve the deficiencies of the previous technology.

The first purpose of the present invention is to provide an interactive heart rate variability analysis parameter model and an index generation system that can customize indicators and index intervals according to parameters. It is a method to quantify the heart rate variability analysis values based on the physiological data of a specific group to establish a parameter model. and define relevant health indicators through an interactive interface. Among them, the specific group may be sub-healthy people, teenagers, etc., and is not limited thereto. As far as sub-healthy people are concerned, sub-healthy people can use the present invention to achieve the goal of improving the SDNN (Standard deviation of NN intervals) generated from the long-term exercise process of sub-healthy people, and enable the corresponding indicators to further achieve Improvement; and, as far as teenagers are concerned, teenagers can detect depression early through the present invention and achieve preventive and therapeutic effects.

In order to achieve the above objects or other objects, the present invention provides an interactive heart rate variability analysis parameter model and index generation system; the interactive heart rate variability analysis parameter model and index generation system include an input unit, a processing unit and a display unit; input The unit receives physiological data related to a degree of change in heart rate. The processing unit is connected to the input unit. The processing unit executes an application program to generate an analytical parameter model with at least a median from the physiological data, and the application program calculates the parameters from the physiological data, such as a standard deviation of beat intervals (SDNN), a low frequency (LF), At least one of a high frequency (HF) or a very low frequency (VLF). The application compares the data of at least one of the parameters to the median of the parameter model to generate the corresponding complex indicator. Among them, the analysis parameter model is established based on the physiological data of a specific group; the display unit is connected to the processing unit to display project indicators related to these parameters.

Further, it further includes an acquisition unit connected to the input unit, and the acquisition unit is used to acquire the physiological data of the heart, wherein the acquisition unit acquires the heart rate change degree within a predetermined time.

Further, the degree of change in the heart rate is obtained based on a heart rate variability analysis method.

Further, the application provides a plurality of the analysis parameter models, and the analysis parameter models have corresponding medians, and the corresponding project indicators are generated according to at least one of the parameters, and the project indicators are based on the threshold value at the and other project indicators to define their indicator ranges.

Furthermore, the application also includes a user interface through which doctors can select individual or multiple project indicators. The project indicators are mental status, physical status, emotional stability, stress, mental fatigue and physical health. At least one of fatigue, stress accumulation, long-term stress, day and night sleep status, dream quality and sleep depth, or the doctor can customize the indicator and its indicator range based on a combination of parameters.

Furthermore, the application further includes a custom indicator module, which selects one or more of the parameters to create a custom indicator, and the custom indicator also provides a custom threshold to define its indicator. interval.

Further, the application further includes an adjustment module to adjust the threshold, and a warning module. The application compares the parameters of the heartbeat interval standard deviation, the low frequency, the high frequency and the ultra-low frequency to the analysis parameters. After the median of the model, when the parameter is different from the median, the warning module generates a warning message.

Compared with the prior art, the present invention provides an interactive heart rate variability analysis parameter model and an indicator generation system, as well as customizable indicators and their indicator intervals, which allows experts to collect the heart rate variability of specific groups of people and define the median of each parameter. number (excluding extreme values) and further customize the indicator according to the combination of parameters.

In order to fully understand the purpose, characteristics and effects of the present invention, the present invention is described in detail through the following specific embodiments and the accompanying drawings, as follows:

In the present invention, “a” or “an” is used to describe the units, elements and components described herein. This is done for convenience of explanation only and to provide a general sense of the scope of the invention. Accordingly, unless it is obvious otherwise, such description should be understood to include one, at least one, and the singular also includes the plural.

As used herein, the terms “includes,” “includes,” “has,” “contains,” or any other similar term are intended to cover a non-exclusive inclusion. For example, an element, structure, article or device containing plural elements is not limited to the elements listed herein, but may include elements not expressly listed but that are generally inherent to the element, structure, article or device. Other requirements. Otherwise, unless expressly stated to the contrary, the term "or" means an inclusive "or" and not an exclusive "or".

Please refer to FIG. 1 , which is a block diagram of an interactive heart rate variability analysis parameter model and index generation system according to an embodiment of the present invention. In FIG. 1 , the interactive heart rate variability analysis parameter model and index generation system 10 includes an input unit 12 , a processing unit 14 and a display unit 16 .

Please refer to Figure 2, which is a block diagram of an interactive heart rate variability analysis parameter model and index generation system according to another embodiment of the present invention; the input unit 12 receives a physiological data BD related to a heart rate variation degree; here, The degree of change in heart rate is obtained based on the method of heart rate variability analysis.

