Parameter determination method, parameter determination device, storage medium, and electronic device

Abstract

A parameter determination method and a parameter determination device, which relate to the technical field of medical data processing. The parameter determination method includes the steps of: determining a first parameter set corresponding to a test subject based on a first time period (S100), the first time period including a nighttime period, and the first parameter set including a first heart rate signature parameter and a first heart rate variability signature parameter; and determining a second parameter set corresponding to the test subject based on a second time period (S200), the second time period including a daytime period, and the second parameter set including a second heart rate signature parameter and a second heart rate variability signature parameter. The effect of noise factors during parameter measurement can be reduced, thereby improving the accuracy of the obtained parameter set and the comparability of changes over time. When the determined first parameter set and second parameter set are used to represent the level and / or state of neurohormones, the accuracy of representation and the comparability of changes over time can be effectively improved.

Description

[Technical field]

[0001] The present application relates to the technical field of medical data processing, and in particular to a parameter determination method, a parameter determination apparatus, a storage medium and an electronic device. [Background technology]

[0002] As is well known, neurohormones driven by the sympathetic and parasympathetic nervous systems are easily affected by many factors, such as day-night changes, progression of disease, sleep conditions, and drugs, making them extremely difficult to measure accurately.

[0003] Thus, there is a need for parameter determination methods for determining parameters that are accurately indicative of neurohormonal levels and / or states. Summary of the Invention [Problem to be solved by the invention]

[0004] In order to solve the above technical problems, the present invention is proposed. The embodiments of the present invention disclose a parameter determination method, a parameter determination apparatus, a computer-readable storage medium and an electronic device. [Means for solving the problem]

[0005] According to one aspect, an embodiment of the present invention discloses a parameter determination method, the method includes the steps of: determining a first parameter set corresponding to a test subject based on a first time period, the first time period including a night time period, the first parameter set including a first heart rate signature parameter and a first heart rate variability signature parameter, and determining a second parameter set corresponding to the test subject based on a second time period, the second time period including a day time period, the second parameter set including a second heart rate signature parameter and a second heart rate variability signature parameter.

[0006] In one embodiment of the present invention, the first time period includes a plurality of first time periods, and the first heart rate signature parameters include a first average heart rate parameter and a first resting heart rate parameter, and determining a first parameter set corresponding to the test subject based on the first time period includes: determining a first average heart rate parameter corresponding to each of the plurality of first time periods based on the plurality of first time periods; and determining a first resting heart rate parameter based on the first average heart rate parameter corresponding to each of the plurality of first time periods.

[0007] In one embodiment of the present invention, the step of determining the first resting heart rate parameter based on the first average heart rate parameters corresponding to each of the plurality of first time periods includes the steps of identifying a minimum first average heart rate parameter among the first average heart rate parameters corresponding to each of the plurality of first time periods, and determining the minimum first average heart rate parameter as the first resting heart rate parameter.

[0008] In one embodiment of the present invention, the first heart rate variability signature parameter includes a first heart rate variability parameter at rest, and after determining the first heart rate parameter at rest based on the first average heart rate parameters corresponding to each of the plurality of first time periods, the method further includes determining the first time period corresponding to the first heart rate parameter at rest as a first resting time period, and determining the heart rate variability parameter corresponding to the first resting time period as the first heart rate variability parameter at rest.

[0009] In one embodiment of the present invention, before the step of determining the first average heart rate parameter corresponding to each of the plurality of first time periods based on the plurality of first time periods, the method further includes a step of removing a non-resting time period corresponding to each of the plurality of first time periods, wherein the step of determining the first average heart rate parameter corresponding to each of the plurality of first time periods based on the plurality of first time periods includes a step of determining the first average heart rate parameter corresponding to each of the plurality of first time periods based on the plurality of first time periods after the non-resting time period is removed.

[0010] In one embodiment of the present invention, the second time period includes a plurality of second time periods, and the second heart rate signature parameters include a second average heart rate parameter and a second resting heart rate parameter, and determining a second set of parameters corresponding to the test subject based on the second time period includes: determining a second average heart rate parameter corresponding to each of the plurality of second time periods based on the plurality of second time periods; and determining a second resting heart rate parameter based on the second average heart rate parameters corresponding to each of the plurality of second time periods.

[0011] In one embodiment of the present invention, determining the second resting heart rate parameter based on the second average heart rate parameters corresponding to each of the plurality of second time periods includes identifying a minimum second average heart rate parameter among the second average heart rate parameters corresponding to each of the plurality of second time periods, and determining the minimum second average heart rate parameter as the second resting heart rate parameter.

[0012] In one embodiment of the present invention, the second heart rate variability signature parameter includes a second heart rate variability parameter at rest, and after determining the second heart rate parameter at rest based on the second average heart rate parameters corresponding to the plurality of second time periods, the method further includes determining the second time period corresponding to the second heart rate parameter at rest as a third resting time period, and determining the heart rate variability parameter corresponding to the third resting time period as the second heart rate variability parameter at rest.

[0013] In one embodiment of the present invention, before the step of determining the second average heart rate parameter corresponding to each of the plurality of second time periods based on the plurality of second time periods, the method further includes a step of removing a non-resting time period corresponding to each of the plurality of second time periods, wherein the step of determining the second average heart rate parameter corresponding to each of the plurality of second time periods based on the plurality of second time periods includes a step of determining the second average heart rate parameter corresponding to each of the plurality of second time periods based on the plurality of second time periods after the non-resting time period is removed.

[0014] According to another aspect, an embodiment of the present invention discloses a parameter determination device, the device comprising a first determination module and a second determination module. The first determination module is configured to determine a first parameter set corresponding to the test subject based on a first time period. The first time period includes a night time period, and the first parameter set includes a first heart rate signature parameter and a first heart rate variability signature parameter. The second determination module is configured to determine a second parameter set corresponding to the test subject based on a second time period. The second time period includes a day time period, and the second parameter set includes a second heart rate signature parameter and a second heart rate variability signature parameter.

[0015] According to another aspect, an embodiment of the present invention provides a computer readable storage medium having a computer program stored thereon, the computer program being configured to perform the parameter determination method according to the embodiment described above.

[0016] According to another aspect, an embodiment of the present invention provides an electronic device, comprising a processor and a memory configured to store processor-executable instructions, wherein the processor is configured to execute a parameter determination method according to any of the embodiments described above. Effect of the Invention

[0017] The parameter determination method according to the present invention can reduce the influence of noise factors in parameter measurement by determining parameter sets (i.e., a first parameter set and a second parameter set) corresponding to a test subject in a first time period and a second time period, thereby improving the accuracy of the obtained parameter sets and comparability at different time points. In addition, when the first parameter set and the second parameter set determined in the embodiment of the present invention are used to represent the level and / or state of neurohormones, the representation accuracy can be effectively improved. [Brief description of the drawings]

