CN113057610B - Dynamic blood pressure measurement calibration method, device and storage medium of wearable equipment - Google Patents
Dynamic blood pressure measurement calibration method, device and storage medium of wearable equipment Download PDFInfo
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- 238000009530 blood pressure measurement Methods 0.000 title claims abstract description 91
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- 238000012937 correction Methods 0.000 claims abstract description 67
- 238000005259 measurement Methods 0.000 claims abstract description 59
- 230000036772 blood pressure Effects 0.000 claims abstract description 19
- 238000001914 filtration Methods 0.000 claims description 10
- 230000007958 sleep Effects 0.000 claims description 9
- 238000004891 communication Methods 0.000 description 8
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- 210000004369 blood Anatomy 0.000 description 1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2560/00—Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
- A61B2560/02—Operational features
- A61B2560/0223—Operational features of calibration, e.g. protocols for calibrating sensors
Abstract
The invention discloses a dynamic blood pressure measurement calibration method of wearable equipment, which comprises the following steps: acquiring first measurement data measured by a medical standard sphygmomanometer and taking the first measurement data as standard data, and acquiring second measurement data measured by a blood pressure measurement module of the wearable equipment; performing discrete calculation on the second measurement data by taking the standard data as a datum point to obtain a discrete calculated current average value; calculating a current correction error parameter according to the current average value; calculating the average value again of the current correction error parameter and the last correction error parameter to obtain a current effective correction error parameter; and correcting the blood pressure value actually measured by using the wearable device by using the current effective correction error parameter. In addition, a dynamic blood pressure measurement calibration device of the wearable device and a storage medium are also provided. According to the technical scheme provided by the invention, the accuracy of dynamic blood pressure measurement of the wearable equipment is improved, and the risk of large error caused by the blood pressure measurement of the wearable equipment is avoided.
Description
Technical Field
The invention relates to the technical field of dynamic blood pressure measurement of wearable equipment, in particular to a method, a device and a storage medium for calibrating dynamic blood pressure measurement of the wearable equipment.
Background
Along with the popularization of intelligent wearing equipment, more and more old people master the blood pressure change of the old people constantly through wearing intelligent wearing equipment, such as a smart watch, and through the dynamic blood pressure measurement of the wearable equipment. The blood pressure measurement of the wearable equipment can be generally performed through a photoelectric sensor, an electrocardiograph method, an oscillography method, a blood oxygen measurement method and the like, so that the current blood pressure condition of the old can be checked in real time, and the blood pressure trend of the old can be further mastered by collecting the blood pressure change of the old; however, in either method, there is a disadvantage of insufficient accuracy and large error, and the blood pressure measurement that is completely dependent on the wearable device often causes misleading to the loss of optimal treatment.
Disclosure of Invention
The invention provides a dynamic blood pressure measurement calibration method, device and storage medium of a wearable device, and aims to solve the problems of insufficient accuracy and large error in blood pressure measurement of the wearable device in the prior art.
In order to achieve the above object, the method for calibrating dynamic blood pressure measurement of a wearable device according to the present invention includes:
step S10: acquiring sleep ending time t1 of the old acquired by the wearable equipment;
step S20: acquiring first measurement data of the current time measured by a medical standard sphygmomanometer and measurement time t2;
step S30: judging whether 1h > (t 2-t 1) >0 is satisfied, executing step S40 when the 1h > (t 2-t 1) >0 is satisfied, otherwise executing step S10;
step S40: taking the first measurement data as standard data, and acquiring second measurement data which are measured by a blood pressure measurement module of the wearable equipment and are continuously repeated; the second measurement data are continuous multiple blood pressure measurement data of the wearable device in a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain a current average value after discrete calculation;
step S60: calculating a current correction error parameter according to the current average value;
step S70: calculating the average value again of the current correction error parameter and the last correction error parameter to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value actually measured by using the wearable device by using the current effective correction error parameter.
Further, the step S50 includes:
step S510: performing discrete filtering on the second measurement data, and filtering out data with maximum discrete property;
step S520: taking the standard data as a datum point, and performing discrete characteristic calculation on the data subjected to discrete filtering;
step S530: and carrying out the average value calculation on the second measurement data subjected to the discrete characteristic calculation.
Further, the average value is calculated as follows:
X′ m ＝(X 1 +X 2 +...X m )/m
wherein:
X′ m representing the average value;
X 1 to X m And representing m second measurement data, wherein m is a natural number.
Further, the discrete characteristic calculation includes the second measurement data being discretely distributed on both sides of the reference point, on the left side of the reference point, and on the right side of the reference point.
