TWI657795B - Unconstrained blood pressure measuring device and blood pressure measuring method using same - Google Patents

Abstract

An unconfined blood pressure measuring device comprises an electrocardiogram sensor, a heart impact map sensor and a measuring host. In operation, the user mainly inputs the physiological state data in the measuring host, and then uses the electrocardiogram sensing And the heart impact map sensor respectively senses the user's ECG signal and the heart impact map signal, and the signal is processed by the measurement host, and then the measurement host will process the result according to the sensing signal and the physiological input by the user. The status data is used to calculate the blood pressure, and finally the calculation result is output to the user to understand his or her physiological state. Therefore, the unconfined blood pressure measuring device of the present invention mainly uses the user's electrocardiogram signal and the heart impact map signal to match the physiological state data of the user, so that the user can measure the blood pressure without being restrained.

Description

Unconstrained blood pressure measuring device and blood pressure measuring method using same

The present invention relates to a blood pressure measurement technique, and more particularly to an unconstrained blood pressure measurement device and a blood pressure measurement method using the same.

Hypertension is one of the most common diseases in today's society. In addition to being proven to cause arteriosclerosis, it also damages organs such as the heart, brain, kidneys and retina, which can cause heart, cerebrovascular disease or renal disease. And other issues. However, general hypertensive patients usually have no symptoms, and it is often too late to find that the complications cause significant harm to the body. Therefore, long-term home blood pressure monitoring is conducive to the diagnosis of early hypertension, which is very important for health maintenance.

Long-term home blood pressure monitoring Due to the limitations of medical equipment, the applicable method is non-invasive blood pressure measurement technology. The most commonly used non-invasive blood pressure measurement methods are auscultation and oscillometry, the former is often used for clinical diagnosis, the latter is the most common method of electronic sphygmomanometer, the common point of these two methods is that the subject needs to wear A compression device (such as an inflatable cuff) pressurizes the arm or other limb to measure the pressure on the arterial vessel by external pressure, but during the measurement process, the pressure of the compression device needs to be large enough The blood flow is completely prevented, which inevitably causes discomfort to the subject. In order to obtain better comfort for the subject to measure blood pressure, the unconstrained blood pressure monitoring method without wearing a pressurizing device has been studied for many years.

Unrestrained blood pressure monitoring techniques There are many, one approach is to use highly correlated with the physiological parameter to be estimated blood pressure value, for example, pulse wave velocity (Pulse wave velocity, PWV) and the pulse wave transit time (Pulse transittime, PTT). PWV is the speed at which pulse waves are transmitted in the arteries. Its high correlation with blood pressure has been discovered as early as the 1920s. As for PTT, the time difference between the two points of the pulse wave reaching the arterial blood vessel (usually the aortic valve and the finger) The distance between the two points is divided by the PTT to obtain the PWV , and then the relationship between PTT and blood pressure can be obtained by the Moens-Korteweg equation, the Bramwell-Hill equation or other fluid mechanics equations.

In recent years, in addition to the use of electrocardiogram (ECG) and photoplethysmography (PPG) for the measurement of PTT, some studies have begun to use the heart impact map (Ballistocardiogram, BCG), which is different from ECG. Potential signals, BCG shows physiological signals directly related to cardiac motion, so the relationship between BCG and other physiological signals can also be used to estimate blood pressure or other cardiovascular related parameters.

For the conventional technique of estimating blood pressure using physiological parameters related to BCG, for example, the invention disclosed in the Chinese Patent Publication No. CN104114084 is a monitoring system using an all-optical method, and the embodiment is to use a BCG signal instead of the ECG signal, and then add The PPG signal is used to estimate the PTT, and the systolic and diastolic blood pressures are calculated. In addition, the invention disclosed in U.S. Patent No. 8,983,854 discloses physiological information such as a heart rate, a standardized normalized stroke volume force, a blood pressure, and an abnormal balance in a non-binding condition in the form of a weight scale. Instead of using PTT, the invention uses the time interval between the R wave of the ECG signal and the J wave of the BCG signal (hereinafter referred to as the RJ interval) to calculate the blood pressure.

