Method for predicting calving period of livestock and device for predicting calving period of livestock

Abstract

To achieve a technique that predicts the calving period of livestock.SOLUTION: A device for predicting the calving period of livestock (10) includes: an analysis section (14) that segregates electrocardiographic data representing the time-based changes over a predetermined period in heart rate information from electrocardiograms measured in the subject livestock, into diurnal variability components, trend components, and residual components; and a prediction section (15) that predicts the calving period of the subject livestock on the basis of an inflection point in the trend components determined by the analysis part (14).SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a method for predicting the time of parturition of livestock and a device for predicting the time of parturition of livestock. [Background technology]

[0002] In recent years, with the decline in the number of livestock workers and the increase in the number of livestock per farm household, the number of livestock workers per farm is decreasing. When livestock give birth, livestock workers often need to be present and provide support. Because the timing of birth cannot be predicted, observation may be required day and night for several days. However, in a situation where the number of livestock workers per livestock is decreasing, this places a heavy burden on farms. As a means for solving such problems, a method for predicting the time of parturition using information on the heart rate of livestock as an index is used (Patent Document 1 and Non-Patent Document 1). Patent Document 1 describes that a transient decrease in heart rate occurs that is specific only to parturition. Non-Patent Document 1 also describes that a high percentage of livestock show a heart rate ratio of 1.3 or higher within two days of parturition compared to the heart rate 30 days before parturition. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP2008-11916 Public Relations [Non-patent literature]

[0004] [Non-Patent Document 1] Fujimoto et al., Bulletin of the Japanese Society of Animal Science, Vol. 59, No. 4, pp. 301-305, 1988 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the above-mentioned conventional technology has the problem that it can only predict parturition immediately before it occurs because it detects a transient decrease in heart rate that is unique to parturition. Furthermore, since parturition is predicted based on the heart rate ratio compared to the heart rate 30 days before parturition, it is necessary to determine approximately 30 days before parturition, but this determination may be difficult due to individual differences. If the time of parturition could be predicted at the appropriate time, it would be possible to prepare a sufficient support system at the time of parturition, which would reduce the burden on livestock workers and be useful. One aspect of the present invention has been made to solve the above-mentioned problems, and an object of the present invention is to realize a technology for predicting the time of parturition in livestock. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems, one embodiment of the present invention provides a method for predicting the timing of parturition in livestock, which includes an analysis step of decomposing electrocardiogram data representing the temporal progression of heart rate information obtained from an electrocardiogram measured in a test livestock over a predetermined period of time into a diurnal fluctuation component, a trend component, and a residual component, and a prediction step of predicting the timing of parturition in the test livestock based on the inflection point of the trend component obtained in the analysis step.

[0007] In the method for predicting the timing of parturition in livestock according to one aspect of the present invention, the prediction step may predict the parturition time of the subject livestock to be 30 to 80 hours after the inflection point of the trend component.

[0008] In a method for predicting the timing of livestock parturition according to one aspect of the present invention, the inflection point of the trend component may be a time point at which the difference between the trend component and the moving average of the trend component reaches a minimum value greater than or equal to 0.

[0009] In the method for predicting the timing of parturition in livestock according to one aspect of the present invention, the predetermined period may be one week or more before the expected date of parturition of the test livestock.

[0010] In the method for predicting the timing of parturition of livestock according to one aspect of the present invention, the moving average may be an average value for 6 to 18 hours immediately before the calculation point.

[0011] Another aspect of the present invention relates to a method for predicting the time of parturition in livestock, which includes an analysis step of comparing a first average value of heart rate information obtained from an electrocardiogram measured in a test livestock over a predetermined time period with a second average value of the heart rate information over the predetermined time period on at least one of the previous day and the day before that, and a prediction step of predicting the time of parturition in the test livestock based on the results of the comparison in the analysis step.

[0012] In another aspect of the method for predicting the time of livestock delivery of the present invention, the specified time range may be either a consecutive 4 to 5 hour period between 1:00 and 8:00, or a consecutive 1 to 3 hour period between 1:00 and 17:00.

[0013] In another aspect of the method for predicting the time of delivery of livestock according to the present invention, when the first average value is lower than the second average value in the prediction step, the time of delivery of the test livestock may be predicted to be within 20 to 30 hours from the date of calculation of the first average value.