Further, in the step S60, the calculation of the current correction error parameter is:
A′ m ＝(X′ m -X 0 )/X′ m
wherein,
A′ m representing a current correction error parameter; m is a natural number;
X 0 representing standard data;
X′ m this average value is shown.
Further, the calculation of the current effective correction error parameter is as follows:
A″ m ＝(X′ m -X′ m-1 )/2
wherein,
A″ m representing a current valid correction error parameter; m is a natural number;
A′ m representing a current correction error parameter;
X′ m-1 indicating the last corrected error parameter.
Further, in the step S80, the correction calculation for correcting the blood pressure value measured by the wearable device by using the current valid correction error parameter is:
Y n ＝X n *(1-A″ m )
wherein,
Y n representing the correction value; n is a natural number;
X n representing the measured value;
A″ m indicating the currently active correction error parameter.
Meanwhile, the invention also provides a dynamic blood pressure measurement calibration device of the wearable device, which comprises a memory and a processor, wherein the memory is stored with a dynamic blood pressure measurement calibration program of the wearable device which can be run by the processor, and the steps of the dynamic blood pressure measurement calibration method of the wearable device are realized when the dynamic blood pressure measurement calibration program of the wearable device is executed by the processor.
In addition, the invention further provides a storage medium, which is a computer readable storage medium, wherein the storage medium stores a dynamic blood pressure measurement calibration program of the wearable device, and the dynamic blood pressure measurement calibration program of the wearable device can be executed by one or more processors to realize the steps of the dynamic blood pressure measurement calibration method of the wearable device.
According to the method, the device and the storage medium for calibrating the dynamic blood pressure measurement of the wearable device, the accuracy of the dynamic blood pressure measurement of the wearable device is improved through the automatic calibration of the dynamic blood pressure measurement of the wearable device, the risk of large errors caused by the blood pressure measurement of the wearable device is avoided, the dynamic blood pressure measurement data of the wearable device has higher reference significance, and the method, the device and the storage medium are non-sensitive to the old or the user, and have good user experience.
Drawings
Fig. 1 is a flow chart of a dynamic blood pressure measurement calibration method of a wearable device according to an embodiment of the present invention;
fig. 2 is a flow chart of step S50 in fig. 1;
fig. 3 is a schematic diagram of an internal structure of a dynamic blood pressure measurement calibration device of a wearable device according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a dynamic blood pressure measurement calibration program module of a wearable device in a dynamic blood pressure measurement calibration apparatus of a wearable device according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an embodiment of the present invention provides a method for calibrating dynamic blood pressure measurement of a wearable device, where the method for calibrating dynamic blood pressure measurement of the wearable device includes:
step S10: acquiring sleep ending time t1 of the old acquired by the wearable equipment;
step S20: acquiring first measurement data of the current time measured by a medical standard sphygmomanometer and measurement time t2;
step S30: judging whether 1h > (t 2-t 1) >0 is satisfied, executing step S40 when the 1h > (t 2-t 1) >0 is satisfied, otherwise executing step S10;
step S40: taking the first measurement data as standard data, and acquiring second measurement data which are measured by a blood pressure measurement module of the wearable equipment and are continuously repeated; the second measurement data are continuous multiple blood pressure measurement data of the wearable device in a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain a current average value after discrete calculation;
step S60: calculating a current correction error parameter according to the current average value;
step S70: calculating the average value again of the current correction error parameter and the last correction error parameter to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value actually measured by using the wearable device by using the current effective correction error parameter.
Specifically, the blood pressure of the aged is measured, the blood pressure is relatively stable in one hour when the aged wakes up during sleep, meanwhile, the wearable device can determine the sleep time of the aged by measuring the heart rate change, blood pressure change and other data changes of the aged, and when the aged sleeps within one hour after the sleep end time t1 (namely, 1 hour is satisfied>(t2-t1)>0) The first measurement data measured using the medical standard sphygmomanometer may be used as standard data. The wearable device is a smart watch, and the wearable device also has a communication module, wherein the communication module comprises Bluetooth, wiFi and a mobile communication network(e.g., 4G, 5G, etc.), the wearable device is connected to a server, and data about the physical state of the elderly, such as heart rate, blood pressure data, etc., on the wearable device can be acquired on the server in real time. Therefore, the multiple blood pressure measurement data of the wearable device within the preset time is taken as the second measurement data, for example, every 5 minutes within 1 hour. The second measurement data is recorded as X 1 、X 2 、……、X m Wherein m is a natural number; for example, 1 hour, every 5 minutes, a total of 12 measurement data are obtained. The second measurement data obtained may be adjusted according to the length of the preset time and the length of the interval time, preferably, the preset time is 0.5 to 3 hours, and the interval time is 1 minute to 30 minutes.