[0018] The above and other objects, features and advantages of the present invention will become more apparent by describing the embodiments of the present invention in more detail with reference to the drawings. The drawings are used to better understand the embodiments of the present invention, and constitute a part of the specification to contribute to the interpretation of the present invention together with the embodiments of the present invention, but are not intended to limit the present invention. In the drawings, the same reference numerals generally represent the same parts or steps. [Figure 1] FIG. 1 is a schematic diagram of a scene in which an embodiment of the present invention is applied; [Diagram 2] FIG. 2 is a schematic diagram of another scenario in which an embodiment of the present invention is applied; [Diagram 3] 4 is a flowchart of a parameter determination method according to an exemplary embodiment of the present invention. [Figure 4] 11 is a flowchart of measuring a first set of parameters corresponding to a test object based on a first time interval according to an exemplary embodiment of the present invention. [Diagram 5] 10 is a flowchart of determining a first resting heart rate parameter based on a first average heart rate parameter corresponding to each of a plurality of first time periods according to an exemplary embodiment of the present invention. [Figure 6] 11 is a flowchart of measuring a first set of parameters corresponding to a test object based on a first time interval according to another exemplary embodiment of the present invention. [Figure 7]11 is a flowchart of measuring a first set of parameters corresponding to a test object based on a first time interval according to another exemplary embodiment of the present invention. [Figure 8] 11 is a flowchart of measuring a second set of parameters corresponding to the test object based on a second time interval according to an exemplary embodiment of the present invention. [Figure 9] 11 is a flowchart of determining a second resting heart rate parameter based on second average heart rate parameters corresponding to a respective one of a plurality of second time periods according to an exemplary embodiment of the present invention. [Figure 10] 11 is a flowchart of measuring a second set of parameters corresponding to a test object based on a second time interval according to another exemplary embodiment of the present invention. [Figure 11] 1 is a structural schematic diagram of a parameter determination device according to an exemplary embodiment of the present invention; [Figure 12] FIG. 2 is a structural schematic diagram of a first determination module according to an exemplary embodiment of the present invention; [Figure 13] FIG. 11 is a structural schematic diagram of a first determination module according to another exemplary embodiment of the present invention; [Figure 14] FIG. 11 is a structural schematic diagram of a first determination module according to another exemplary embodiment of the present invention; [Figure 15] FIG. 2 is a structural schematic diagram of a second determination module according to an exemplary embodiment of the present invention; [Figure 16] FIG. 13 is a structural schematic diagram of a second determination module according to another exemplary embodiment of the present invention; [Figure 17] 1 is a structural schematic diagram of an electronic device according to an exemplary embodiment of the present invention; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the drawings. Apparently, the embodiments described herein are only some of the embodiments of the present invention, and are not all of the embodiments of the present invention. It should be noted that the present invention is not limited to the exemplary embodiments described herein.

[0020] <Background to the invention> As is well known, neurohormones driven by sympathetic and parasympathetic nerves are easily influenced by many factors. In particular, neurohormones in cardiac patients suffering from heart failure or arrhythmia are highly susceptible to factors such as day-night changes, progression of disease, sleep conditions, exercise or activity levels, medications, and mood changes. Therefore, in the prior art, heart rate (HR) and heart rate variability (HRV) are generally used as diagnostic grounds capable of expressing neurohormones or as substitute measurement indicators. Specifically, heart rate is the number of times the heart beats per minute. Heart rate variability refers to the change in the difference in the cycle of each heartbeat. The calculation of heart rate includes, but is not limited to, surface electrocardiogram, endocardial, epicardial electrocardiogram, electrocardiogram using subcutaneous electrodes, or ventricular or atrial heart rate calculated by R waves and P waves. In addition, heart rate may be calculated by other techniques, such as photoplethysmography (PPG).

[0021] However, both the heart rate and the heart rate variability are also very susceptible. For example, at night, the heart rate and / or the heart rate variability frequently change according to the sleep stage, and such changes are not necessarily related to neurohormones. In addition, because of the low heart rate, patients with pacemakers or implantable cardioverter defibrillators are often paced at night. In this case, the patient's actual heart rate is "hidden" and cannot be represented by the heart rate data that can be measured. Furthermore, in the prior art, the measured daytime heart rate and the daytime heart rate variability also include data of the exercise stage and the mental arousal stage. However, the exercise stage and the mental arousal stage can only represent a temporary state, and such temporary changes vary from time to time (day to day). At the same time, diseases such as heart failure have a significant impact on the patient's neurohormonal levels and / or states, but are relatively long-term in terms of time. Therefore, there is a need for a parameter determination method that can determine parameters that can accurately represent the neurohormonal levels and / or states and improve the comparability of the determined parameters.

[0022] In view of the above technical problems, the present invention proposes, as a basic idea, a parameter determination method, a parameter determination apparatus, a computer-readable storage medium, and an electronic device.

[0023] The parameter determination method of the present invention includes the steps of: determining a first parameter set corresponding to a test subject based on a first time period, where the first time period includes a nighttime period, and the first parameter set includes a first heart rate signature parameter and a first heart rate variability signature parameter; and determining a second parameter set corresponding to the test subject based on a second time period, where the second time period includes a daytime period, and the second parameter set includes a second heart rate signature parameter and a second heart rate variability signature parameter.

[0024] The parameter determination method according to the present invention can reduce the influence of noise factors in parameter measurement by determining parameter sets (i.e., the first parameter set and the second parameter set) corresponding to the test subject in the first time interval and the second time interval, respectively, thereby improving the accuracy and comparability of the obtained parameter sets. In addition, when the first parameter set and the second parameter set determined according to the present invention are used to represent the level and / or state of neurohormones, the representation accuracy can be effectively improved.

[0025] After explaining the basic principles of the present invention, some non-limiting embodiments of the present invention will now be presented with reference to the drawings.

[0026] <Example Scene> 1 is a schematic diagram of a scenario in which an embodiment of the present invention is applied. As shown in FIG. 1, the scenario in which the embodiment of the present invention is applied includes a server 1 and a medical device 2, where a communicable connection relationship exists between the server 1 and the medical device 2.

[0027] Specifically, the medical equipment 2 is used to collect reference parameters of the test subject, where the reference parameters include, but are not limited to, heart rate parameters and heart rate variability parameters. The server 1 is configured to determine a first parameter set corresponding to the test subject based on a first time period, and determine a second parameter set corresponding to the test subject based on a second time period, where the first time period includes a nighttime period, and the first parameter set includes a first heart rate signature parameter and a first heart rate variability signature parameter. section The second parameter set includes a daytime period, and the second parameter set includes a second heart rate signature parameter and a second heart rate variability signature parameter. That is, in this scenario, a parameter determination method is implemented.

[0028] Exemplarily, the server 1 determines the above-mentioned first parameter set and / or second parameter set based on the reference parameters collected by the medical equipment 2 .

[0029] In the above-mentioned scenario shown in Fig. 1, the parameter determination method is realized by using the server 1, which can improve the adaptability of the scenario and effectively reduce the computational load of the medical equipment 2.

[0030] It should be noted that the present invention can also be applied to another scenario. Figure 2 is a schematic diagram of another scenario in which the embodiment of the present invention is applied. Specifically, the scenario includes a medical device 3, and the medical device 3 includes a parameter collection module 301 and a calculation module 302.

[0031] Specifically, the parameter collection module 301 in the medical equipment 3 is configured to collect reference parameters of the test subject, where the reference parameters include, but are not limited to, heart rate parameters and heart rate variability parameters. The calculation module 302 is configured to determine a first parameter set corresponding to the test subject based on a first time period, and determine a second parameter set corresponding to the test subject based on a second time period, where the first time period includes a night time period, and the first parameter set includes a first heart rate signature parameter and a first heart rate variability signature parameter. section The second parameter set includes a daytime period, and the second parameter set includes a second heart rate signature parameter and a second heart rate variability signature parameter. That is, in this scenario, a parameter determination method is implemented.

[0032] Exemplarily, the calculation module 302 determines the above-mentioned first parameter set and / or second parameter set based on the reference parameters collected by the parameter collection module 301 .