[0014] In another aspect of the method for predicting the time of delivery of livestock, in the prediction step, when the first average value is lower than the second average value by 5% or more, the delivery time of the test livestock may be predicted to be within 20 to 30 hours from the date of calculation of the first average value.

[0015] A livestock parturition timing prediction device according to one embodiment of the present invention comprises an analysis unit that decomposes electrocardiogram data representing the temporal progression of heart rate information obtained from an electrocardiogram measured on a test livestock over a predetermined period of time into a diurnal fluctuation component, a trend component, and a residual component, and a prediction unit that predicts the parturition timing of the test livestock based on the inflection point of the trend component obtained by the analysis unit.

[0016] Another aspect of the present invention provides a livestock parturition timing prediction device that includes an analysis unit that compares a first average value of heart rate information obtained from an electrocardiogram measured on a test livestock over a predetermined time period with a second average value of the heart rate information over the predetermined time period on at least one of the previous day and the day before that, and a prediction unit that predicts the parturition timing of the test livestock based on the results of the comparison made by the analysis unit. [Effects of the Invention]

[0017] According to one aspect of the present invention, a technology for predicting the timing of livestock parturition can be realized. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a block diagram showing the configuration of a main part of a delivery timing prediction device according to one aspect of the present invention. [Figure 2] FIG. 1 is a diagram illustrating an outline of trend analysis. [Figure 3] 10 is a flowchart illustrating an example of a delivery timing prediction process executed by a delivery timing prediction device according to an aspect of the present invention. [Figure 4] 10 is a flowchart illustrating another example of the delivery timing prediction process executed by the delivery timing prediction device according to an aspect of the present invention. [Figure 5] FIG. 10 is a diagram showing the results of trend analysis in an example. [Figure 6] FIG. 10 is a diagram showing the results of trend analysis in an example. [Figure 7] FIG. 10 is a diagram showing the extraction results of inflection points in an example. [Figure 8] FIG. 10 is a diagram showing the extraction results of inflection points in an example. [Figure 9] FIG. 10 is a diagram showing the extraction results of inflection points in an example. [Figure 10] FIG. 10 is a diagram showing the extraction results of inflection points in an example. [Figure 11] FIG. 10 is a diagram showing the results of parturition time prediction in an example. [Figure 12] FIG. 10 is a diagram showing the results of parturition time prediction in an example. [Figure 13]FIG. 10 is a diagram showing the results of parturition time prediction in an example. [Figure 14] FIG. 10 is a diagram showing the results of parturition time prediction in an example. DETAILED DESCRIPTION OF THE INVENTION

[0019] [Method for predicting delivery time] One aspect of the present invention provides a calving timing prediction method for predicting the calving timing of livestock. In the calving timing prediction method according to one aspect of the present invention, examples of livestock for which the calving timing is predicted include cows, horses, pigs, goats, sheep, etc. In the calving timing prediction method, one example of the livestock for which the calving timing is predicted is cows.

[0020] A method for predicting the timing of parturition in livestock according to one aspect of the present invention predicts the timing of parturition in livestock using heartbeat information of the livestock as an index. Here, heartbeat information is information that represents the pulsation, which is the electrical activity of the heart, and examples include the heart rate and heartbeat interval obtained from an electrocardiogram, which represents the pulsation as a waveform signal, and the pulse wave, pulse rate, and pulse interval, which represent changes in the flow rate in peripheral blood vessels transmitted in accordance with the pulsation. In this embodiment, the prediction of the timing of parturition in livestock will be mainly described using the R-R interval, which represents the interval between heartbeats (R waves), out of the heartbeat information obtained from an electrocardiogram.

[0021] A method for predicting the time of parturition in livestock according to one embodiment of the present invention includes an analysis step of decomposing electrocardiogram data representing the temporal progression of heart rate information obtained from an electrocardiogram measured in a test livestock over a predetermined period of time into a diurnal fluctuation component, a trend component, and a residual component, and a prediction step of predicting the time of parturition in the test livestock based on the inflection point of the trend component obtained in the analysis step.

[0022] An example of a livestock parturition timing prediction method according to one aspect of the present invention is a livestock parturition timing prediction process executed in a livestock parturition timing prediction device 10 shown in Fig. 1. Therefore, in this embodiment, a livestock parturition timing prediction method according to one aspect of the present invention will be described as a livestock parturition timing prediction process executed in the livestock parturition timing prediction device 10.