However, it can be found from the aforementioned conventional patent that unless a specific subject is used, the measurement result using a single parameter (for example, PTT or RJ interval) has a problem of insufficient accuracy.

The main object of the present invention is to provide an unconstrained blood pressure measuring device which allows a subject to perform blood pressure estimation in a comfortable and relaxed state, and can effectively improve measurement accuracy.

In order to achieve the above object, the unconstrained blood pressure measuring device of the present invention comprises an electrocardiogram sensor, a heart impact map sensor and a measuring host. The ECG sensor is configured to send an ECG signal to a user for contact sensing; the heart impact map sensor is configured to send a heart beat signal to the user for contact sensing; the measuring host has an input unit a signal processor, a computing unit and an output unit, wherein the input unit is configured to input a physiological state data to the user, and the signal processor is coupled to the electrocardiogram sensor and the cardiac impact map sensor for Processing the electrocardiogram signal sensed by the electrocardiograph sensor and the heart impact signal sensed by the heart impact map sensor to the user, the computing unit is connected to the input unit and the signal processor, and is mainly used Calculating the blood pressure of the user according to the physiological state data input by the user in the input unit and the processing result of the signal processor, and the output unit is connected to the calculating unit for outputting the calculation result of the calculating unit to the use People understand their own physiological state.

It can be seen from the above that the unconstrained blood pressure measuring device of the present invention allows the user to measure the ECG signal and the heart impact signal of the user in an unconstrained state, and then match the physiological input of the user. Status data to calculate the blood pressure of the user.

A second object of the present invention is to provide a blood pressure measuring method using the above-mentioned unconstrained blood pressure measuring device, in which the user first inputs the physiological state data of the user by using the input unit, and then causes the user to touch the electrocardiogram feeling. The sensor and the heart impact map sensor enable the electrocardiogram sensor and the heart impact map sensor to respectively sense the ECG signal and the heart impact map signal of the user, and the signal processing is performed by the signal processor And calculating, by the calculating unit, the blood pressure of the user according to the physiological state data input by the user and the processing result of the signal processor, and finally outputting the calculation result of the calculating unit to the user as a reference by the output unit . Therefore, the blood pressure measurement method of the present invention mainly selects an appropriate calculation formula to estimate systolic blood pressure and diastolic blood pressure according to physiological state data of different users.

The detailed construction, features, assembly or use of the unconfined blood pressure measuring device provided by the present invention will be described in the detailed description of the following embodiments. However, it should be understood by those of ordinary skill in the art that the present invention is not limited by the scope of the invention.

10‧‧‧Unconstrained blood pressure measuring device

20‧‧‧ECG sensor

22‧‧‧ECG signal

30‧‧‧heart impact map sensor

32‧‧‧ Heart impact map signal

40‧‧‧Measurement host

42‧‧‧Input unit

44‧‧‧Signal Processor

46‧‧‧Computation unit

48‧‧‧Output unit

50‧‧‧Base

52‧‧‧ column

54‧‧‧Ranging module

Fig. 1 is a schematic view showing the structure of an unconstrained blood pressure measuring device of the present invention.

Fig. 2 is a block diagram of the unconfined blood pressure measuring device of the present invention.

Figure 3 is a flow chart of the blood pressure measurement method of the present invention.

Figure 4 is a waveform diagram of the ECG signal and the heart impact signal.

Figure 5A is a graphical representation of a linear regression analysis of predicting systolic blood pressure in men and women by conventional methods.

Figure 5B is a graphical representation of a linear regression analysis of male and female diastolic blood pressure predicted by conventional methods.

Fig. 6A is a graph showing the error analysis of the male systolic blood pressure and the actual value by the blood pressure measurement method of the present invention.

Fig. 6B is a graph showing the error analysis of the male blood pressure and the actual value of the blood pressure measurement method of the present invention.