Referring to fig. 2, the step S50 includes:
step S510: performing discrete filtering on the second measurement data, and filtering out data with maximum discrete property; further, since the data with the largest discreteness may be interference data, among the m second measurement data, the data with the largest discreteness may be filtered, and the data with the largest discreteness may be 1 or more, and when the data is calculated, the data is analyzed according to the average value, the maximum value and the minimum value of the m second measurement data and the discrete distribution condition of the m data, to find the value with the largest discrete number, where the value with the largest discrete number includes the possible maximum value or the possible minimum value.
Step S520: taking the standard data as a datum point, and performing discrete characteristic calculation on the data subjected to discrete filtering; the discrete characteristic calculation includes the second measurement data being discretely distributed on both sides of the reference point, on the left side of the reference point, and on the right side of the reference point.
Step S530: carrying out the average value calculation of the time on the second measurement data calculated by the discrete characteristics; specifically, the current average value is calculated as:
X′ m ＝(X 1 +X 2 +...X m )/m
wherein:
X′ m representing the average value;
X 1 to X m Represents m thAnd (2) measuring data, wherein m is a natural number.
Among the m second measurement data, the data with the largest filtering discreteness is calculated through discrete characteristics, for example, the data with the error exceeding the set range (for example, the error exceeding 20%) of the measurement data is filtered as invalid data, and the filtered data is used as the second measurement data to calculate the average value.
Calculating a current correction error parameter according to the current average value; the calculation of the current correction error parameter in step S60 is as follows:
A′ m ＝(X′ m -X 0 )/X′ m
wherein,
A′ m representing a current correction error parameter; m is a natural number;
X 0 representing standard data;
X′ m this average value is shown.
Calculating the average value again of the current correction error parameter and the last correction error parameter to obtain a current effective correction error parameter; the calculation of the current effective correction error parameter is as follows:
A″ m ＝(X′ m -X′ m-1 )/2
wherein,
A″ m representing a current valid correction error parameter; m is a natural number;
A′ m representing a current correction error parameter;
X′ m-1 indicating the last corrected error parameter.
After the calculation of the current effective correction error parameter is completed, the current effective correction error parameter can be used for correcting the blood pressure measurement of the following old people by using the intelligent watch in real time. Specifically, using the current valid correction error parameter to correct and calculate a blood pressure value measured by using the wearable device is as follows:
Y n ＝X n *(1-A″ m )
wherein,
Y n representation correctionA value; n is a natural number;
X n representing the measured value;
A″ m indicating the currently active correction error parameter.
I.e. the blood pressure measurement X of the nth measurement n By currently correcting the error parameter A m After correction, a correction value Y is obtained n 。
Therefore, the current effective correction error parameter is calculated by correlating the current correction error parameter obtained in the last time with the current correction error parameter of the last time, so that the error parameter distortion rate is reduced, and the correction accuracy is improved.
In addition, the invention also provides a dynamic blood pressure measurement calibration device of the wearable equipment, in particular to a device such as a mobile phone terminal for monitoring the blood pressure of the old, wherein the dynamic blood pressure measurement calibration device of the wearable equipment is a host or a server for medical care.
Referring to fig. 3, an internal structure diagram of a dynamic blood pressure measurement calibration device of a wearable device according to an embodiment of the invention is provided, where the dynamic blood pressure measurement calibration device of the wearable device at least includes a memory 11, a processor 12, a communication bus 13, and a network interface 14.
The memory 11 includes at least one type of readable storage medium including flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of a dynamic blood pressure measurement calibration device of the wearable apparatus, for example a hard disk of the dynamic blood pressure measurement calibration device of the wearable apparatus. The memory 11 may in other embodiments also be an external storage device of the dynamic blood pressure measurement calibration apparatus of the wearable device, such as a plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card) or the like, which is provided on the dynamic blood pressure measurement calibration apparatus of the wearable device. Further, the memory 11 may also comprise both an internal memory unit and an external memory device of the dynamic blood pressure measurement calibration apparatus of the wearable device. The memory 11 may be used not only for storing application software of a dynamic blood pressure measurement calibration device mounted on a wearable apparatus and various kinds of data, for example, codes of a dynamic blood pressure measurement calibration program of the wearable apparatus, etc., but also for temporarily storing data that has been output or is to be output.
The processor 12 may in some embodiments be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor or other data processing chip for running program code or processing data stored in the memory 11, for example performing a dynamic blood pressure measurement calibration procedure of the wearable device, etc.
