WO2019198691A1 - Information processing device and wearable terminal - Google Patents

Abstract

Provided are information processing devices (500, 300) provided with: a plurality of electrodes (401, 402, 403); and processors (510, 310) for outputting an error when a prescribed condition is met on the basis of the degree of potential difference fluctuation in a first period and the degree of potential difference fluctuation in a second period that includes a period before the first period, the degrees being acquired through the plurality of electrodes (401, 402, 403).

Description

Information processing apparatus and wearable terminal

The following disclosure relates to a technique for acquiring the mental state or physical state of an animal.

Conventionally, techniques for acquiring the mental or physical state of an animal are known. For example, JP 2010-155166 A (Patent Document 1) discloses a pulse wave diagnostic device and a pulse wave diagnostic device control method. According to Patent Document 1, the pulse wave diagnostic device and the pulse wave diagnostic device control method detect a pulse wave using a photoelectric sensor, and calculate a fluctuation of the pulse wave from the detected pulse wave. Specifically, the pulse wave diagnostic device control method according to the present invention includes a photoelectric pulse wave detector that receives transmitted light transmitted through an artery or scattered light scattered by an artery and detects a pulse wave, and the photoelectric pulse The pulse wave amplitude for each beat of the pulse wave detected by the wave detection unit is calculated, and the point of the pulse wave amplitude on the orthogonal coordinate plane formed by the two pulse wave amplitudes calculated successively is calculated. And a pulse wave amplitude Poincare calculation unit that calculates Poincare coordinates for each beat.

JP 2010-155166 A

An object of the present disclosure is to provide an information processing apparatus, a state acquisition program, a server, and an information processing apparatus that can accurately grasp the mental state or physical state of an animal more accurately than in the past or more efficiently than in the past. It is to provide an information processing method.

According to an aspect of the present invention, a second electrode including a plurality of electrodes, a dispersion or standard deviation of the potential difference in the first period, which is obtained via the plurality of electrodes, and a second period including the period before the first period. There is provided an information processing apparatus including a processor having a first determination unit that determines whether a predetermined condition is satisfied based on a variance or standard deviation of a potential difference of a period.

As described above, according to the present disclosure, an information processing apparatus capable of grasping an animal's mental state or physical state more accurately than before or grasping more efficiently than before, and state acquisition A program, a server, and an information processing method are provided.