Fig. 7A is a graph showing the error analysis of the blood pressure measurement method for predicting female systolic blood pressure and actual value.

Fig. 7B is a graph showing the error analysis of the predicted diastolic blood pressure and the actual value of the blood pressure measurement method of the present invention.

Referring to FIGS. 1 and 2 , the unconfined blood pressure measuring device 10 of the present invention includes a two-cardiogram sensor 20 , a heart impact map sensor 30 , and a measuring host 40 .

The electrocardiogram sensor 20 is mainly used to directly contact the skin of the user to obtain an electrocardiogram signal. The electrocardiogram sensor 20 is in the form of a grip in the present embodiment for the user's hand to hold, and the electrocardiogram signal of the I lead in the standard 12 lead is measured by the electrode disposed on the surface. In terms of electrode configuration, it can be changed depending on the electrocardiograph instrument or the user's needs. For example, the electrode can use a general dry electrode, a gel electrode or a soft electrode carrier plate, and the lead can be expanded to a standard 12-lead. One or several of the joints with the pressurized limb. In addition, the electrodes can also be placed at other locations where the ECG signal is conveniently measured, such as on a scale to measure the ECG signals of the feet.

The heart impact map sensor 30 is primarily disposed at a location that facilitates measurement of the user's heart impact map signal 32. In this embodiment, the heart impact map sensor 30 is disposed on a base 50 in contact with the user's feet to obtain the user's heart impact map signal 32.

The measuring unit 40 is disposed between a column 52 and connected between the two electrocardiograph sensors 20, and has an input unit 42, a signal processor 44, a calculating unit 46 and an output unit 48, wherein: the input unit 42 For the user to input their own physiological status data, such as gender, age, waist circumference and measurement posture (for example: standing, sitting or lying). The input mode can be transmitted by a keyboard, a button, a touch screen, a voice input or via an Ethernet or wireless network, or can be connected to a memory device, and is selected from previously input materials, and the input interface can include a text interface. Graphical interface or other means.

In addition, the input unit 42 can be simultaneously coupled to a digital height meter and a body weight fat meter, or a body composition analyzer to obtain information such as the height, weight, and body fat ratio of the user. The height measurement method of the digital height gauge can be contact measurement or non-contact measurement. If it is a contact measurement method, such as gauge gauge automatic or manual lift measurement, first set the gauge plate to a fixed height. Then, the gauge plate is moved to the highest part of the user's body, and the height is calculated by linearly adjustable potentiometer, capacitive grid displacement sensor or other means to measure the displacement of the gauge plate on the column 52. If it is a non-contact measurement, a distance measuring module 54 is mainly disposed at a position higher than the height of the user, and the time difference between the transmitted signal and the received signal can be obtained between the highest part of the user's body and the ranging module 54. The distance of the user is the height of the distance measuring module 54 minus this distance. The non-contact height measuring device can be fixed or portable, and the signal used by the distance measuring module 54 can be ultrasonic, infrared or radio.

The signal processor 44 is connected to the electrocardiogram sensor 20 and the cardiac impact map sensor 30, and is mainly used for processing the electrocardiogram signal 22 and the cardiac impact map signal 32, such as amplification and filtering. Waves (including bandpass, band reject filtering, and other filtering methods), as well as noise suppression (such as removing baseline drift or moving artifacts), and then analyzing the resulting two signals.

The calculating unit 46 is connected to the input unit 42 and the signal processor 44 for receiving the data transmitted by the input unit 42 and the signal processed by the signal processor 44, and selecting an appropriate calculation formula to calculate and use according to the received message data. The blood pressure of the person. The computing unit 46 can be in any form, such as a microprocessor, a central processing unit, a mobile computing device, or a remote computing device. In addition, the computing unit 46 and the signal processor 44 can also be integrated into a single IC chip, or can be separately The IC chips perform the processing of the sub-unit functions.