The communication bus 13 is used to enable connection communication between these components.
The network interface 14 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), typically used to establish a communication connection between the dynamic blood pressure measurement calibration device of the wearable device and other electronic devices; specifically, the dynamic blood pressure measurement calibration device of the wearable device is in communication connection with the wearable device (such as a smart watch) worn by the elderly, and meanwhile, the dynamic blood pressure measurement calibration device of the wearable device can also be in communication connection with a medical standard sphygmomanometer to acquire first measurement data.
Optionally, the dynamic blood pressure measurement calibration device of the wearable device may further comprise a user interface, which may comprise a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface may further comprise a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the dynamic blood pressure measurement calibration device of the wearable device and for displaying a visual user interface.
Fig. 3 only shows a dynamic blood pressure measurement calibration apparatus of a wearable device with components 11-14 and a dynamic blood pressure measurement calibration procedure of the wearable device, it will be understood by those skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the dynamic blood pressure measurement calibration apparatus of the wearable device, may comprise fewer or more components than shown, or may combine certain components, or a different arrangement of components.
In the embodiment of the dynamic blood pressure measurement calibration device of the wearable device shown in fig. 3, the memory 11 stores a dynamic blood pressure measurement calibration program of the wearable device; the processor 12 when executing the dynamic blood pressure measurement calibration program of the wearable device stored in the memory 11 implements the following steps:
step S10: acquiring sleep ending time t1 of the old acquired by the wearable equipment;
step S20: acquiring first measurement data of the current time measured by a medical standard sphygmomanometer and measurement time t2;
step S30: judging whether 1h > (t 2-t 1) >0 is satisfied, executing step S40 when the 1h > (t 2-t 1) >0 is satisfied, otherwise executing step S10;
step S40: taking the first measurement data as standard data, and acquiring second measurement data which are measured by a blood pressure measurement module of the wearable equipment and are continuously repeated; the second measurement data are continuous multiple blood pressure measurement data of the wearable device in a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain a current average value after discrete calculation;
step S60: calculating a current correction error parameter according to the current average value;
step S70: calculating the average value again of the current correction error parameter and the last correction error parameter to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value actually measured by using the wearable device by using the current effective correction error parameter.
Referring to fig. 4, a schematic program module of a dynamic blood pressure measurement calibration procedure of a wearable device in an embodiment of a dynamic blood pressure measurement calibration apparatus of a wearable device according to the present invention is shown, where the dynamic blood pressure measurement calibration procedure of the wearable device may be divided into an acquisition module 10, an acquisition module 20, a calculation module 30 and a calibration module 40, which are exemplified:
the acquisition module 10 is used for executing acquisition of the sleep end time t1 of the old people acquired by the wearable equipment;
an acquisition module 20 for performing acquisition of the first measurement data and the second measurement data;
a calculation module 30 for performing calculation of the average pitch;
a calibration module 40 for performing a calibration of the blood pressure value measured using the wearable device using the calibration coefficient.
The functions or operation steps implemented when the program modules such as the acquisition module 10, the acquisition module 20, the calculation module 30, and the calibration module 40 are executed are substantially the same as those of the foregoing embodiments, and will not be described herein.
In addition, an embodiment of the present invention further provides a storage medium, where the storage medium is a computer readable storage medium, and a dynamic blood pressure measurement calibration program of a wearable device is stored on the storage medium, where the dynamic blood pressure measurement calibration program of the wearable device may be executed by one or more processors to implement the following operations:
step S10: acquiring sleep ending time t1 of the old acquired by the wearable equipment;
step S20: acquiring first measurement data of the current time measured by a medical standard sphygmomanometer and measurement time t2;
step S30: judging whether 1h > (t 2-t 1) >0 is satisfied, executing step S40 when the 1h > (t 2-t 1) >0 is satisfied, otherwise executing step S10;
step S40: taking the first measurement data as standard data, and acquiring second measurement data which are measured by a blood pressure measurement module of the wearable equipment and are continuously repeated; the second measurement data are continuous multiple blood pressure measurement data of the wearable device in a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain a current average value after discrete calculation;
step S60: calculating a current correction error parameter according to the current average value;
step S70: calculating the average value again of the current correction error parameter and the last correction error parameter to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value actually measured by using the wearable device by using the current effective correction error parameter.
The specific implementation manner of the storage medium of the present invention is basically the same as the above embodiments of the method and apparatus for calibrating dynamic blood pressure measurement of the wearable device, and will not be described here.