It is a figure showing the whole information processing system 1 composition concerning a 1st embodiment. It is a figure which shows the function structure of the information processing system 1 concerning 1st Embodiment. It is a flowchart which shows the process sequence for calculating the 1st autonomic nerve balance of the information processing system 1 concerning 1st Embodiment. It is an example of the electrocardiogram data and pulsation interval according to the first embodiment. It is a figure which shows the corresponding | compatible relationship table of pulsation interval RR (n) concerning the 1st Embodiment, and the following pulsation interval RR (n + 1). Correspondence relationship table 321A between pulsation interval RR (n) and the next pulsation interval RR (n + 1) according to the first embodiment from the Y = X direction and the axis in the direction perpendicular thereto. It is an image figure which shows conversion. The standard deviation about the Y = X axis and the standard deviation about the axis perpendicular to Y = X as the first autonomic nerve balance for each mental state or physical state of the dog according to the first embodiment It is a table | surface which shows a standard. It is a Poincare plot figure in the excitement state of the dog concerning a 1st embodiment. It is a Poincare plot figure in the state where breathing is stable in the normal state of the dog concerning a 1st embodiment. It is a Poincare plot figure in the normal state of the dog concerning 1st Embodiment. It is a Poincare plot figure in the resting state of the dog concerning 1st Embodiment. It is a flowchart which shows the process sequence for calculating the 2nd autonomic nerve balance of the information processing system 1 concerning 1st Embodiment. The standard deviation about the Y = X axis, the standard deviation about the axis perpendicular to Y = X, and the standard deviation as the second autonomic balance for each mental or physical state of the dog according to the first embodiment It is a table | surface which shows the standard of the product of and the ratio of standard deviation. It is a flowchart which shows the 1st process sequence for calculating the respiration rate of the information processing system 1 concerning 1st Embodiment. It is an example of the relationship between the pulsation detection timing concerning 1st Embodiment, and a pulsation interval. It is an example of the power spectrum distribution concerning 1st Embodiment. It is an example of RRI fluctuation and power spectrum distribution after spline interpolation when the dog according to the first embodiment is at rest. It is an example of RRI fluctuation and power spectrum distribution after spline interpolation during dog excitement according to the first embodiment. It is an example of the effect of the acquisition method of the respiration rate by a 1st embodiment. It is a flowchart which shows the 2nd process sequence of the respiration rate of the information processing system 1 concerning 1st Embodiment. It is an image figure which shows the voltage value of the electrocardiogram input concerning 1st Embodiment. It is an image figure which shows the display screen of the diagnostic graph which shows the normal state concerning 1st Embodiment. It is an image figure which shows the display screen of the diagnostic graph which shows the abnormal state concerning 1st Embodiment. It is an image figure which shows an example of the display screen of the diagnostic terminal 300 concerning 1st Embodiment. It is a flowchart which shows the process sequence of the determination process which determines whether the obtained electrocardiogram data concerning 1st Embodiment are data sufficient to detect an R wave. It is a flowchart which shows the process sequence of the flat determination concerning 1st Embodiment. It is an image figure which shows the diagnostic graph concerning 3rd Embodiment. It is an image figure which shows an example of the 1st display screen of the diagnostic terminal 300 concerning 3rd Embodiment. It is an image figure which shows an example of the 2nd display screen of the diagnostic terminal 300 concerning 3rd Embodiment. It is an image figure which shows an example of transition of the display screen of the diagnostic terminal 300 concerning 3rd Embodiment. It is an image figure which shows the 1st diagnostic graph concerning 4th Embodiment. It is an image figure which shows the 2nd diagnostic graph concerning 4th Embodiment. It is an image figure which shows the 3rd diagnostic graph concerning 4th Embodiment. It is a figure which shows the function structure of the 1st information processing system 1 concerning 6th Embodiment. It is a figure which shows the function structure of the 2nd information processing system 1 concerning 6th Embodiment. It is a figure which shows the function structure of the 3rd information processing system 1 concerning 6th Embodiment. It is a figure which shows the function structure of the 4th information processing system 1 concerning 6th Embodiment. It is an image figure which shows an example of the display screen of the diagnostic terminal 300 concerning 7th Embodiment. R relating to the determination according to the eighth embodiment is a flowchart showing a processing procedure for determining whether or not the amplitude is too large. It is a flowchart which shows the flat determination regarding the determination concerning 8th Embodiment, and the process sequence which judges whether the amplitude of R wave is too large. It is a flowchart which shows the process sequence of the 1st determination process which determines whether the obtained electrocardiogram data concerning 9th Embodiment are data sufficient to detect an R wave. It is an example of the electrocardiogram data concerning 9th Embodiment. It is a flowchart which shows the process sequence of the 2nd determination process which determines whether the obtained electrocardiogram data concerning 9th Embodiment are data sufficient to detect an R wave. It is a flowchart which shows the process sequence of the 3rd determination process which determines whether the obtained electrocardiogram data concerning 9th Embodiment are data sufficient to detect an R wave. It is a figure which shows the function structure of the information processing system 1 concerning 10th Embodiment. It is a 1st image figure which shows the wearable terminal as the signal processing apparatus 500 concerning 10th Embodiment. It is a 2nd image figure which shows the wearable terminal as the signal processing apparatus 500 concerning 10th Embodiment. It is a flowchart which shows the process sequence of the determination process which determines whether the obtained electrocardiogram data concerning 11th Embodiment are data sufficient to detect an R wave.

Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the following description, the same parts are denoted by the same reference numerals. Their names and functions are also the same. Therefore, detailed description thereof will not be repeated.
<First Embodiment>
<Overall configuration of information processing system>

First, the overall configuration of the information processing system 1 according to the present embodiment will be described with reference to FIG. FIG. 1 is a diagram showing an overall configuration of an information processing system 1 according to the present embodiment. In addition, below, the case where the state of the dog which has a respiratory arrhythmia is judged on behalf of an animal is demonstrated.

An information processing system 1 according to the present embodiment mainly includes electrodes 401, 402, and 403 for acquiring electrocardiograms attached to a chest of a dog, a signal processing device 500 for processing an electrocardiogram signal, and signal processing. Diagnostic terminal 300 that can communicate with apparatus 500 is included.

The electrodes 401, 402, and 403 for acquiring electrocardiograms are preferably attached to the chest and the like so as to sandwich the heart part. For example, the hair balls such as the paws of both front legs (or front legs and rear legs) are grown. There may be no place. In addition, it is desirable that the hair is in a state of being trimmed, or has an electrode with a gel attached thereto, or a protrusion-like structure that contacts the skin even if hair is present. Or the form which induces an electrocardiogram through a capacitive material without contact in the state with hair is desirable. Thereby, even an animal whose epidermis such as a dog is covered with hair can obtain an electrocardiogram. In this embodiment, three electrodes 401, 402, and 403 are used. However, the number of electrodes may be two or more, and more electrodes may be used.
<Functional configuration and processing procedure of information processing system>

Next, the functional configuration and processing procedure of the information processing system 1 according to the present embodiment will be described with reference to FIGS. FIG. 2 is a diagram illustrating a functional configuration of the information processing system 1 according to the present embodiment. FIG. 3 is a flowchart showing a processing procedure of the information processing system 1 according to the present embodiment.

First, the configuration of the signal processing device 500 of the information processing system 1 will be described. The signal processing device 500 includes an electrocardiogram preprocessing unit 511, a pulsation interval calculation unit 512, and a transmission unit 560.

