Patent Grant
11426082
This application is based on and claims priority under 35 USC 119 from Japanese Patent Application No. 2018-062700 filed on Mar. 28, 2018, the contents of which are incorporated herein by reference.
The disclosure relates to a physiological information processing apparatus and a physiological information processing method. The disclosure further relates to a non-transitory computer readable storage medium on which a program for causing a computer to execute the physiological information processing method is stored.
Japanese Patent No. 5779299 discloses a method for non-invasively determining a measured value of the cardiac output of a patient based on measurement results of one or more physiological characteristics of the patient. Particularly, Japanese Patent No. 5779299 discloses a method in which measurement results of physiological characteristics including the heart rate, and systolic and diastolic blood pressures of the patient are acquired, and then a measured value of the cardiac output of the patient is determined.
Recently, it has been reported that the cardiac output of a patient varies in accordance with a parameter relating to the vascular distensibility such as the systemic vascular resistance (hereinafter, such a parameter is referred to as “vascular distensibility parameter”). Therefore, it is desired to calculate the cardiac output of a patient in consideration of the vascular distensibility parameter of the patient. In the case where the cardiac output of a patient is calculated without considering the vascular distensibility parameter of the patient, there is a possibility that a large discrepancy arises between a measured value of the cardiac output which is invasively measured by a cardiac output sensor, and a calculation value of the cardiac output which is calculated by using the heart rate and pulse wave transit time (hereinafter, referred to as PWTT) of the patient. When attention is focused on the phenomenon that the cardiac output varies in accordance with the vascular distensibility parameter (i.e., dependence on the vascular distensibility parameter), consequently, there is room for further improvement of the calculation accuracy of the cardiac output.
The disclosure provides a physiological information processing method and apparatus which can further improve the calculation accuracy of the cardiac output of a patient. The disclosure provides a non-transitory computer readable storage medium on which a program for causing a computer to execute the physiological information processing method is stored.
A physiological information processing method of one mode of the disclosure is to be executed by a computer, and includes:
acquiring electrocardiogram data of a subject;
acquiring pulse wave data of the subject;
measuring a heart rate based on the electrocardiogram data;
measuring a pulse wave transit time based on the electrocardiogram data and the pulse wave data;
calculating a cardiac output based on the pulse wave transit time and heart rate which have been measured;
calculating a vascular distensibility parameter relating to a vascular distensibility; and
correcting the calculated cardiac output based on the vascular distensibility parameter.
Moreover, a non-transitory computer readable storage medium on which a program for causing a computer to execute the physiological information processing method is stored are provided.
A physiological information processing apparatus of one mode of the disclosure includes:
one or more processor; and
one or more memory which stores computer readable instructions.
When the computer readable instructions are executed by the processor, the physiological information processing apparatus
acquires electrocardiogram data of a subject,
acquires pulse wave data of the subject,
measures a heart rate based on the electrocardiogram data,
measures a pulse wave transit time based on the electrocardiogram data and the pulse wave data,
calculates a cardiac output based on the pulse wave transit time and heart rate which have been measured,
calculates a vascular distensibility parameter relating to a vascular distensibility, and
corrects the calculated cardiac output based on the vascular distensibility parameter.
According to the disclosure, it is possible to provide a physiological information processing method and apparatus which can further improve the calculation accuracy of the cardiac output of a patient. Moreover, it is possible to provide a non-transitory computer readable storage medium on which a program for causing a computer to execute the physiological information processing method is stored.
Hereinafter, an embodiment will be described with reference to the drawings. Initially, the hardware configuration of a physiological information processing apparatus 1 of an embodiment of the presently disclosed subject matter (hereinafter, referred to simply as the embodiment) will be described.
The processing apparatus 1 may be an apparatus (a patient monitor or the like) dedicated to display of a trend graph of vital signs of a subject P, or, for example, a personal computer, a workstation, a smart phone, a tablet, or a wearable device (such as a smart watch or an AR glass) which is to be attached to the body (such as the arm or the head) of a medical person U.
The controller 2 includes a memory and a processor. The memory is configured so as to store computer readable instructions (programs), and may be configured by, for example, a ROM (Read Only Memory) which stores various programs and the like, and a RAM (Random Access Memory) having a plurality of work areas in which various programs to be executed by the processor, and the like are stored. Alternatively, the memory may be configured by a flash memory or the like. For example, the processor is a CPU (Central Processing Unit), an MPU (Micro Processing Unit), and/or a GPU (Graphics Processing Unit). The CPU may be configured by a plurality of CPU cores. The GPU may be configured by a plurality of GPU cores. The processor may be configured so as to develop a designated one of the various programs installed in the storage device 3 or the ROM, in the RAM, and execute various processes in cooperation with the RAM.