The output unit 48 is connected to the calculation unit 46 for displaying the calculation result of the calculation unit 46 to the user as a reference. The display of output unit 48 includes digital, graphical, voice or other readily identifiable means. The output unit 48 can also be coupled to a memory device and transfer data to a remote device via an Ethernet or wireless network, or to a universal serial bus (USB) or the like. In addition to the systolic and diastolic pressures, the output unit 48 can also output at least one of the following signals, data or results, including an electrocardiogram waveform, a heart beat waveform, and a heart rate.

Before starting to use the unconfined blood pressure measuring device 10 of the present invention, the blood pressure mathematical mode can be established in the measuring host, that is, the age, height, weight, waist circumference and body fat of a plurality of men and women are collected and measured in advance. Rates and heart rate, systolic blood pressure, diastolic blood pressure, ECG signal and heart impact map signal and heart rate obtained in different measurement positions, and then establish a database, and then by statistics or other means (such as neural network or machine learning, etc.) Artificial intelligence), taking systolic and diastolic pressures as dependent variables or target values, and the remaining parameters are independent variables or input parameters, considering different mathematical models under different combinations, or further distinguishing different ethnic groups (For example, different genders, different age groups, different exercise volumes, different races, etc.) corresponding to the preferred blood pressure estimation mathematical model.

As shown in Fig. 3, the blood pressure measurement method of the present invention comprises the following steps:

Step a): Let the user stand on the base 50 and input the physiological state data of the user by using the input unit 42, such as gender, age, height, weight, waist circumference, body fat ratio and measurement posture (for example: standing posture, sitting posture or leaning back) Lying) and other information.

Step b): allowing the user to hold the electrocardiogram sensor 20 with both hands while simultaneously touching the heart impact map sensor 30 with both feet, so that the electrocardiogram sensor 20 and the heart impact map sensor 30 can respectively sense and use The electrocardiogram signal 22 and the heart impact map signal 32 are as shown in FIG. 4, and the signal processor 44 amplifies, filters, and suppresses the electrocardiogram signal 22 and the heart impact map signal 32, and simultaneously detects the electrocardiogram. The R wave of the signal 22 and the I wave and the J wave of the heart impact map signal 32 can obtain the time interval TI and the heart impact map between the heart rate, the R wave of the electrocardiogram signal 22 and the J wave of the heart impact map signal 32. The slope S between the I wave and the J wave of the signal 32.

Step c): The calculation unit 46 selects the most suitable mathematical mode to calculate the blood pressure of the user according to the physiological state data input by the user and the processing result of the signal processor 44. In the present embodiment, the calculation unit 46 classifies by gender and uses a multiple linear regression analysis method to obtain the following equation: (1) SBP _m = C _1m + C _2m × Age + C _3m × H + C _4m × W _e + C _5m × W _a + C _6m × BF + C _7m × HR + C _8m × TI + C _9m × S

(2) DBP _m = C _10m + C _11m × Age + C _12m × H + C _13m × W _e + C _14m × W _a + C _15m × BF + C _16m × HR + C _17m × TI + C _18m × S

(3) SBP _f = C _1f + C _2f × Age + C _3f × H + C _4f × W _e + C _5f × W _a + C _6f × BF + C _7f × HR + C _8f × TI + C _9f × S

(4) DBP _f = C _10f + C _11f × Age + C _12f × H + C _13f × W _e + C _14f × W _a + C _15f × BF + C _16f × HR + C _17f × TI + C _18f × S

Among them, SBP _m is male systolic blood pressure (in millimeters of mercury), SBP _f is female systolic blood pressure (in millimeters of mercury), DBP _m is male diastolic blood pressure (in millimeters of mercury), DBP _f is female diastolic blood pressure (in millimeters of mercury), C _1m ~ C _18m and C _1f ~ C _18f are multiple regression analysis coefficients, Age is age (in years), H is height (in centimeters), and W _e is weight (in Kg), W _a is waist circumference (unit is cm), BF is body fat ratio (unit is percentage), HR is heart rate (unit is sub/min), TI is ECG signal 22 R wave and heart impact map signal 32 The time interval between J waves (in seconds), where S is the slope (in milligrams per second) between the I and J waves of the heart beat signal 32.