[0023] (Parturition time prediction device 10) Fig. 1 is a block diagram showing the main configuration of a delivery timing prediction device 10 according to one embodiment of the present invention. As shown in Fig. 1, the delivery timing prediction device 10 is connected to a measurement device 20, a storage device 30, and an output device 40 so as to be able to send and receive data.

[0024] The measuring device 20 measures the electrocardiogram of livestock. As an example, the measuring device 20 is a wearable device attached to the body of the livestock. As an example, the measuring device 20 is equipped with a plurality of electrodes, and measures the electrocardiogram by detecting the current flowing between the electrodes attached to the livestock. Another example of the measuring device 20 is equipped with a light source (LED or laser) and a photodiode, and measures a pulse wave from which an RR interval approximates an electrocardiogram by detecting light emitted from the light source and reflected from the blood vessels of the livestock with the photodiode. The RR interval is the interval between heartbeats (R waves) on an electrocardiogram, and is a value corresponding to the heart rate within a certain period of time.

[0025] The measurement device 20 outputs the measured electrocardiogram to the storage device 30, and stores the heart rate information obtained from electrocardiograms continuously measured within a predetermined period in chronological order. This makes it possible to obtain changes in the heart rate information over time. The measurement device 20 may also output the measured electrocardiogram to the delivery timing prediction device 10. The measurement device 20 may be configured to constantly measure the electrocardiogram, or may be configured to measure it periodically at predetermined intervals.

[0026] The storage device 30 stores programs and data used by the delivery timing prediction device 10. The storage device 30 stores electrocardiograms measured by the measurement device 20. As an example, the storage device 30 stores, in chronological order, heart rate information obtained from electrocardiograms measured continuously within a predetermined period. The storage device 30 may have a database on the cloud or a server that stores electrocardiograms and heart rate information.

[0027] The storage device 30 preferably stores heart rate information obtained from the electrocardiogram measured by the measurement device 20 in association with the measurement time. The heart rate information may be waveform data representing the electrocardiogram within a predetermined period.

[0028] The output device 40 outputs information regarding the delivery time predicted by the delivery time prediction device 10. There are no particular limitations on the manner of output by the output device 40. The output device 40 may be, for example, a display device that displays the information as an image, a printing device that prints the information, or an alarm device that outputs the information as sound.

[0029] The delivery timing prediction device 10 includes a control unit 11. The control unit 11 controls each unit of the delivery timing prediction device 10, and is realized by a processor and a memory, for example. In this example, the processor accesses a storage (not shown), loads a program (not shown) stored in the storage into the memory, and executes a series of instructions included in the program. This configures each unit of the control unit 11. As each unit, the control unit 11 includes a data acquisition unit 12, a data conversion unit 13, an analysis unit 14, and a prediction unit 15.

[0030] The data acquiring unit 12 acquires heart rate information obtained from an electrocardiogram measured by the measurement device 20. The data acquiring unit 12 acquires the heart rate information based on an input signal representing an instruction to start prediction from an input device (not shown). As an example, the data acquiring unit 12 may read the heart rate information from the storage device 30 or acquire the heart rate information directly from the measurement device 20. The data acquiring unit 12 outputs the acquired heart rate information to the data converting unit 13.

[0031] The data conversion unit 13 acquires heartbeat information and converts it into data representing R-R intervals, which are intervals between heartbeats (R waves). As an example, the data conversion unit 13 acquires waveform data representing an electrocardiogram within a predetermined period and generates R-R interval data (electrocardiogram data) representing changes in the R-R intervals over time from the waveform data. The data conversion unit outputs the generated R-R interval data to the analysis unit 14.

[0032] Here, the waveform data may be waveform data representing an electrocardiogram of the test livestock one week or more before the expected calving date, and more preferably waveform data representing an electrocardiogram of the test livestock two weeks or more before the expected calving date. One example of the waveform data is waveform data representing electrocardiograms measured continuously from one week before the expected calving date to the expected calving date, more preferably from two weeks before the expected calving date to the expected calving date. The expected calving date is set based on the breeding date of the livestock, and for example, in the case of dairy cows, it may be 280 days after the breeding date.