[0033] In the above-mentioned scene shown in Figure 2, the parameter determination method is realized using the medical equipment 3, so there is no need to perform data transmission operations with related devices such as a server. Therefore, the above-mentioned scene can guarantee the real-time nature of the parameter determination method.

[0034] It should be noted that the medical equipment mentioned in the above scenario may be implantable medical devices (IMD) or wearable medical devices (WMD), and the embodiments of the present invention are not limited thereto.

[0035] Exemplary Methods 3 is a flowchart of a parameter determination method according to an exemplary embodiment of the present invention. As shown in FIG. 3, the parameter determination method according to the embodiment of the present invention includes the following steps.

[0036] In step S100, a first set of parameters corresponding to the test object is determined based on a first time interval.

[0037] Exemplarily, the first time interval includes a night time interval. For example, in the case of a 24-hour system, the first time interval is a time interval from 18:00 of one day to 6:00 of the next day. Preferably, the first time interval is a time interval from 22:00 of one day to 6:00 of the next day. Preferably, in the first time interval, the test subject is in a resting or sleeping state, so that noise is reduced and the accuracy of the finally obtained first parameter set is increased. Here, the resting state refers to the body being in a resting state, and the sleeping state refers to the state in which the body is asleep and in a resting and "lying" position.

[0038] For example, the test object referred to in step S100 refers to a human body, i.e., determining a first parameter set corresponding to the human body. Note that, determining a first parameter set corresponding to the test object referred to in step S100 may also mean calculating a first parameter set corresponding to the test object.

[0039] In an embodiment of the present invention, the first parameter set includes a first heart rate signature parameter and a first heart rate variability signature parameter. Here, the first heart rate signature parameter is a parameter capable of representing a heart rate condition within a first time period. The first heart rate variability signature parameter is a parameter capable of representing a heart rate variability condition within the first time period. For example, the first heart rate signature parameter is obtained based on a heart rate measured in real time, and the first heart rate variability signature parameter is obtained based on heart rate variability measured in real time.

[0040] In step S200, a second set of parameters corresponding to the test object is determined based on the second time interval.

[0041] Exemplarily, the second time period includes a daytime period. For example, in the case of a 24-hour system, the second time period is a time period from 6:00 to 18:00 of the day. Preferably, the second time period is a time period from 8:00 to 20:00 of the day. Preferably, in the second time period, the test subject is in a resting state or in a state of almost no movement or activity, thereby reducing noise and increasing the accuracy and comparability of the finally obtained second parameter set. More preferably, in the second time period, the test subject is in a non-standing resting or non-moving state. Exemplarily, the non-moving state referred to herein can be determined based on a movement / body movement or other physiological parameter threshold. For example, the test subject may be determined to be in a non-moving state if the test subject's real-time body movement signal is lower than a predetermined threshold or the test subject's real-time heart rate does not continuously exceed a preset movement heart rate threshold.

[0042] In an embodiment of the present invention, the second parameter set includes a second heart rate signature parameter and a second heart rate variability signature parameter, where the second heart rate signature parameter refers to a parameter that can represent a heart rate condition in a second time period. The second heart rate variability signature parameter refers to a parameter that can represent a heart rate variability condition in a second time period. For example, the second heart rate signature parameter is obtained based on a heart rate measured in real time, and the second heart rate variability signature parameter is obtained based on a heart rate variability measured in real time.

[0043] In practical application, a first parameter set corresponding to the test object is determined based on the first time interval, and a second parameter set corresponding to the test object is determined based on the second time interval.

[0044] The parameter determination method according to the embodiment of the present invention can reduce the influence of noise factors in parameter measurement by determining parameter sets (i.e., a first parameter set and a second parameter set) corresponding to a test subject in a first time period and a second time period, respectively, thereby improving the accuracy and comparability of the obtained parameter sets. In addition, when the first parameter set and the second parameter set determined by the present invention are used to represent the level and / or state of neurohormones, the representation accuracy can be effectively improved.

[0045] 4 is a flow chart of measuring a first set of parameters corresponding to a test object based on a first time interval according to an exemplary embodiment of the present invention. Since the embodiment shown in FIG. 4 can be expanded based on the embodiment shown in FIG. 3, the following description will focus on the differences between the embodiment shown in FIG. 4 and the embodiment shown in FIG. 3, and will omit the common parts.

[0046] As shown in Fig. 4, in the parameter determining method according to the embodiment of the present invention, the first time period includes a plurality of first time periods, and the first heart rate signature parameters include a first average heart rate parameter and a first resting heart rate parameter, and the step of determining a first parameter set corresponding to the test object according to the first time period includes the following steps:

[0047] In step S110, a first average heart rate parameter corresponding to each of the first time periods is determined based on the first time periods.

[0048] For example, the first time period is a time window with a time length of 60 seconds. In other words, step S110 refers to determining first average heart rate parameters corresponding to the multiple time windows according to the multiple time windows included in the first time period.

[0049] Optionally, a first Mean Heart Rate (MHR) parameter corresponding to each time window is an average value of the heart rates measured within that time window.

[0050] In step S120, a first resting heart rate parameter is determined based on the first average heart rate parameters corresponding to each of the plurality of first time periods.

[0051] In one embodiment of the present invention, the first resting heart rate parameter is a Sleep Rest Heart Rate (Sleep RHR) parameter.

[0052] Since the first resting heart rate parameter is determined based on the first average heart rate parameters corresponding to each of the plurality of first time periods, the obtained first resting heart rate parameter can fully reflect the characteristics of the first average heart rate parameters corresponding to each of the plurality of first time periods, so that the obtained first resting heart rate parameter can better represent the heart rate status of the test subject in the first time period.

[0053] The parameter determination method according to the embodiment of the present invention can determine a first parameter set corresponding to the test subject based on a first time period by determining a first average heart rate parameter corresponding to each of the first time periods based on a plurality of first time periods, and determining a first resting heart rate parameter based on the first average heart rate parameters corresponding to each of the first time periods. Compared with the real-time heart rate, the first average heart rate parameter and the first resting heart rate parameter can more accurately represent the heart rate status of the test subject in the first time period. Therefore, when predicting the neurohormonal level and / or state of the test subject in the first time period based on the first average heart rate parameter and the first resting heart rate parameter obtained by the embodiment of the present invention, a more accurate neurohormonal prediction result can be obtained.

[0054] In another embodiment of the present invention, the process of determining the first average heart rate parameter includes determining a heart rate variability parameter corresponding to each of the first time periods based on the first time periods, and determining the first average heart rate parameter based on the heart rate variability parameter corresponding to each of the first time periods. For example, first, the first time period corresponding to the maximum heart rate variability parameter among the heart rate variability parameters corresponding to each of the first time periods is identified, and then the average heart rate parameter corresponding to the first time period is determined as the first average heart rate parameter. Here, the heart rate variability parameter may be described by other statistics, such as a 75% value. The average heart rate parameter may also be described by other statistics, such as a 25% value.

[0055] Similarly, in the embodiment of the present invention, the non-rest time period may be removed from the first time period first. Here, the detailed meaning of the non-rest time period may be referred to the embodiment shown in FIG. 7 and is omitted in this embodiment.

[0056] 5 is a flow chart of determining a first resting heart rate parameter based on a first average heart rate parameter corresponding to each of a plurality of first time periods according to an exemplary embodiment of the present invention. Since the embodiment shown in FIG. 5 can be expanded based on the embodiment shown in FIG. 4, the following description will focus on the difference between the embodiment shown in FIG. 5 and the embodiment shown in FIG. 4, and will omit the common parts.