In the mathematical modes of (1) to (4) above, there are many variations in the selection of parameters, such as replacing the S with the maximum distance between the I wave and the J wave (that is, the amplitude A), and replacing the body fat with the body fat weight. Ratio, or add different time intervals, such as the time interval between the R wave and the I wave. In addition, when considering the measurement of blood pressure, there are three postures, namely standing, sitting and lying down, then P1 and P2 can be added as virtual variables of the posture. If the standing position is the basic category, P1=1 and P2=0 can be set as sitting posture, P1=0 and P2=1 as lying posture, and then the two variables are added to the analysis to obtain the mathematical mode of blood pressure in different postures.

In order to compare the accuracy of the method of the present invention with the conventional univariate linear regression method, physical measurement information and basic data of 20 male and female females were obtained and verified. In the prior art, firstly, TI was used as an independent variable, and systolic blood pressure and diastolic blood pressure were used as dependent variables. Linear regression analysis was performed on the forty data. Conventional blood pressure gender-specific, it is classified as gender, male obtain the systolic and diastolic blood pressure estimation model R ² of 0.406 and 0.151 respectively; Women's systolic and diastolic blood pressure estimation mode of R ² are both 0.04 As shown in Figures 5A and 5B. From the above analysis, TI has a greater correlation with systolic blood pressure in men, similar to known patents and papers, but not applicable to blood pressure estimation of women participating in this experiment.

Also grouped by gender, using the present invention, four sets of estimation modes are obtained, namely, a male systolic blood pressure and diastolic blood pressure estimation mode and a female systolic blood pressure and diastolic blood pressure estimation mode. After substituting age, height, weight, waist circumference, body fat ratio, heart rate, TI and S into equations (1) and (2), as shown in Figures 6A and 6B, the R ² of the male systolic blood pressure estimation model is 0.868. The estimated standard error is 6.284, and the male diastolic blood pressure estimation model has an R ² of 0.759 and an estimated standard error of 5.106. Similarly, after substituting the above data into formulas (3) and (4), as shown in Figures 7A and 7B, the R ² of the female systolic blood pressure estimation model is 0.850, the estimated standard error is 10.560, and the female diastolic blood pressure estimation mode is obtained. The R ² is 0.741 and the estimated standard error is 8.808. It is apparent that the model of the present invention is more accurate for blood pressure estimation than conventional methods.

In summary, the unconstrained blood pressure measuring device 10 of the present invention allows the user to measure the user's electrocardiogram signal 22 and heart impact map signal 32 without being restrained, comfortable and relaxed. Using the physiological state data input by the user to select the appropriate mathematical mode to calculate the user's blood pressure is very suitable for long-term blood pressure monitoring, and is conducive to early diagnosis and home care of hypertension.

Claims (2)