[0033] The analysis unit 14 decomposes RR interval data, which represents the temporal transition of RR intervals, which are intervals between heartbeats (R waves) obtained from an electrocardiogram measured in a test livestock, over a predetermined period of time, into a diurnal fluctuation component, a trend component, and a residual component. As shown in FIG. 2, the analysis unit 14 performs trend analysis on the RR interval data to decompose the RR interval data into the diurnal fluctuation component, trend component, and residual component. FIG. 2 is a diagram illustrating an overview of trend analysis. The diurnal fluctuation component is a data component that represents the daily fluctuation of the RR interval. The trend component is a data component that represents a general tendency of the temporal transition of the RR interval. The residual component is a data component that represents a numerical difference that is neither diurnal fluctuation nor a trend. The analysis unit 14 outputs the trend component to the prediction unit 15.

[0034] The trend analysis of the RR interval data in the analysis unit 14 can be performed using a conventionally known trend analysis algorithm, such as STL (Seasonal Decomposition of Time Series by Loess) decomposition (RB Cleveland et al., Journal of Official Statistics, 6, 3-73, 1990).

[0035] The prediction unit 15 predicts the time of parturition of the test livestock based on the inflection points of the trend component. The prediction unit 15 extracts the inflection points of the trend component. As an example, the inflection points of the trend component may be transient peak values ​​or inflection points seen in a trend graph representing the trend component. The method for extracting the inflection points of the trend component in the prediction unit 15 is not particularly limited, and the inflection points may be extracted by visually checking the trend graph. Examples of inflection points extracted in the trend graph are shown in Figures 5 and 6, which show the results of the Examples described below.

[0036] Furthermore, the prediction unit 15 may extract, as an inflection point of the trend component, a time point at which the difference between the trend component and the moving average of the trend component becomes a minimum value greater than or equal to 0. The prediction unit 15 extracts, as an inflection point, a point at which the difference between the trend component and the moving average becomes 0 or a point at which the difference becomes a minimum value greater than or equal to 0.

[0037] The moving average used to extract the inflection point of the trend component may be calculated from the measurement value of the previous day, or may be calculated from the measurement value for a predetermined time immediately prior to the calculation time. As an example, the moving average is the average value for the 6 to 18 hours immediately prior to the calculation time. Furthermore, the moving average is preferably the average value for the 8 to 15 hours immediately prior to the calculation time, more preferably the average value for the 10 to 13 hours immediately prior to the calculation time, and as an example, the average value for the 12 hours immediately prior to the calculation time.

[0038] The calculation of the moving average in the prediction unit 15 can be performed using a conventionally known moving average calculation algorithm. Examples of the moving average calculation algorithm include DPO (Detrended Price Oscillator) and MAD (Moving Average Deviation Rate). The prediction unit 15 can modify these moving average calculation algorithms to calculate the moving average using measured values ​​for a predetermined time immediately before the calculation time, and use the modified algorithm to calculate the moving average. Examples of inflection points extracted based on the difference between the trend component and the moving average of the trend component are shown in Figures 7 to 10, which show the results of examples described later.

[0039] The prediction unit 15 predicts the parturition time of the test livestock to be 30 to 80 hours after the inflection point of the trend component. As an example, the prediction unit 15 predicts the parturition time of the test livestock to be 35 to 75 hours, preferably 36 to 72 hours, after the inflection point of the trend component. In other words, the prediction unit 15 predicts the parturition time of the test livestock to be 2 to 3 days after the inflection point of the trend component. The prediction unit 15 outputs information indicating the predicted parturition time of the test livestock to the output device 40. The prediction unit 15 may store the information indicating the predicted parturition time of the test livestock in the storage device 30.

[0040] (Flow of delivery prediction process) FIG. 3 is a flowchart illustrating an example of a delivery timing prediction process executed by a delivery timing prediction device according to an aspect of the present invention.

[0041] First, the data acquisition unit 12 acquires heart rate information obtained from an electrocardiogram measured by the measurement device 20 (step S11). Next, the data conversion unit 13 acquires the heart rate information and generates RR interval data representing the time transition of the RR interval (step S12). Then, the analysis unit 14 performs trend analysis on the RR interval data and decomposes it into a diurnal fluctuation component, a trend component, and a residual component (step S13). The prediction unit 15 extracts an inflection point of the trend component and predicts the time of parturition of the test livestock (step S14), and the parturition time prediction process ends.