The processor may develop a physiological information processing program which will be described later, in the RAM, and execute the program in cooperation with the RAM, thereby enabling the controller 2 to control various operations of the processing apparatus 1. The physiological information processing program will be described in detail later.
For example, the storage device 3 is a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or a flash memory, and configured so as to store programs and various data. The physiological information processing program may be incorporated in the storage device 3. The storage device 3 may store physiological information data such as electrocardiogram data, blood pressure data, and pulse wave data of the subject P. For example, electrocardiogram data which are acquired by an electrocardiogram sensor 20 may be stored in the storage device 3 through the sensor interface 7.
The network interface 4 is configured so as to connect the processing apparatus 1 to a communication network. Specifically, the network interface 4 may include various wired connection terminals for communicating with an external apparatus such as a server through the communication network. The network interface 4 may further include various processing circuits, antenna, and the like for wirelessly communicating with an access point. For example, the standard of wireless communication between the access point and the processing apparatus 1 is the Wi-Fi (registered trademark), the Bluetooth (registered trademark), the ZigBee (registered trademark), the LPWA, or a fifth generation mobile communication system (5G). The communication network is a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, or the like. For example, the physiological information processing program and physiological information data may be acquired from the server placed in the communication network through the network interface 4.
The displaying section 5 may be a display device such as a liquid crystal display or an organic EL display, or that such as a transmission or non-transmission head mounted display which is to be attached to the head of the operator. Alternatively, the displaying section 5 may be a projector device which projects an image onto a screen.
The input operating section 6 is configured so as to receive an input operation performed by the medical person U who operates the processing apparatus 1, and produce an instruction signal corresponding to the input operation. For example, the input operating section 6 is configured by a touch panel which is placed overlappingly on the displaying section 5, operation buttons which are attached to the housing, or a mouse and/or a keyboard. The instruction signal which is produced by the input operating section 6 is transmitted to the controller 2 via the bus 8, and then the controller 2 executes a predetermined operation according to the instruction signal.
The sensor interface 7 is an interface which enables vital sensors such as the electrocardiogram sensor 20, a blood pressure sensor 21, and a pulse wave sensor 22 to be communicably connected to the processing apparatus 1. The sensor interface 7 may include input terminals to which the physiological data output from these vital sensors are input. The input terminals may be physically connected to connectors of the vital sensors. The sensor interface 7 may further include various processing circuits, antenna, and the like for wirelessly communicating with the vital sensors.
The electrocardiogram sensor 20 is configured so as to acquire electrocardiogram data indicating the electrocardiogram waveform of the subject P. The pulse wave sensor 22 is configured so as to acquire pulse wave data indicating the pulse wave of the subject P. The blood pressure sensor 21 is configured so as to acquire blood pressure data indicating a temporal change of the blood pressure (particularly, the arterial blood pressure and/or the venous blood pressure) of the subject P. The blood pressure sensor 21 may be configured by a plurality of blood pressure sensors. The blood pressure sensor 21 may invasively acquire the blood pressure data of the subject P, or non-invasively acquire the blood pressure data of the subject P. A cardiac output sensor 23 is configured so as to acquire cardiac output data indicating a temporal change of the cardiac output of the subject P.
Next, a physiological information processing method of the embodiment will be described with reference to
Next, the controller 2 measures in step S2 the pulse wave transit time (hereinafter, referred to as PWTT) based on the electrocardiogram data and the pulse wave data. The PWTT means a time interval from the peak point of a predetermined R wave of an electrocardiogram to the rising point of a predetermined pulse waveform which appears next to the predetermined R wave. Therefore, the controller 2 specifies the time of the peak point of the predetermined R wave from the electrocardiogram data, and further specifies that of the rising point of the predetermined pulse waveform which appears next to the predetermined R wave, from the pulse wave data. Next, the controller 2 calculates the time interval between the time of the rising point of the predetermined pulse waveform and that of the peak point of the predetermined R wave, thereby measuring the PWTT. The controller 2 may calculate the PWTT every predetermined time interval (for example, every one second).
Next, the controller 2 calculates the cardiac output of the subject P based on the PWTT and heart rate which have been measured (step S3). Specifically, the controller 2 calculates the cardiac output from the PWTT and the heart rate in accordance with following relational expression (1). In the expression, esCCO (estimated Continuous Cardiac Output) indicates a calculated cardiac output, HR indicates the heart rate, and K0, α, and β are specific coefficients which are set for each subject. Specific examples of methods for deriving the coefficients K0, α, and β are described in, for example, Japanese Patent No. 4,742,644 that is incorporated by reference herein. The controller 2 may calculate the cardiac output every predetermined time interval (for example, every one second).