In another embodiment, the input unit 12 can acquire the physiological data BD of the subject's heart through the acquisition unit 18. For example, the acquisition unit 18 may include electrode pads, amplification circuits, signal processing circuits, and analog-to-digital conversion circuits. Etc., the acquisition unit 18 can obtain the subject's corresponding electromyographic signal through the electrode pads; it is worth noting that the degree of change in the heart rate can also be obtained based on the heart rate variability analysis method. For example, the heart rate variability analysis calculation method is mainly Analyze the time series of heartbeats and heartbeat intervals obtained through electrocardiogram or pulse measurement, such as the R wave peak in the electrocardiogram, by measuring the time interval between two R wave peaks, and then using the discrete Fourier transform to convert the heartbeat interval The time series is converted into the frequency domain and expressed in the form of power spectrum density or spectrum distribution. Generally, spectrum analysis of heart rate variability signals requires stable recording performance of 200 to 500 consecutive heartbeat intervals, so a recording time is required, such as 2 minutes; the frequency of the heartbeat interval spectrum appears below 1Hz, and several peaks can mainly be found in the range of 0 to 0.4Hz.

The processing unit 14 is connected to the input unit 12; the processing unit 14 executes an application program APP to calculate and generate an analytical parameter model AIM with at least a median MD by removing extreme values from the physiological data BD of each age of a specific group. The application APP calculates complex parameters from the physiological data BD, such as a standard deviation of heartbeat intervals (SDNN), a low frequency (LF), a high frequency (HF) or a very low frequency (VLF) or a combination of the above data, such as low frequency ( The ratio of LF) to high frequency (HF) (LF/HF), the percentage of low frequency (LF) in high frequency (HF) plus low frequency (LF) (LF%), etc., among which the standard deviation of the heartbeat interval is clinically The significance can be represented by the overall activity of the autonomic nervous system. The low-frequency frequency band can range from 0.04 Hz to 0.15 Hz. The clinical significance can be represented by the activity of the sympathetic and parasympathetic nerves. The high-frequency frequency band can range from 0.15 Hz. to 0.4 Hz and can represent the activity of parasympathetic nerves in clinical significance. The frequency used in the ultra-low frequency range is ≦0.04 Hz, and the ratio of low frequency (LF) to high frequency (HF) (LF/HF) is The clinical significance can be represented by the balance of autonomic nervous system activity; it is worth noting that the number of analysis parameter models AIM and median MD can be one or more, and the application APP can select one or more from multiple analysis parameter models AIM Multiple models, and each analysis parameter model AIM has its corresponding median MD, and the median MD can also be different according to the parameters PT; here, the analysis parameter model AIM is based on the physiological characteristics of a specific group. Established by data BD, the specific group can be 100 athletes, 50 elderly people over 65 years old, 20 young adults aged 30 to 50, 30 primary school students, etc. For example, use 50 18-year-old boys LF is calculated by experts based on their clinical diagnosis and removing extreme values through a user interface UI to help doctors generate the analytical parameter model AIM of these 18-year-old boys, the most important of which is the median MD.

In another embodiment, the processing unit 14 executes the application APP, and compares the analysis parameter model AIM with at least one of the parameters PT to generate the corresponding project index IDX and its index interval, and the doctor can use the user interface UI to select Individual or multiple project indicators IDX or custom indicators M1 and their indicator ranges. For example, project indicators IDX can be mental status, physical status, mood stability, stress tension, mental fatigue and physical fatigue, stress accumulation, and long-term stress. , at least one of day and night sleep state, dream quality and sleep depth, or the doctor can customize the indicator and its indicator range according to the parameter combination; the project indicator IDX uses the threshold VL to define its indicator range in the project indicator IDX, and is carried out in a situation Note that "cardiac status", one of the project indicators IDX, measures the standard deviation of the heartbeat distance (SDNN). If the median of the analysis parameter model AIM is defined as "normal", it will be about 10 higher than the median MD. A percentage above the median MD can be displayed as "upset and irritable" on the threshold VL, and a value below about 10 percentage points below the median MD can be displayed as "frustrated" on the threshold VL.

In another embodiment, the application APP further includes a custom indicator module M1, which selects one or more parameters PT to create a custom indicator M1, and the custom indicator module M1 also provides customized The threshold defines the indicator range in the custom indicator. The doctor can use the user interface UI to customize the indicator and the indicator range. For example, in the custom indicator module M1, set the custom indicator to "cardiac status", and use these parameters to PT selects the standard deviation of heartbeat intervals (SDNN). If the median of the analysis parameter model AIM is defined as "normal", then it is about 15 percentage points higher than the median MD and can be set on the custom threshold VL to display as "Upset and irritable", which is about 15 percentage points lower than the median MD, can be set on the customized threshold VL to be displayed as "frustrated".

In another embodiment, the application APP further includes an adjustment module M2 to adjust the threshold VL, and a warning module M3. In the application APP, the standard deviation of the heartbeat interval, the low frequency, the high frequency or the After the ultra-low frequency parameters are compared with the median MD of the analysis parameter model AIM, when the parameter is different from the median MD, the warning module M3 generates a warning message.