Compared with the prior art, the dynamic blood pressure measurement calibration method, the device and the storage medium of the wearable equipment, provided by the invention, have the advantages that the accuracy of the dynamic blood pressure measurement of the wearable equipment is improved through the automatic calibration of the dynamic blood pressure measurement of the wearable equipment, the risk of large errors caused by the blood pressure measurement of the wearable equipment is avoided, the dynamic blood pressure measurement data of the wearable equipment has higher reference significance, and the implementation is non-inductive for the old or the user, and the user experience is good.
It should be noted that, the foregoing reference numerals of the embodiments of the present invention are merely for describing the embodiments, and do not represent the advantages and disadvantages of the embodiments. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of other like elements in a process, apparatus, article or method that comprises the element.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a drone, a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (9)
1. A method for calibrating dynamic blood pressure measurement of a wearable device, comprising:
step S10: acquiring sleep ending time t1 of the old acquired by the wearable equipment;
step S20: acquiring first measurement data of the current time measured by a medical standard sphygmomanometer and measurement time t2;
step S30: judging whether 1h > (t 2-t 1) >0 is satisfied, executing step S40 when the 1h > (t 2-t 1) >0 is satisfied, otherwise executing step S10;
step S40: taking the first measurement data as standard data, and acquiring second measurement data which are measured by a blood pressure measurement module of the wearable equipment and are continuously repeated; the second measurement data are continuous multiple blood pressure measurement data of the wearable device in a preset time;
step S50: performing discrete calculation on the second measurement data by taking the standard data as a datum point, and calculating to obtain a current average value after discrete calculation;
step S60: calculating a current correction error parameter according to the current average value;
step S70: calculating the average value again of the current correction error parameter and the last correction error parameter to obtain a current effective correction error parameter;
step S80: and correcting the blood pressure value actually measured by using the wearable device by using the current effective correction error parameter.
2. The method for calibrating dynamic blood pressure measurement of a wearable device according to claim 1, wherein the step S50 comprises:
step S510: performing discrete filtering on the second measurement data, and filtering out data with maximum discrete property;
step S520: taking the standard data as a datum point, and performing discrete characteristic calculation on the data subjected to discrete filtering;
step S530: and carrying out the average value calculation on the second measurement data subjected to the discrete characteristic calculation.
3. The method for calibrating dynamic blood pressure measurement of a wearable device according to claim 2, wherein the current average value is calculated as:
X′ m ＝(X 1 +X 2 +...X m )/m
wherein:
X′ m representing the average value;
X 1 to X m And representing m second measurement data, wherein m is a natural number.
4. The method of calibrating dynamic blood pressure measurements of a wearable device of claim 2, wherein the discrete characteristic calculation includes the second measurement data being discretely distributed on both sides of a reference point, on the left side of the reference point, and on the right side of the reference point.
5. The method according to claim 1, wherein the calculating of the current correction error parameter in step S60 is:
A′ m ＝(X′ m -X 0 )/X′ m
wherein,
A′ m representing a current correction error parameter; m is a natural number;
X 0 representing standard data;
X′ m this average value is shown.
6. The method for calibrating dynamic blood pressure measurement of a wearable device according to claim 1, wherein the calculation of the current effective correction error parameter is:
A″ m ＝(A′ m -A′ m-1 )/2
wherein,
A″ m representing a current valid correction error parameter; m is a natural number;
A′ m representing a current correction error parameter;
A′ m-1 indicating the last corrected error parameter.
7. The method according to claim 1, wherein the correction calculation for correcting the blood pressure value measured by the wearable device using the current valid correction error parameter in step S80 is:
Y n ＝X n *(1-A″ m )
wherein,
Y n representing the correction value; n is a natural number;
X n representing the measured value;
A″ m indicating the currently active correction error parameter.
8. A dynamic blood pressure measurement calibration device for a wearable device, comprising a memory and a processor, wherein the memory stores a dynamic blood pressure measurement calibration program for the wearable device that is executable by the processor, and the dynamic blood pressure measurement calibration program for the wearable device, when executed by the processor, implements the steps of the dynamic blood pressure measurement calibration method for the wearable device according to any one of claims 1 to 7.
9. A storage medium, characterized in that the storage medium is a computer readable storage medium, on which a dynamic blood pressure measurement calibration program of a wearable device is stored, which is executable by one or more processors to implement the steps of the method of dynamic blood pressure measurement calibration of a wearable device according to any of claims 1 to 7.
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| TW201306798A (en) * | 2011-08-08 | 2013-02-16 | Ostar Meditech Corp | Blood pressure measurement system with automatic inspection and self-calibration functions |
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