esCCO=K0×(α×PWTT+β)×HR (1)
Next, the controller 2 calculates in step S4 the systemic vascular resistance (hereinafter, referred to as SVR) of the subject P. The SVR is an example of the vascular distensibility parameter relating to the vascular distensibility of the subject P. Specifically, the controller 2 acquires blood pressure data indicating a temporal change of the arterial blood pressure from the blood pressure sensor 21, and then calculates the mean blood pressure (MAP) of the subject P from the acquired blood pressure data. Moreover, the controller 2 acquires blood pressure data indicating a temporal change of the central venous pressure (CVP) from the blood pressure sensor 21. Furthermore, the controller 2 acquires cardiac output data indicating a temporal change of the cardiac output from the cardiac output sensor 23, and then calculates the cardiac output CO. Thereafter, the controller 2 calculates the SVR from the mean blood pressure (MAP), the central venous pressure (CVP), and the cardiac output (CO) in accordance with following relational expression (2):
SVR={(MAP−CVP)×80}/CO (2)
Further, the controller 2 may calculate the SVR every predetermined time interval (for example, every one second).
Next, the controller 2 determines in step S5 whether the newly calculated SVR satisfies a predetermined condition associated with the previously calculated SVR or not. The previously calculated SVR may be the SVRn−1 (n is an integer of 2 or more) which is calculated just before the newly calculated SVRn, the initially calculated SVR (i.e., SVR1), or an SVRm (m is an integer that is smaller than n) which is calculated before a predetermined time period.
Examples of “predetermined condition associated with the previously calculated SVR” are the following three conditions:
1) condition associated with a variation ΔSVR between the newly calculated SVR and the previously calculated SVR;
2) condition associated with a ratio of the variation ΔSVR to the newly calculated SVR or the previously calculated SVR; and
3) condition associated with a predetermined range which is set based on the previously calculated SVR.
The above conditions 1) to 3) will be described in detail below. For the sake of convenience of the description, “previously calculated SVR” is assumed to be the SVRn−1 which is calculated just before.
In the case of condition 1), the controller 2 determines whether the variation ΔSVR=|SVRn−SVRn−1| between the newly calculated SVRn and the just before calculated SVRn−1 is equal to or smaller than a predetermined value ΔSVRth or not. Here, the predetermined value ΔSVRth can be appropriately set on the side of a medical facility. If it is determined that the variation ΔSVR is equal to or smaller than the predetermined value ΔSVRth (in step S5, YES), the controller 2 ends the process. By contrast, if it is determined that the variation ΔSVR is larger than the predetermined value ΔSVRth (in step S5, NO), the controller 2 executes the process of step S6.
In the case of condition 2), the controller 2 determines whether the ratio R of the variation ΔSVR=|SVRn−SVRn−1| to the newly calculated SVRn (or the just before calculated SVRn−1) is equal to or smaller than a predetermined value Rth or not. Here, R=ΔSVR/SVRn×100% or R=ΔSVR/SVRn−1×100%. The predetermined value Rth can be appropriately set on the side of the medical facility. If it is determined that the ratio R is equal to or smaller than the predetermined value Rth (in step S5, YES), the controller 2 ends the process. By contrast, if it is determined that the ratio R is larger than the predetermined value Rth (in step S5, NO), the controller 2 executes the process of step S6.
In the case of condition 3), if it is determined that the newly calculated SVRn is included within a predetermined range S which is set based on the previously calculated SVRn−1 (in step S5, YES), the controller 2 ends the process. By contrast, if it is determined that the newly calculated SVRn is not included within the predetermined range S which is set based on the previously calculated SVRn−1 (in step S5, NO), the controller 2 executes the process of step S6. Here, the predetermined range S may be set as SVRn−1±γ (γ is a predetermined value). If it is determined that the SVRn is SVRn−1−γ≤SVRn≤SVRn−1+γ (in step S5, YES), the controller 2 ends the process. By contrast, if it is determined that the SVRn is not SVRn−1−γ≤SVRn≤SVRn−1+γ (in step S5, NO), the controller 2 executes the process of step S6.
As described above, in the case where the newly calculated SVRn largely varies from the just before calculated SVRn−1, the determination result of step S5 is NO, and, in the case where the newly calculated SVRn does not largely vary from the just before calculated SVRn−1, the determination result of step S5 is YES. In this way, in the case where the predetermined condition is satisfied in step S5 (in other words, in the case where the SVRn does not largely vary from the SVRn−1), the processes of steps S6 and S7 are not executed, and therefore the computing load of the controller 2 (processor) can be reduced.
Next, the controller 2 corrects in step S6 the coefficient K0 which is used in relational expression (1), based on the newly calculated SVRn. For example, the controller 2 can calculate the corrected coefficient K0 from the SVRn, based on following relational expression (3):
corrected coefficient K0=K0+ΔKn=K0+c×SVRn+d (3)
Here, the slope c and the intercept d are values which are determined by linearly approximating the correlation between ΔKi=Ki−K0 (i is an integer of 1 or more) and the SVRi, respectively. Namely, the correlation between ΔKi and the SVRi can be expressed as a linear function (ΔKi=c×SVRi+d) based on a plurality of ΔKi and a plurality of SVRi each of which is associated with corresponding one of the plurality of ΔKi. In this way, the slope c and the intercept d can be determined. The values of the slope c and the intercept d may be appropriately set on the side of the medical facility.