[0042] According to a method and device for predicting the time of parturition for livestock in accordance with one aspect of the present invention, the time of parturition for livestock can be predicted based on the electrocardiogram of the test livestock. Also, according to a method and device for predicting the time of parturition for livestock in accordance with one aspect of the present invention, the time of parturition is predicted based on electrocardiograms from a predetermined period before the expected date of parturition, thereby shortening the observation period for the test livestock. Furthermore, according to a method and device for predicting the time of parturition for livestock in accordance with one aspect of the invention, the expected time of parturition can be predicted two to three days before parturition, thereby ensuring sufficient time to prepare for parturition.

[0043] When livestock give birth, it is often necessary for livestock workers to be present and provide support. If the time of birth cannot be predicted, it may be necessary to observe the livestock day and night for several days. Furthermore, if the time of birth is predicted at the last minute, there may not be enough time to prepare before the birth and sufficient support may not be possible. According to a method and device for predicting the time of livestock birth according to one aspect of the invention, the time of birth can be predicted several days before the birth, so long-term observation is not necessary and sufficient time for preparation can be secured.

[0044] (Variations of the method for predicting the time of delivery) A method for predicting the time of parturition in livestock according to one embodiment of the present invention may predict the time of parturition in livestock by analyzing an electrocardiogram as described below.

[0045] A modified example of a method for predicting the time of delivery in livestock according to one embodiment of the present invention includes an analysis step of comparing a first average value of heart rate information obtained from an electrocardiogram measured in a test livestock over a predetermined time period with a second average value of the heart rate information over the predetermined time period on at least one of the previous day and the day before that, and a prediction step of predicting the time of delivery of the test livestock based on the results of the comparison in the analysis step.

[0046] An example of a livestock parturition timing prediction method according to an aspect of the present invention relating to a modified example is a modified example of the livestock parturition timing prediction process executed in the livestock parturition timing prediction device 10 shown in Fig. 1. Therefore, in this embodiment, a modified example of the livestock parturition timing prediction method according to an aspect of the present invention will be described as a modified example of the livestock parturition timing prediction process executed in the livestock parturition timing prediction device 10. Note that in the modified example, only the differences from the livestock parturition timing prediction method and parturition timing prediction device according to an aspect of the present invention described above will be described, and a description of the common points will be omitted.

[0047] In a modified example, the analysis unit 14 compares a first average value of the RR intervals obtained from the electrocardiogram measured in the test livestock over a predetermined time span with a second average value of the RR intervals over the predetermined time span on at least one of the previous day and the day before that. The analysis unit 14 calculates the first average value over the predetermined time span using the RR interval data generated by the data conversion unit 13. Then, the analysis unit 14 calculates a second average value over the same time span as the predetermined time span used to calculate the first average value on at least one of the day before and the day before that on which the measurement values ​​used to calculate the first average value were measured.

[0048] As an example, the predetermined time span is either a four to five consecutive hour period between 1:00 and 8:00, or a one to three consecutive hour period between 1:00 and 17:00. The analysis unit 14 calculates the average value of the R-R intervals for the four to five consecutive hours between 1:00 and 8:00 on a certain day as the first average value, and calculates the average value of the R-R intervals for the four to five consecutive hours between 1:00 and 8:00 on the previous day or the day before that as the second average value. As an example, the predetermined time span is from 2:00 to 7:30, and preferably from 2:30 to 7:00.

[0049] For example, the analysis unit 14 compares the first average value with the second average value and extracts points where the first average value decreases. For example, the analysis unit 14 extracts points where the first average value decreases by a predetermined percentage relative to the second average value. Here, the predetermined percentage may be 5% or more, 8% or more, 10% or more, 14% or more, 16% or more, or 20% or more. The analysis unit 14 outputs the comparison result between the first average value and the second average value to the prediction unit 15.

[0050] When the first average value is lower than the second average value, the prediction unit 15 predicts the parturition time of the test livestock to be 20 to 30 hours after the calculation date of the first average value. As an example, the prediction unit 15 predicts the parturition time of the test livestock to be within 24 hours after the calculation date of the first average value. In other words, the prediction unit 15 predicts the parturition time of the test livestock to be the day after the calculation date of the first average value. The prediction unit 15 outputs information indicating the predicted parturition time of the test livestock to the output device 40. The prediction unit 15 may store the information indicating the predicted parturition time of the test livestock in the storage device 30.