[0057] As shown in FIG. 5, in the parameter determining method according to the embodiment of the present invention, the step of determining a first resting heart rate parameter based on a first average heart rate parameter corresponding to each of a plurality of first time periods includes the following steps:

[0058] In step S121, the minimum first average heart rate parameter is identified from among the first average heart rate parameters corresponding to each of the plurality of first time slots.

[0059] In step S122, the smallest first average heart rate parameter is determined as the first resting heart rate parameter.

[0060] For example, the number of first time periods included in the first time section is 5, which are the first time period a, the first time period b, the first time period c, the first time period d, and the first time period e. Correspondingly, the first average heart rate parameter corresponding to the first time period a is 80 beats / min, the first average heart rate parameter corresponding to the first time period b is 85 beats / min, the first average heart rate parameter corresponding to the first time period c is 90 beats / min, the first average heart rate parameter corresponding to the first time period d is 75 beats / min, and the first average heart rate parameter corresponding to the first time period e is 95 beats / min. Obviously, the first average heart rate parameter corresponding to the first time period d (75 beats / min) is the smallest first average heart rate parameter. Therefore, as described in step S122, the first average heart rate parameter corresponding to the first time period d (75 beats / min) can be determined as the first resting heart rate parameter.

[0061] The parameter determination method according to the embodiment of the present invention can determine the first resting heart rate parameter based on the first average heart rate parameters corresponding to the plurality of first time periods by identifying the minimum first average heart rate parameter among the first average heart rate parameters corresponding to the plurality of first time periods, and determining the minimum first average heart rate parameter as the first resting heart rate parameter. Since the minimum first average heart rate parameter among the first average heart rate parameters corresponding to the plurality of first time periods can represent the heart rate characteristics of the test subject in the first time period to a certain extent, the embodiment of the present invention can further increase the amount of information contained in the first parameter set, thereby improving the prediction accuracy and comparability of the neurohormonal levels and / or states.

[0062] Another embodiment of the present invention is obtained by expanding on the embodiment shown in FIG. 5. The embodiment of the present invention further includes a step of selecting a preset time section in the first time section before the step of identifying the minimum first average heart rate parameter among the first average heart rate parameters corresponding to each of the plurality of first time periods. Here, the length of the preset time section is shorter than the first time period. Also, in the embodiment of the present invention, the step of identifying the minimum first average heart rate parameter among the first average heart rate parameters corresponding to each of the plurality of first time periods includes a step of identifying the minimum first average heart rate parameter among the first average heart rate parameters corresponding to the first time periods included in the preset time section. By providing in this way, some atypical time sections in the first time section can be identified. To The corresponding average heart rate parameter can be effectively eliminated, thus further improving the accuracy of the smallest first average heart rate parameter that can be determined.

[0063] 6 is a flowchart of measuring a first set of parameters corresponding to a test object based on a first time interval according to another exemplary embodiment of the present invention. Since the embodiment shown in FIG. 6 can be expanded based on the embodiment shown in FIG. 4, the following description will focus on the differences between the embodiment shown in FIG. 6 and the embodiment shown in FIG. 4, and will omit the common parts.

[0064] As shown in FIG. 6 , after the step of determining a first resting heart rate parameter based on a first average heart rate parameter corresponding to each of a plurality of first time periods, the parameter determining method according to an embodiment of the present invention further includes the following steps:

[0065] In step S130, a first time period corresponding to the first resting heart rate parameter is determined as a first resting time period.

[0066] In step S140, the heart rate variability parameters corresponding to the first resting time period are determined as first resting heart rate variability parameters.

[0067] In one embodiment of the present invention, the first rest heart rate variability parameter is a Sleep Rest Heart Rate Variability (Sleep RHRV) parameter.

[0068] In practical application, a first average heart rate parameter corresponding to each of the first time periods is determined based on the first time periods, and a first resting heart rate parameter is determined based on the first average heart rate parameters corresponding to each of the first time periods. Then, the first time period corresponding to the first resting heart rate parameter is determined as a first resting time period, and the heart rate variability parameter corresponding to the first resting time period is determined as a first resting heart rate variability parameter. Furthermore, a second parameter set corresponding to the test subject is determined based on a second time period.

[0069] Compared to the prior art, embodiments of the present invention can improve the ability and comparability of the obtained first resting heart rate variability parameter to represent the neurohormonal levels and / or states of the test subject during the first time period because the obtained first resting heart rate variability parameter is determined based on the first resting heart rate parameter.

[0070] In addition, in another embodiment of the present invention, the first resting heart rate variability parameter may be determined first, and then the first resting heart rate parameter may be determined (this is also applicable to the second resting heart rate variability parameter and the second resting heart rate parameter, that is, the second resting heart rate parameter may be determined first, and then the second resting heart rate parameter may be determined). For example, the first heart rate variability parameter corresponding to each of the first time periods is determined based on the first time periods, and then the first time period corresponding to the first heart rate variability parameter is determined as the first resting time period, and the average heart rate parameter corresponding to the first resting time period is determined as the first resting heart rate parameter. Here, the step of determining the first resting heart rate variability parameter based on the first heart rate variability parameters corresponding to each of the plurality of first time slots can be performed so as to determine the first resting heart rate variability parameter based on the first time slot corresponding to the maximum first heart rate variability parameter among the first heart rate variability parameters corresponding to each of the plurality of first time slots. Here, the heart rate variability parameter may be described by other statistics than the maximum, for example, a 75% value. Also, average Heart Rate P The parameter may also be described by other statistics, such as the 25th percentile value.

[0071] 7 is a flowchart of determining a first parameter set corresponding to a test object based on a first time interval according to another exemplary embodiment of the present invention. Since the embodiment shown in FIG. 7 can be expanded based on the embodiment shown in FIG. 4, the following description will focus on the differences between the embodiment shown in FIG. 7 and the embodiment shown in FIG. 4, and will omit the common parts.

[0072] As shown in FIG. 7, the parameter determination method according to an embodiment of the present invention further includes the following steps before the step of confirming first average heart rate parameters corresponding to each of the multiple first time periods based on the multiple first time periods.

[0073] In step S105, the non-resting time periods corresponding to the plurality of first time slots are removed.

[0074] Exemplarily, the non-resting time period referred to in step S105 is, for example, a snoring time period and / or a time period during which the breathing frequency is unstable (eg, sleep apnea).

[0075] In one embodiment of the present invention, the non-resting time period further includes a time period corresponding to a special stage during sleep in which the degree of physical activity is high. For example, the special stage during sleep is a Rapid Eye Movement (REM) stage, in which the heart rate changes drastically during dreaming. As another example, the non-resting time period further includes a time period corresponding to an incident such as a premature atrial contraction (PAC), a premature ventricular contraction (PVC), atrial tachycardia or atrial arrhythmia (e.g., atrial fibrillation, etc.), and a ventricular tachycardia (VT).

[0076] In addition, in the parameter determining method according to the embodiment of the present invention, the step of determining first average heart rate parameters corresponding to the plurality of first time periods based on the plurality of first time periods includes the following steps.

[0077] In step S115, a first average heart rate parameter corresponding to each of the first time periods is determined based on the first time periods after the non-resting time periods are removed.

[0078] In view of the fact that the non-resting time period has strong specificity and cannot well represent the typical state of the test subject, the embodiment of the present invention removes the non-resting time period, thereby improving the representation ability of the determined parameters such as the first average heart rate parameter and the first resting heart rate variability parameter.