Next, the controller 2 again calculates in step S7 the cardiac output based on the corrected coefficient K0, thereby correcting the cardiac output (esCCO) which is calculated in step S3. Specifically, the controller 2 again calculates the cardiac output based on following relational expression (4):
According to the embodiment, as described above, the coefficient K0 is corrected based on the newly calculated SVRn, and then the cardiac output is again calculated based on the corrected coefficient K0. Since the calculated cardiac output is corrected in consideration of the SVR which is an example of the vascular distensibility parameter as described above, it is possible to provide the processing apparatus 1 in which the calculation accuracy of the cardiac output of the subject can be further improved.
The processes (particularly, the processes illustrated in steps S3 to S7) illustrated in
(Modification of the Embodiment)
Next, a physiological information processing method of a modification of the embodiment (hereinafter, referred to merely as modification) will be described with reference to
As illustrated in
Here, the slope e and the intercept f are values which are determined by linearly approximating the correlation between ΔesCCOi=esCCOi−esCCO0 (i is an integer of 1 or more) and the SVRi, respectively, and esCCO0 is a predetermined cardiac output which is determined in the case of PWTT=PWTT0 and HR=HR0. For example, PWTT0 is the value of the PWTT in the stable condition of the subject, and HR0 is the value of HR in the stable condition of the subject.
Namely, the correlation between the ΔesCCOi and the SVRi can be expressed as a linear function (ΔesCCOi=e×SVRi+f) based on a plurality of ΔesCCOi and a plurality of SVRi each of which is associated with corresponding one of the plurality of ΔesCCOi. In this way, the slope e and the intercept f can be determined. The values of the slope e and the intercept f may be appropriately set on the side of the medical facility.
According to the modification, as described above, the calculated value of the cardiac output is corrected by adding the value of ΔesCCO=e×SVRn+f which is calculated based on the newly calculated SVRn, to the cardiac output which is calculated in step S12. Since the calculated value of the cardiac output is corrected in consideration of the SVR which is an example of the vascular distensibility parameter as described above, it is possible to provide the processing apparatus 1 in which the calculation accuracy of the cardiac output of the subject can be further improved.
In this respect, the degree by which the calculation accuracy of the cardiac output is improved will be described with reference to
The processes (particularly, the processes illustrated in steps S12 to S15) illustrated in
Although, in the descriptions of the embodiment and the modification, the SVR is used as an example of the vascular distensibility parameter, the vascular distensibility parameter is not limited to the SVR. In place of the SVR, for example, the arterial elastic modulus, the dynamic arterial elastic modulus, or the pulse-amplitude index may be used as an example of the vascular distensibility parameter. Also in this case, samely or similarly, the calculated value of the cardiac output is corrected in consideration of the arterial elastic modulus, the dynamic arterial elastic modulus, or the pulsation rate, and therefore it is possible to provide the processing apparatus 1 in which the calculation accuracy of the cardiac output of the subject can be further improved.
In order to realize the processing apparatus 1 of the embodiment by using software, the physiological information processing program may be pre-installed in the storage device 3 or the ROM. Alternatively, the physiological information processing program may be stored on a computer readable storage medium such as a magnetic disk (such as an HDD or a floppy disk), an optical disk (such as a CD-ROM, a DVD-ROM, or a Blu-ray (registered trademark) disk), a magneto-optical disk (such as an MO), or a flash memory (such as an SD card, a USB memory, or an SSD). In the alternative, when the physiological information processing program which is stored in the storage medium may be installed in the storage device 3. Then, the program which is installed in the storage device 3 is loaded into the RAM, and thereafter the processor executes the program which is loaded into the RAM. In this way, the physiological information processing method of the embodiment is executed by the processing apparatus 1.
The physiological information processing program may be downloaded from a computer on a communication network, through the network interface 4. The downloaded program may be installed in the storage device 3.
Although the embodiment of the presently disclosed subject matter has been described, the technical scope of the presently disclosed subject matter should not be limitedly interpreted by the description of the embodiment. It should be understood by those skilled in the art that the embodiment is a mere example, and may be variously changed within the scope of the presently disclosed subject matter as defined in the claims. The technical scope of the presently disclosed subject matter should be determined based on the scope of the presently disclosed subject matter as defined in the claims, and the scope of equivalence thereof.
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| JP2018-062700 | Mar 2018 | JP | national |
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| 20190298180 A1 | Oct 2019 | US |