A blood pressure measuring method using an unconstrained blood pressure measuring device is applied to an unconstrained blood pressure measuring device, wherein the unconfined blood pressure measuring device includes an electrocardiogram sensor for contacting a user Sensing and transmitting an ECG signal; a heart impact map sensor for the user to perform contact sensing and transmitting a heart impact map signal; and a measuring host having an input unit, a signal processor, and a calculation a unit and an output unit, wherein the input unit is configured to input a physiological state data to the user, and the signal processor is connected to the electrocardiogram sensor and the cardiac impact map sensor for processing the generated by the electrocardiogram sensor The ECG signal and the heart impact map signal generated by the heart impact map sensor, the computing unit is connected to the input unit and the signal processor for determining the physiological state data input by the input unit and the signal processor Processing the result to calculate the blood pressure of the user, the output unit is connected to the calculation unit for outputting the calculation result of the calculation unit: the blood pressure measurement method The method comprises: a) inputting, by the user, the physiological state data of the user by using the input unit; b) contacting the user with the electrocardiogram sensor and the cardiac impact map sensor, so that the electrocardiogram sensor and the heart The impact map sensor can respectively sense one of the user's electrocardiogram signal and the one-heart impact map signal, and the signal processor processes the signal; c) the computing unit according to the physiological state data input by the user and the The processing result of the signal processor is used to calculate the blood pressure of the user; d) the calculation result of the calculation unit is output by the output unit; the calculation unit uses one of the multiple linear regression analysis methods to calculate the male blood pressure as follows: SBP _m = C _1m + C _2m × Age + C _3m × H + C _4m × W _e + C _5m × W _a + C _6m × BF + C _7m × HR + C _8m × TI + C _9m × S DBP _m = C _10m + C _11m ×Age+C _12m ×H+C _13m ×W _e +C _14m ×W _a +C _15m ×BF+C _16m ×HR+C _17m ×TI+C _18m ×S Among them, SBP _m is systolic blood pressure (unit is mmHg), DBP _m diastolic blood pressure (in mm Hg), C _1m ~ C _18m multiple regression analysis coefficients, Age is the age (in years), H is the height ( Bits cm), W _e is the weight (in kilograms), W _a waist circumference (in centimeters), BF is a ratio of body fat (in percent), HR is the heart rate (in beats / min), TI electrocardiogram The time interval (in seconds) between the R wave of the signal and the J wave of the heart impact signal, and S is the slope (in milligrams per second) between the I wave and the J wave of the heart impact signal. A blood pressure measuring method using an unconstrained blood pressure measuring device is applied to an unconstrained blood pressure measuring device, wherein the unconfined blood pressure measuring device includes an electrocardiogram sensor for contacting a user Sensing and transmitting an ECG signal; a heart impact map sensor for the user to perform contact sensing and transmitting a heart impact map signal; and a measuring host having an input unit, a signal processor, and a calculation a unit and an output unit, wherein the input unit is configured to input a physiological state data to the user, and the signal processor is connected to the electrocardiogram sensor and the cardiac impact map sensor for processing the generated by the electrocardiogram sensor The ECG signal and the heart impact map signal generated by the heart impact map sensor, the computing unit is connected to the input unit and the signal processor for determining the physiological state data input by the input unit and the signal processor Processing the result to calculate the blood pressure of the user, the output unit is connected to the calculation unit for outputting the calculation result of the calculation unit: the blood pressure measurement method The method comprises: a) inputting, by the user, the physiological state data of the user by using the input unit; b) contacting the user with the electrocardiogram sensor and the cardiac impact map sensor, so that the electrocardiogram sensor and the heart The impact map sensor can respectively sense one of the user's electrocardiogram signal and the one-heart impact map signal, and the signal processor processes the signal; c) the computing unit according to the physiological state data input by the user and the The processing result of the signal processor is used to calculate the blood pressure of the user; d) the calculation result of the calculation unit is output by the output unit; the calculation unit uses one of the multiple linear regression analysis methods to calculate the female blood pressure as follows: SBP _f = C _1f + C _2f × Age + C _3f × H + C _4f × W _e + C _5f × W _a + C _6f × BF + C _7f × HR + C _8f × TI + C _9f × S DBP _f = C _10f + C _11f ×Age+C _12f ×H+C _13f ×W _e +C _14f ×W _a +C _15f ×BF+C _16f ×HR+C _17f ×TI+C _18f ×S where SBP _f is the systolic blood pressure (unit is mmHg), DBP _f diastolic blood pressure (in mm Hg), C _1f ~ C _18f multiple regression analysis coefficients, Age is the age (in years), H is the height ( Bits cm), W _e is the weight (in kilograms), W _a waist circumference (in centimeters), BF is a ratio of body fat (in percent), HR is the heart rate (in beats / min), TI electrocardiogram The time interval (in seconds) between the R wave of the signal and the J wave of the heart impact signal, and S is the slope (in milligrams per second) between the I wave and the J wave of the heart impact signal.