[0079] 8 is a flowchart of measuring a second set of parameters corresponding to a test object based on a second time interval according to an exemplary embodiment of the present invention. Since the embodiment shown in FIG. 8 can be expanded based on the embodiment shown in FIG. 3, the following description will focus on the differences between the embodiment shown in FIG. 8 and the embodiment shown in FIG. 3, and will omit the common parts.

[0080] 8, in the parameter determining method according to the embodiment of the present invention, the second time period includes a plurality of second time periods, and the second heart rate signature parameters include a second average heart rate parameter and a second resting heart rate parameter, and the step of determining a second parameter set corresponding to the test object according to the second time period includes the following steps:

[0081] In step S210, second average heart rate parameters corresponding to each of the second time periods are determined based on the second time periods.

[0082] For example, the second time period is a time window with a time length of 60 seconds. In other words, step S210 refers to respectively determining second average heart rate parameters corresponding to the multiple time windows according to the multiple time windows included in the second time period.

[0083] Optionally, a second Mean Heart Rate (MHR) parameter corresponding to each time window is the average value of the heart rates that can be measured within that time window.

[0084] In step S220, a second resting heart rate parameter is determined based on the second average heart rate parameters corresponding to each of the plurality of second time periods.

[0085] In one embodiment of the present invention, the second resting heart rate parameter is a Day Rest Heart Rate (Day RHR) parameter.

[0086] Since the second resting heart rate parameter is determined based on the second average heart rate parameters corresponding to the plurality of second time periods, respectively, the obtained second resting heart rate parameter can fully reflect the characteristics of the second average heart rate parameters corresponding to the plurality of second time periods, respectively, so that the obtained second resting heart rate parameter can better represent the heart rate status of the test subject in the second time period.

[0087] The parameter determination method according to the embodiment of the present invention can determine a second average heart rate parameter corresponding to each of the second time periods according to the second time periods, and determine a second resting heart rate parameter according to the second average heart rate parameters corresponding to each of the second time periods, thereby achieving determining a second parameter set corresponding to the test subject according to the second time period. Compared with the real-time heart rate, the second average heart rate parameter and the second resting heart rate parameter can more accurately represent the heart rate status of the test subject in the second time period. Therefore, by predicting the neurohormonal level and / or state of the test subject in the second time period based on the second average heart rate parameter and the second resting heart rate parameter obtained by the embodiment of the present invention, a more accurate neurohormonal prediction result can be obtained.

[0088] 9 is a flowchart of determining a second resting heart rate parameter based on a second average heart rate parameter corresponding to each of a plurality of second time periods according to an exemplary embodiment of the present invention. Since the embodiment shown in FIG. 9 can be expanded based on the embodiment shown in FIG. 8, the following description will focus on the differences between the embodiment shown in FIG. 9 and the embodiment shown in FIG. 8, and will omit the common parts.

[0089] As shown in FIG. 9, in the parameter determining method according to an embodiment of the present invention, the step of determining a second resting heart rate parameter based on second average heart rate parameters corresponding to each of a plurality of second time periods includes the following steps:

[0090] In step S221, the minimum second average heart rate parameter is identified from among the second average heart rate parameters corresponding to each of the plurality of second time periods.

[0091] In step S222, the minimum second average heart rate parameter is determined as the second resting heart rate parameter.

[0092] For example, the number of second time periods included in the second time section is three, which are second time period a, second time period b, and second time period c. Correspondingly, the second average heart rate parameter corresponding to the second time period a is 80 beats / min, the second average heart rate parameter corresponding to the second time period b is 85 beats / min, and the second average heart rate parameter corresponding to the second time period c is 90 beats / min. Obviously, the second average heart rate parameter corresponding to the second time period a (80 beats / min) is the smallest second average heart rate parameter. Therefore, as described in step S222, the second average heart rate parameter corresponding to the second time period a (80 beats / min) can be determined as the second resting heart rate parameter. Note that the second resting heart rate parameter may be described by other statistics, such as a 25% value.

[0093] Similarly, since the smallest second average heart rate parameter among the second average heart rate parameters corresponding to each of the multiple second time periods can represent to some extent the heart rate characteristics of the test subject in the second time period, the embodiment of the present invention can further increase the useful information contained in the second parameter set, and thus improve the prediction accuracy and comparability of neurohormonal levels and / or states.

[0094] Another embodiment of the present invention is obtained by expanding on the embodiment shown in Fig. 8. The embodiment of the present invention further includes a step of removing non-resting time periods corresponding to each of the plurality of second time periods before the step of determining second average heart rate parameters corresponding to each of the plurality of second time periods based on the plurality of second time periods. Here, the step of determining second average heart rate parameters corresponding to each of the plurality of second time periods based on the plurality of second time periods includes a step of determining second average heart rate parameters corresponding to each of the plurality of second time periods based on the plurality of second time periods after the non-resting time periods are removed.

[0095] For example, the test subject is excited (due to a fight or other reasons). Or, the non-resting time period further includes time periods corresponding to events such as premature atrial contraction (PAC), premature ventricular contraction (PVC), atrial tachycardia or atrial arrhythmia (e.g., atrial fibrillation, etc.), and ventricular tachycardia (VT). Thus, the embodiment of the present invention can further improve the prediction accuracy and comparability of the neurohormonal levels and / or states. Here, the detailed meaning of the non-resting time period may be referred to the embodiment shown in FIG. 7 and is omitted in this embodiment.

[0096] 10 is a flowchart of measuring a second set of parameters corresponding to a test object based on a second time interval according to another exemplary embodiment of the present invention. Since the embodiment shown in FIG. 10 can be expanded based on the embodiment shown in FIG. 8, the following description will focus on the differences between the embodiment shown in FIG. 10 and the embodiment shown in FIG. 8, and will omit the common parts.

[0097] As shown in Fig. 10, in the parameter determining method according to the embodiment of the present invention, the second HRV signature parameters include a second HRV parameter at rest, and after determining the second HRV parameter at rest according to second average HRV parameters corresponding to each of a plurality of second time periods, the method further includes the following steps:

[0098] In step S230, the second time period corresponding to the second resting heart rate parameter is determined as a third resting time period.

[0099] In step S240, the HRV parameters corresponding to the third resting time period are determined as second HRV parameters at rest.

[0100] In one embodiment of the present invention, the second resting heart rate variability parameter is a Day Rest Heart Rate Variability (Day RHRV) parameter.

[0101] In practical application, 2 Based on the time interval, a second 2 Determine the parameter set The steps are determine a second average heart rate parameter corresponding to each of the second time periods based on the second time periods, determine a second resting heart rate parameter based on the second average heart rate parameters corresponding to each of the second time periods, determine the second time period corresponding to the second resting heart rate parameter as a third resting time period, and determine the heart rate variability parameter corresponding to the third resting time period as a second resting heart rate variability parameter. This can include .

[0102] Since the resulting second resting heart rate variability parameter is determined based on the second resting heart rate parameter, compared to the prior art, embodiments of the present invention can improve the ability of the determined second resting heart rate variability parameter to represent neurohormonal levels and / or states of the test subject during the second time period.