[0051] For example, when the first average value is lower than the second average value by 5% or more, the prediction unit 15 predicts that the delivery time of the test livestock will be within 20 to 30 hours from the calculation date of the first average value. For example, when the first average value is lower than the second average value by 5% or more, 8% or more, 10% or more, 14% or more, 16% or more, or 20% or more, the prediction unit 15 predicts that the delivery time of the test livestock will be within 20 to 30 hours from the calculation date of the first average value.

[0052] For example, when the first average value from 2:30 to 7:00 is lower by 10% or more compared to the second average value from 2:30 to 7:00 on the previous day, the prediction unit 15 predicts that the delivery time will be within 24 hours. Also, for example, when the first average value from 2:30 to 7:00 is lower by 8% or more compared to the second average value from 2:30 to 7:00 on the day before that, the prediction unit 15 predicts that the delivery time will be within 24 hours. Note that if the second average value is obtained from measurements taken on the day before that, and the first average value is lower than the second average value for two consecutive days on the day before that and the day before that, and the first average value is lower by 8% or less compared to the second average value on the day before that, the prediction unit 15 may predict that the delivery time will be within 24 hours.

[0053] Furthermore, as an example, when the first average value from 14:00 to 16:00 is lower by 14% or more compared to the second average value from 14:00 to 16:00 on the day before that, the prediction unit 15 predicts that the delivery time will be within 24 hours.

[0054] The prediction unit 15 outputs information indicating the predicted parturition time of the test livestock to the output device 40. The prediction unit 15 may store the information indicating the predicted parturition time of the test livestock in the storage device 30.

[0055] (Flow of modified example of delivery time prediction process) FIG. 4 is a flowchart illustrating another example of the delivery timing prediction process executed by the delivery timing prediction device according to an aspect of the present invention.

[0056] First, the data acquisition unit 12 acquires heart rate information obtained from an electrocardiogram measured by the measurement device 20 (step S21). Next, the data conversion unit 13 acquires the heart rate information and generates RR interval data that represent the time transition of the RR interval, which is the interval between heart rates (R waves) (step S22). Then, the analysis unit 14 compares a first average value of the RR interval data over a predetermined time width with a second average value over a predetermined time width on the previous day or the day before that (step S23). The prediction unit 15 predicts the time of parturition of the subject livestock based on the prediction results of the first average value and the second average value (step S24), and the parturition time prediction process ends.

[0057] [Software implementation example] The functions of the delivery timing prediction device 10 (hereinafter referred to as the "device") can be realized by a program that causes a computer to function as the device, and a program that causes a computer to function as each control block of the device (particularly each part included in the control unit 11).

[0058] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The control device and storage device execute the program, thereby realizing the functions described in each of the above embodiments.

[0059] The program may be non-transitory and may be recorded on one or more computer-readable recording media. The recording media may or may not be included in the device. In the latter case, the program may be supplied to the device via any wired or wireless transmission medium.

[0060] Furthermore, some or all of the functions of the control blocks can be realized by logic circuits. For example, an integrated circuit in which a logic circuit that functions as each of the control blocks is formed is also included in the scope of the present invention. In addition, the functions of the control blocks can also be realized by, for example, a quantum computer.

[0061] Furthermore, each process described in each of the above embodiments may be executed by AI (Artificial Intelligence). In this case, the AI ​​may run on the control device or on another device (for example, an edge computer or a cloud server).

[0062] The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention. [Example]

[0063] A trend analysis was performed using RR interval data obtained by measuring the heart rates of livestock. Holter electrocardiogram monitors were attached to the bodies of seven dairy cows starting one day or two days before heart rate measurements began, and heart rate measurements began seven days before the expected delivery date of 280 days after conception, until the day of delivery. As a general rule, feeding was carried out between 9:30 and 10:00 and 15:30 and 16:00 each day. Before the morning feeding, the electrocardiogram monitors were reattached and batteries were replaced as necessary, and recording resumed at 10:00. Electrocardiogram data was collected until delivery.