The display unit 16 is connected to the processing unit 14 to display the project index IDX related to the parameters PT.

Please refer to Figure 3, which is a threshold diagram of an interactive heart rate variability analysis parameter model and indicator generation system according to an embodiment of the present invention. The threshold VL can be represented graphically, such as a fan shape, a circle, a triangle, etc., and can Distinguish the indicator range defined by the project indicator IDX. For example, "mental state" is the project indicator IDX. When the threshold VL displays "upset and irritable", the pointer will be in the red range.

In another embodiment, the standard deviation of heartbeat intervals (SDNN) of a young male is displayed as 53.2, and below it is displayed a multiple of the difference between the young male and the SDNN of the specific ethnic group, such as 1.95, and the project indicator IDX is displayed on the display unit 16 And the threshold VL. For example, if the "mental status" of the project indicator IDX shows that the threshold VL is "normal range", the pointer will be in the blue section.

The present invention has been disclosed above with preferred embodiments. However, those skilled in the art should understand that the embodiments are only used to illustrate the present invention and should not be interpreted as limiting the scope of the present invention. It should be noted that any changes and substitutions that are equivalent to this embodiment should be considered to be within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the scope of the patent application.

10: Interactive heart rate variability analysis parameter model and indicator generation system

12:Input unit

14: Processing unit

16:Display unit

18: Capture unit

APP: application

BD: physiological data

MD: median

AIM: Analytical Parametric Model

PT: parameters

IDX: project indicator

VL: threshold

UI: User interface

M1: Custom indicator module

M2: Adjustment module

M3: Alert module

Figure 1 is a block diagram of an interactive heart rate variability analysis parameter model and index generation system according to an embodiment of the present invention; Figure 2 is a block diagram of an interactive heart rate variability analysis parameter model and index generation system according to another embodiment of the present invention; Figure 3 is a threshold diagram of an interactive heart rate variability analysis parameter model and index generation system according to another embodiment of the present invention.

10: Interactive heart rate variability analysis parameter model and indicator generation system

12:Input unit

14: Processing unit

16:Display unit

Claims (8)

An interactive heart rate variability analysis parameter model and index generation system includes: an input unit that receives physiological data related to the degree of change in heart rate; a processing unit that is connected to the input unit, and the processing unit executes an application program to The physiological data of each age group of a specific group is calculated and an analytical parameter model with at least a median is generated. The application calculates complex parameters from the physiological data, such as standard deviation of heartbeat intervals (SDNN), low frequency (LF) and at least one of high frequency (HF), VLF (very low frequency) or a combination, and the application assists experts to compare parameters of at least one of the standard deviation of the heartbeat interval, the low frequency, the high frequency and the ultra-low frequency, etc. The median of the analysis parameter model is used to generate corresponding complex indicators and their index intervals, wherein the analysis parameter model is established based on the physiological data of a specific group; the display unit is connected to the processing unit to display information related to the Project indicators of such parameters, wherein the processing unit executes the application program to allow the analysis parameter to generate a corresponding project indicator based on at least one of the parameters, and the project indicator defines its indicator among the project indicators through a threshold interval, the application also includes a user interface through which the doctor can select individual or multiple project indicators, and the doctor can customize the indicators and their indicator ranges based on the parameter combination, and the project indicators are heart rate, At least one of physical condition, mood stability, stress intensity, mental fatigue and physical fatigue, stress accumulation, long-term stress, day and night sleep status, dream quality and sleep depth. The interactive heart rate variability analysis parameter model and index generation system as described in claim 1 further includes an acquisition unit connected to the input unit, and the acquisition unit is used to acquire the physiological data of the heart. The interactive heart rate variability analysis parameter model and index generation system as described in claim 2, wherein the acquisition unit acquires the heart rate variation degree within a predetermined time. The interactive heart rate variability analysis parameter model and index generation system as described in claim 1 or 2, wherein the heart rate variation degree is obtained based on the heart rate variability analysis method. The interactive heart rate variability analysis parameter model and indicator generation system as described in claim 1, wherein the application provides a plurality of the analysis parameter models, and the analysis parameter models have corresponding medians. The interactive heart rate variability analysis parameter model and indicator generation system as described in request item 1, wherein the application further includes a custom indicator module, which selects one or more from the parameters to create a custom indicator, and the Custom indicators also provide custom thresholds to define the indicator range within the custom indicator. The interactive heart rate variability analysis parameter model and indicator generation system as described in claim 1, wherein the application further includes an adjustment module to adjust the threshold. The interactive heart rate variability analysis parameter model and indicator generation system as described in request item 1, wherein the application further includes a warning module, and the application program combines the standard deviation of the heartbeat interval, the low frequency, the high frequency and the ultra-low frequency. After the parameter is compared with the median of the analysis parameter model, when the parameter is different from the median, the warning module generates a warning message.