[0103] In one embodiment of the present invention, the first average heart rate parameter and / or the second average heart rate parameter mentioned in the above embodiment can be changed to other statistical descriptions, such as statistical indicator parameters, such as the median and / or quartiles (e.g. 75% or 25%) of the corresponding heart rates. Or, based on the above embodiment, the first parameter set and / or the second parameter set can be further supplemented with statistical indicator parameters, such as the median and / or quartiles (e.g. 75% or 25%) of the corresponding heart rates. This can improve the flexibility of the parameter determination method and increase the amount of effective information contained in the corresponding parameter set.

[0104] In one embodiment of the present invention, the first HRV signature parameter referred to in the above embodiment includes a corresponding HRV parameter and / or the second HRV signature parameter referred to in the above embodiment includes, but is not limited to, a HRV parameter commonly used in the literature, and the included HRV parameters are obtained using standard deviation information of the heart rate (RR interval or PP interval).

[0105] Another embodiment of the present invention is obtained by extending the embodiment shown in Fig. 3. After the step of determining a second set of parameters corresponding to the test subject based on the second time interval (i.e., step S200), the embodiment of the present invention further includes a step of determining a level and / or state of a neurohormonal corresponding to the test subject based on the first set of parameters and the second set of parameters.

[0106] The embodiment of the present invention can utilize the first and second parameter sets to improve the accuracy of representation of neurohormonal levels and / or states, thus providing a prerequisite for better assisting doctors in diagnosing diseases.

[0107] Exemplary Devices 11 is a structural schematic diagram of a parameter determination device according to an exemplary embodiment of the present invention. As shown in FIG. 11, the parameter determination device according to the embodiment of the present invention includes a first determination module 100 and a second determination module 200.

[0108] The first determination module 100 is configured to determine a first set of parameters corresponding to the test object based on a first time interval, and the second determination module 200 is configured to determine a second set of parameters corresponding to the test object based on a second time interval.

[0109] Figure 12 is a structural schematic diagram of a first determination module according to an exemplary embodiment of the present invention. The embodiment shown in Figure 12 can be expanded based on the embodiment shown in Figure 11, so the following description will focus on the differences between the embodiment shown in Figure 12 and the embodiment shown in Figure 11, and omit the common parts.

[0110] As shown in FIG. 12 , in the parameter determining device according to the embodiment of the present invention, the first determining module 100 includes a first average heart rate parameter determining unit 110 and a first resting heart rate parameter determining unit 120 .

[0111] The first average heart rate parameter determining unit 110 is configured to determine first average heart rate parameters corresponding to each of the plurality of first time periods based on the plurality of first time periods, and the first resting heart rate parameter determining unit 120 is configured to determine the first resting heart rate parameter based on the first average heart rate parameters corresponding to each of the plurality of first time periods.

[0112] In one embodiment of the present invention, the first resting heart rate parameter determination unit 120 is further configured to identify a minimum first average heart rate parameter among the first average heart rate parameters corresponding to each of the multiple first time periods, and determine the minimum first average heart rate parameter as the first resting heart rate parameter.

[0113] Figure 13 is a structural schematic diagram of a first determination module according to another exemplary embodiment of the present invention. The embodiment shown in Figure 13 can be expanded based on the embodiment shown in Figure 12, so the following description will focus on the differences between the embodiment shown in Figure 13 and the embodiment shown in Figure 12, and omit the common parts.

[0114] As shown in FIG. 13, in the parameter determining device according to the embodiment of the present invention, the first determining module 100 further includes a first resting time period determining unit 130 and a first resting HRV parameter determining unit 140 .

[0115] The first resting time period determination unit 130 is configured to determine a first time period corresponding to a first resting heart rate parameter as a first resting time period, and the first resting heart rate variability parameter determination unit 140 is configured to determine a heart rate variability parameter corresponding to the first resting time period as a first resting heart rate variability parameter.

[0116] Figure 14 is a structural schematic diagram of a first determination module according to another exemplary embodiment of the present invention. The embodiment shown in Figure 14 can be expanded based on the embodiment shown in Figure 12, so the following description will focus on the differences between the embodiment shown in Figure 14 and the embodiment shown in Figure 12, and omit the common parts.

[0117] As shown in Fig. 14, the parameter determining apparatus according to the embodiment of the present invention further includes a non-rest time interval removing unit 105. The non-rest time interval removing unit 105 is configured to remove non-rest time intervals corresponding to each of a plurality of first time periods.

[0118] In addition, in the parameter determining device according to the embodiment of the present invention, the first average heart rate parameter determining unit 110 includes a first average heart rate parameter determining subunit 115. The first average heart rate parameter determining subunit 115 is configured to determine first average heart rate parameters corresponding to each of the plurality of first time periods based on the plurality of first time periods after the non-resting time periods are removed.

[0119] Figure 15 is a structural schematic diagram of a second determination module according to an exemplary embodiment of the present invention. The embodiment shown in Figure 15 can be expanded based on the embodiment shown in Figure 12, so the following description will focus on the differences between the embodiment shown in Figure 15 and the embodiment shown in Figure 12, and omit the common parts.

[0120] As shown in FIG. 15 , in the parameter determining device according to the embodiment of the present invention, the second determining module 200 includes a second average heart rate parameter determining unit 210 and a second resting heart rate parameter determining unit 220 .

[0121] The second average heart rate parameter determining unit 210 is configured to determine second average heart rate parameters corresponding to each of the plurality of second time periods based on the plurality of second time periods, and the second resting heart rate parameter determining unit 220 is configured to determine second resting heart rate parameters based on the second average heart rate parameters corresponding to each of the plurality of second time periods.

[0122] In one embodiment of the present invention, the second resting heart rate parameter determination unit 220 is further configured to identify a minimum second average heart rate parameter among the second average heart rate parameters corresponding to each of the plurality of second time periods, and determine the minimum second average heart rate parameter as the second resting heart rate parameter.

[0123] Figure 16 is a structural schematic diagram of a second determination module according to another exemplary embodiment of the present invention. The embodiment shown in Figure 16 can be expanded based on the embodiment shown in Figure 15, so the following description will focus on the differences between the embodiment shown in Figure 16 and the embodiment shown in Figure 15, and omit the common parts.

[0124] As shown in FIG. 16 , in the parameter determining device according to the embodiment of the present invention, the second determining module 200 further includes a third resting time period determining unit 230 and a second resting HRV parameter determining unit 240 .

[0125] The third resting time period determination unit 230 is configured to determine a second time period corresponding to the second resting heart rate parameter as the third resting time period, and the second resting heart rate variability parameter determination unit 240 is configured to determine a heart rate variability parameter corresponding to the third resting time period as the second resting heart rate variability parameter.

[0126] In addition, the first determination module 100 and the second determination module 200 in the parameter determination device according to FIG. 11 to FIG. 16, the first average heart rate parameter determination unit 110, the first resting heart rate parameter determination unit 120, the first resting period determination unit 130, and the second resting period determination unit 140, all of which are included in the first determination module 100, and , a first resting HRV parameter determination unit 140, a second average HRV parameter determination unit 210, a second resting HRV parameter determination unit 220, a third resting time period determination unit 230, a second resting HRV parameter determination unit 240, and a first resting HRV parameter determination subunit included in the first resting HRV parameter determination unit 140. and For the operation and function of the parameter determination method according to the above-mentioned FIGS. 3 to 10, they will be omitted here to avoid duplication.