[0064] The RR intervals obtained from the data acquired by the electrocardiograph were calculated as averages every 30 minutes, counting backward from the time of delivery. Time series analysis was performed using these average values ​​every 30 minutes, and average values ​​by time period were calculated. Time series analysis was performed on six dairy cows with few missing values, using the calculation software R. Hourly analysis was performed on seven dairy cows, using Microsoft Excel. The times shown in the examples include an error of less than ±15 minutes. For example, when calculating the average value from 2:30 to 7:00, it also includes times such as 2:35 to 7:05.

[0065] The results of the time series analysis are shown in Figures 5 and 6. Figures 5 and 6 are diagrams showing the results of the trend analysis of the example. Figures 5 and 6 show graphs of the analysis results for each dairy cow, and the graphs show, from top to bottom, the RR interval data, the diurnal fluctuation component, the trend component, and the residual component. In Figures 5 and 6, as indicated by the arrows in the graphs of the trend component, an inflection point or a transient peak value was observed in the trend component, and parturition began 36 to 72 hours after that.

[0066] Figures 7 to 10 show the results of extracting inflection points of the trend component based on the difference between the trend component and its moving average. Figures 7 to 10 are diagrams showing the results of extracting inflection points in the example. Figures 7 to 10 show graphs of the analysis results for each dairy cow, with the upper graph showing the trend component of the RR interval data and its moving average, and the lower graph showing the difference between the trend component and the moving average. Figures 7 and 8 show the results using the moving average calculated by DPO, and the points indicated by the arrows, where the difference is the minimum value exceeding 0, are the inflection points. Figures 9 and 10 show the results using the moving average calculated by MAD, and the points marked with circles, where the difference is the minimum value exceeding 0, are the inflection points. As shown in Figures 7 to 10, inflection points of the trend component were extracted based on the difference between the trend component and the moving average, and parturition began 36 to 72 hours after that.

[0067] The results of the analysis by time period are shown in Figures 11 and 12. Figures 11 and 12 are diagrams showing the results of predicting the timing of delivery using the analysis by time period in the embodiment. As shown in Figures 11 and 12, the RR interval within 24 hours tends to decrease, but in order to examine the trend in more detail, further analysis was performed by narrowing down to specific time periods. The average value of the RR interval from around 2:30 to around 7:00 is shown in Figure 13, and the average value of the RR interval from around 14:00 to around 16:00 is shown in Figure 14.

[0068] As shown in Figures 13 and 14, when the average RR interval from around 2:30 to around 7:00 decreased by 10% or more compared to the previous day, delivery occurred within 24 hours. Also, when the average RR interval from around 2:30 to around 7:00 decreased for two consecutive days and by 8% or more compared to the day before last, delivery occurred within 24 hours. Furthermore, as shown in Figure 14, when the average RR interval from around 2:00 to around 4:00 p.m. decreased by 14% or more compared to the day before last, delivery occurred within 24 hours. [Explanation of symbols]

[0069] 10. Delivery timing prediction device 14 Analysis Department 15 Prediction Department

Claims

1. an analysis step of comparing a first average value of heart rate information obtained from an electrocardiogram measured in a test livestock over a predetermined time period with a second average value of the heart rate information over the predetermined time period on at least one of the previous day and the day before; a prediction step of predicting the time of delivery of the test livestock based on the results of the comparison in the analysis step; A method for predicting the time of calving in livestock.

2. The method for predicting the time of livestock birth as described in claim 1, wherein the specified time range is either a consecutive 4 to 5 hours between 1:00 and 8:00, or a consecutive 1 to 3 hours between 1:00 and 17:

00.

3. A method for predicting the time of birth of livestock as described in claim 1 or 2, wherein in the prediction step, when the first average value is lower than the second average value, the time of birth of the test livestock is predicted to be within 20 to 30 hours from the date of calculation of the first average value.

4. 3. A method for predicting the time of birth of livestock as described in claim 1 or 2, wherein, in the prediction step, when the first average value is lower than the second average value by 5% or more, the time of birth of the test livestock is predicted to be within 20 to 30 hours from the date of calculation of the first average value.

5. an analysis unit that compares a first average value of heart rate information obtained from an electrocardiogram measured in a test livestock over a predetermined time period with a second average value of the heart rate information over the predetermined time period on at least one of the previous day and the day before that; a prediction unit that predicts the delivery time of the test livestock based on the results of the comparison made by the analysis unit; A livestock birth timing prediction device equipped with the above.

Images