[0127] In addition, the parameter determination device mentioned in the above-mentioned embodiments may be equipped with the parameter determination method according to the above-mentioned embodiments in itself to realize functions such as definition, detection, etc. of abnormal heart rate events (including, but not limited to, PVC or PAC, non-sustained VT, Atrial Fibrillation (AF), Ventricular Tachycardia (VT) and Ventricular Fibrillation (VF)), or may be combined with conventional medical equipment / device to realize the parameter determination method according to the above-mentioned embodiments using reference parameters collected by the data collection function of the conventional medical equipment / device and / or the judgment function of the conventional medical equipment / device, and may use the first parameter set and the second parameter set determined by the parameter determination method.

[0128] Hereinafter, an electronic device according to an embodiment of the present invention will be described with reference to Fig. 17. Fig. 17 is a structural schematic diagram of an electronic device according to an exemplary embodiment of the present invention.

[0129] As shown in FIG. 17, an electronic device 1700 includes one or more processors 1701 and a memory 1702 .

[0130] The processor 1701 may be a central processing unit (CPU) or other type of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device 1700 to perform desired functions.

[0131] The memory 1702 may include one or more computer program products. The computer program products may include various types of computer readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored in the computer readable storage medium, and the processor 1701 may execute the program instructions to realize the parameter determination method according to each embodiment of the present invention described above and / or other desired functions. The computer readable storage medium may further store various contents, such as heart rate information.

[0132] In one example, electronic device 1700 may further include input devices 1703 and output devices 1704, and these components may be connected together by a bus system and / or other type of connection means (not shown).

[0133] The input device(s) 1703 may include, for example, a keyboard, a mouse, and the like.

[0134] The output device 1704 can output various information (including the first and second parameter sets that can be determined) to the outside. The output device 1704 can include, for example, a display, a speaker, a printer, a communication network, and a remote output device connected thereto.

[0135] Of course, for the sake of simplicity, Fig. 17 shows only some components related to the present invention in the electronic device 1700, and omits components such as buses, input / output ports, etc. In addition, the electronic device 1700 may include any other suitable components according to the detailed application.

[0136] In addition to the methods and devices described above, an embodiment of the present invention may also be a computer program product having computer program instructions that, when executed by a processor, cause the processor to perform the steps of the parameter determination methods according to each embodiment of the present invention described herein.

[0137] The computer program product may include program code for performing operations according to embodiments of the present invention compiled in any combination of one or more programming languages, including object-oriented programming languages ​​(e.g., Java, C++, etc.), and further including general procedural programming languages ​​(e.g., "C" or similar programming languages). The program code may be executed entirely on the user computing device, partially on the user device, as a separate software pack, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0138] Furthermore, an embodiment of the present invention may be a computer readable storage medium having computer program instructions stored thereon, which, when executed by a processor, cause the processor to perform steps of the parameter determination method according to each embodiment of the present invention described herein.

[0139] A computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include an electrical connection having one or more conductors, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), a programmable erasable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical memory component, a magnetic memory component, or any suitable combination of the above.

[0140] Although the basic principles of the present invention have been described above based on specific embodiments, the advantages, merits, effects, etc. mentioned in the present invention are merely illustrative and not limiting. These advantages, merits, effects, etc. should not be considered as essential to any embodiment of the present invention. Furthermore, the detailed details described above are merely illustrative and for the purpose of aiding understanding, and are not limiting. The details described above do not necessarily limit the present invention to be realized with the detailed details described above.

[0141] Block diagrams of devices, apparatus, facilities, and systems according to the present invention are illustrative examples only and are not intended to require or imply that they must be connected, arranged, or configured in the manner depicted in the block diagrams. As will be understood by those skilled in the art, these devices, apparatus, facilities, and systems can be connected, arranged, or configured in any manner. Terms such as "including," "comprising," and "having" are open-ended terms and are interchangeable, meaning "including but not limited to." As used herein, the terms "or" and "and" mean "and / or" and are interchangeable, unless the context clearly dictates otherwise. As used herein, the term "for example" means "for example, but not limited to" and is interchangeable.

[0142] Furthermore, in the apparatus, devices and methods according to the present invention, each part or each step can be disassembled and / or recombined, which disassembly and / or recombination should be considered as equivalent forms of the present invention.

[0143] The above description of the embodiments is disclosed to enable any person skilled in the art to realize or use the present invention. Various modifications of these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the scope of the present invention. Thus, the present invention is not intended to be limited to the embodiments disclosed herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0144] The foregoing description has been presented for purposes of illustration and description, and is not intended to limit the embodiments of the present invention to the precise form disclosed herein. While a number of exemplary aspects and embodiments have been described above, those skilled in the art will appreciate modifications, variations, additions, and subcombinations thereof.

Claims

1. A parameter determination method executed by a server or a medical device, comprising: determining a first parameter set corresponding to the test subject based on a first time period, the first time period including a nighttime period, the first parameter set including a first heart rate signature parameter and a first heart rate variability signature parameter, the first heart rate signature parameters including a first average heart rate parameter and a first resting heart rate parameter, and the first heart rate variability signature parameters including a first resting heart rate variability parameter; determining a second set of parameters corresponding to the test subject based on a second time period, the second time period including a daytime period, the second set of parameters including a second heart rate signature parameter and a second heart rate variability signature parameter, the second heart rate signature parameters including a second average heart rate parameter and a second resting heart rate parameter, and the second heart rate variability signature parameters including a second resting heart rate variability parameter; wherein the first time interval includes a plurality of first time periods, and the step of determining a first parameter set corresponding to the test object based on the first time interval includes: determining a first average heart rate parameter corresponding to each of the first time periods based on the plurality of first time periods; determining the first resting heart rate parameters based on first average heart rate parameters corresponding to each of the plurality of first time periods, the first resting heart rate parameters including a sleep resting heart rate parameter; determining a first time period corresponding to the first resting heart rate parameter as a first resting time period; determining a heart rate variability parameter corresponding to the first resting time period as the first resting heart rate variability parameter, the first resting heart rate variability parameter including a sleep resting heart rate variability parameter; and, The second time interval includes a plurality of second time periods, and the step of determining a second set of parameters corresponding to the test object based on the second time interval includes: determining second average heart rate parameters corresponding to each of the second time periods based on the second time periods; determining said second resting heart rate parameters based on second average heart rate parameters corresponding to each of said plurality of second time periods, said second resting heart rate parameters including a daytime resting heart rate parameter; determining a second time period corresponding to the second resting heart rate parameter as a third resting time period; determining a heart rate variability parameter corresponding to the third resting time period as the second resting heart rate variability parameter, the second resting heart rate variability parameter including a daytime resting heart rate variability parameter; A parameter determination method comprising:

2. determining the first resting heart rate parameter based on a first average heart rate parameter corresponding to each of the plurality of first time periods, identifying a minimum first average heart rate parameter among the first average heart rate parameters corresponding to each of the plurality of first time periods; determining said minimum first average heart rate parameter as said first resting heart rate parameter.

2. The parameter determination method according to claim 1 .

3. determining the first resting heart rate parameter based on a first average heart rate parameter corresponding to each of the plurality of first time periods, selecting a preset time interval from the first time interval, the preset time interval having a length shorter than the first time interval; Identifying a minimum first average heart rate parameter among first average heart rate parameters corresponding to a plurality of first time slots included in the preset time section; determining said minimum first average heart rate parameter as said first resting heart rate parameter.

2. The parameter determination method according to claim 1 .

4. prior to the step of determining a first average heart rate parameter corresponding to each of the first time periods based on the plurality of first time periods, The method further includes removing a non-rest time period corresponding to each of the plurality of first time periods; Here, the step of determining a first average heart rate parameter corresponding to each of the first time periods based on the first time periods includes: determining a first average heart rate parameter corresponding to each of the first time periods based on the first time periods after the non-resting time period is removed.

3. The parameter determination method according to claim 2.

5. The first time period includes a time period from 22:00 of one day to 6:00 of the next day, and the second time period includes a time period from 8:00 of one day to 20:00 of the same day.

2. The parameter determination method according to claim 1 .

6. determining the second resting heart rate parameter based on second average heart rate parameters corresponding to each of the plurality of second time periods, identifying a minimum second average heart rate parameter among the second average heart rate parameters corresponding to each of the plurality of second time periods; determining the minimum second average heart rate parameter as the second resting heart rate parameter.

2. The parameter determination method according to claim 1 .

7. prior to the step of determining second average heart rate parameters corresponding to each of the plurality of second time periods based on the plurality of second time periods; The method further includes removing a non-rest time period corresponding to each of the plurality of second time periods; Here, the step of determining second average heart rate parameters corresponding to each of the second time periods based on the second time periods includes: determining second average heart rate parameters corresponding to the second time periods based on the second time periods after the non-resting time periods are removed.

2. The parameter determination method according to claim 1 .

8. after the step of determining a second set of parameters corresponding to the test object based on a second time interval; determining a neurohormonal level and / or state corresponding to the test subject based on the first set of parameters and the second set of parameters.

2. The parameter determination method according to claim 1 .

9. A parameter determination device, comprising: a first determination module and a second determination module; The first determination module is configured to determine a first parameter set corresponding to the test subject based on a first time period, the first time period including a nighttime period, the first parameter set including a first heart rate signature parameter and a first heart rate variability signature parameter, the first heart rate signature parameter including a first average heart rate parameter and a first resting heart rate parameter, and the first heart rate variability signature parameter including a first resting heart rate variability parameter; The second determination module is configured to determine a second set of parameters corresponding to the test subject based on a second time period, the second time period including a daytime period, the second set of parameters including a second heart rate signature parameter and a second heart rate variability signature parameter, the second heart rate signature parameter including a second average heart rate parameter and a second resting heart rate parameter, and the second heart rate variability signature parameter including a second resting heart rate variability parameter; Wherein, the first time period includes a plurality of first time periods, and the first determination module includes a first average heart rate parameter determination unit, a first resting heart rate parameter determination unit, a first resting time period determination unit and a first resting heart rate variability parameter determination unit; The first average heart rate parameter determining unit is configured to determine, based on the plurality of first time periods, a first average heart rate parameter corresponding to each of the plurality of first time periods; The first resting heart rate parameter determining unit is configured to determine the first resting heart rate parameter based on a first average heart rate parameter corresponding to each of the plurality of first time periods, the first resting heart rate parameter including a sleep resting heart rate parameter; The first resting time period determining unit is configured to determine a first time period corresponding to the first resting heart rate parameter as a first resting time period; The first resting HRV parameter determination unit is configured to determine a HRV parameter corresponding to the first resting time period as the first resting HRV parameter, and the first resting HRV parameter includes a sleep resting HRV parameter; And the second time period includes a plurality of second time periods, and the second determination module includes a second average heart rate parameter determination unit, a second resting heart rate parameter determination unit, a second resting time period determination unit and a second resting heart rate variability parameter determination unit; The second average heart rate parameter determining unit is configured to determine, based on the second time periods, second average heart rate parameters corresponding to each of the second time periods; The second resting heart rate parameter determining unit is configured to determine the second resting heart rate parameter based on second average heart rate parameters corresponding to each of the plurality of second time periods, the second resting heart rate parameters including a daytime resting heart rate parameter; The second resting time period determining unit is configured to determine a second time period corresponding to the second resting heart rate parameter as a third resting time period; The second resting HRV parameter determination unit is configured to determine a HRV parameter corresponding to the third resting time period as the second resting HRV parameter, and the second resting HRV parameter includes a daytime resting HRV parameter. A parameter determination device comprising:

10. A parameter determination method executed by a server or a medical device, comprising: determining a first parameter set corresponding to the test subject based on a first time period, the first time period including a nighttime period, the first parameter set including a first heart rate signature parameter and a first heart rate variability signature parameter, the first heart rate signature parameters including a first average heart rate parameter and a first resting heart rate parameter, and the first heart rate variability signature parameters including a first resting heart rate variability parameter; determining a second set of parameters corresponding to the test subject based on a second time period, the second time period including a daytime period, the second set of parameters including a second heart rate signature parameter and a second heart rate variability signature parameter, the second heart rate signature parameters including a second average heart rate parameter and a second resting heart rate parameter, and the second heart rate variability signature parameters including a second resting heart rate variability parameter; wherein the first time interval includes a plurality of first time periods, and the step of determining a first parameter set corresponding to the test object based on the first time interval includes: determining first heart rate variability parameters corresponding to each of the first time periods based on the first time periods; determining the first resting heart rate variability parameters based on first heart rate variability parameters corresponding to each of the plurality of first time periods, the first resting heart rate variability parameters including a sleep resting heart rate variability parameter; determining a first time period corresponding to the first resting heart rate variability parameter as a first resting time period; determining a first average heart rate parameter corresponding to the first resting time period as the first resting heart rate parameter, the first resting heart rate parameter including a sleep resting heart rate parameter; and, The second time interval includes a plurality of second time periods, and the step of determining a second set of parameters corresponding to the test object based on the second time interval includes: determining second heart rate variability parameters corresponding to each of the second time periods based on the second time periods; determining the second resting heart rate variability parameters based on second heart rate variability parameters corresponding to each of the plurality of second time periods, the second resting heart rate variability parameters including a daytime resting heart rate variability parameter; determining a second time period corresponding to the second resting heart rate variability parameter as a second resting time period; determining a second average heart rate parameter corresponding to the second resting time period as the second resting heart rate parameter, the second resting heart rate parameter comprising a daytime resting heart rate parameter. A parameter determination method comprising:

11. The step of determining the first resting heart rate variability parameter based on the first heart rate variability parameters corresponding to each of the plurality of first time periods includes: Identifying a maximum first heart rate variability parameter among the first heart rate variability parameters corresponding to each of the plurality of first time periods; determining the maximum first HRV parameter as the first resting HRV parameter.

11. The parameter determination method according to claim 10.

12. The step of determining the first resting heart rate variability parameter based on the first heart rate variability parameters corresponding to each of the plurality of first time periods includes: selecting a preset time interval from the first time interval, the preset time interval having a length shorter than the first time interval; Identifying a maximum first heart rate variability parameter among first heart rate variability parameters corresponding to each of a plurality of first time periods included in the preset time section; determining the maximum first HRV parameter as the first resting HRV parameter.

11. The parameter determination method according to claim 10.

13. The step of determining the second resting heart rate variability parameter based on the second heart rate variability parameters corresponding to each of the plurality of second time periods includes: Identifying a maximum second heart rate variability parameter among the second heart rate variability parameters corresponding to each of the plurality of second time periods; determining the maximum second HRV parameter as the second resting HRV parameter.

11. The parameter determination method according to claim 10.

14. 1. A computer-readable storage medium, comprising: The storage medium stores a computer program, the computer program being configured to execute the parameter determination method according to any one of claims 1 to 8 or 10 to 13. A computer-readable storage medium comprising:

15. 1. An electronic device comprising: The electronic device comprises a processor and a memory storing instructions executable by the processor; The processor is configured to perform a parameter determination method according to any one of claims 1 to 8 or 10 to 13.

1. An electronic device comprising:

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