The electrocardiogram preprocessing unit 511 includes a filter and an amplifier. The electrocardiogram pre-processing unit 511 converts the electrocardiogram signal sent from the electrodes 401, 402, and 403 into pulsation data, and delivers it to the pulsation interval calculation unit 512.

More specifically, the electrocardiogram preprocessing unit 511 includes a filter device such as a high-pass filter and a low-pass filter, an amplification device including an operational amplifier, an A / D conversion device that converts an electrocardiogram analog signal into a digital signal, and the like. Is included. The filter device, the amplification device, and the like may be implemented by software. In addition, in the A / D converter, it is desirable to perform sampling with a period and accuracy that can determine the difference in fluctuation amount of the pulsation interval. That is, it is desirable to acquire an electrocardiographic signal at a frequency of at least 25 Hz. For example, in the present embodiment, sampling of an electrocardiogram signal at 100 Hz is performed. By increasing the sampling frequency, it is possible to accurately grasp the fluctuation amount of the beat interval.

The beat interval calculation unit 512 is realized by, for example, a CPU (Central Processing Unit) 510 executing a memory program. The pulsation interval calculation unit 512 sequentially calculates pulsation intervals based on the pulsation data. More specifically, the pulsation interval calculation unit 512 detects an electrocardiographic peak signal (R wave) by a method such as threshold detection, and calculates the interval (time) of each electrocardiographic peak. In addition to the above, the pulsation interval may be calculated by derivation of a period using an autocorrelation function or a method using a rectangular wave correlation trigger.

In the present embodiment, as shown in FIG. 4, the pulsation interval calculation unit 512 continuously calculates the pulsation interval for the electrocardiogram signals that are continuously input. The pulsation interval calculation unit 512 transmits the calculated pulsation interval and pulsation data itself to the diagnosis terminal 300 via the transmission unit 560. The transmission unit 560 is realized by a communication interface including an antenna, a connector, and the like, for example.

Next, the configuration of the diagnostic terminal 300 will be described. The diagnostic terminal 300 includes a reception unit 361, a beat interval storage unit 321, a statistical processing unit 311, a graph creation unit 312, a result output unit 313, a display 330, a data storage unit 322, and a transmission unit 362. .

First, the reception unit 361 and the transmission unit 362 are realized by a communication interface 360 including an antenna, a connector, and the like, for example. The receiving unit 361 receives data indicating the beat interval from the signal processing device 500 (step S102).

The pulsation interval storage unit 321 includes various types of memory 320 and stores data received from the signal processing device 500. In the present embodiment, CPU 310 sequentially accumulates beat intervals received via communication interface 360 as a beat interval table in memory 320 (step S104). However, these data may be stored in the memory 320 of the diagnostic terminal 300 or may be stored in another device accessible from the diagnostic terminal 300.

The statistical processing unit 311, the graph creation unit 312, and the result output unit 313 are realized by the CPU 310 executing a program in the memory 320, for example. The statistical processing unit 311 reads out the beat interval data from the beat interval storage unit 321 in a unit of time necessary for determining the state, for example, 1 minute, 10 minutes, 1 hour, etc. As shown in FIG. 5, a correspondence table 321A between the pulsation interval RR (n) and the next pulsation interval RR (n + 1) is created (step S106). For example, the beat interval is calculated in units of msec (millisec) as shown in the figure.

As shown in FIG. 6, the statistical processing unit 311 determines the Y = X direction and the direction perpendicular thereto from the correspondence table between the pulsation interval RR (n) and the next pulsation interval RR (n + 1). Is converted into an axis (step S108).

The statistical processing unit 311 calculates a standard deviation regarding a numerical sequence constituting each axis after the conversion of the axis as a numerical value indicating the autonomic nerve balance (step S110). Note that the statistical processing unit 311 may calculate only the standard deviation about the Y = X axis, may calculate only the standard deviation about the axis perpendicular to Y = X, or may calculate both. . FIG. 7 is a table showing a standard deviation of the standard deviation on the Y = X axis and the standard deviation on the axis perpendicular to Y = X for each mental state or physical state of the dog.

Note that the statistical processing unit 311 may specify an axis that maximizes the variance by a method such as principal component analysis, and may calculate a standard deviation regarding the axis and an axis perpendicular to the axis. Furthermore, the statistical processing unit 311 may calculate a standard deviation regarding the X axis and the Y axis without performing axis conversion. When the direction of large variance is the X-axis direction and the Y-axis direction, the standard deviation of the X-axis and the Y-axis is calculated without performing axis conversion, thereby evaluating the variation state of the beat interval plotted by Poincare plot. it can. In this case, since it is not necessary to perform axis conversion, the amount of calculation can be reduced.

The result output unit 313 displays the standard deviation or outputs a voice message on an output device such as the display 330 or the speaker, for example, outside the diagnostic terminal 300 (step S114). More specifically, the result output unit 313 may output only the standard deviation regarding the Y = X axis, may output only the standard deviation regarding the axis perpendicular to Y = X, or may output both. Alternatively, only the larger one may be output, or only the smaller one may be output.

By calculating the standard deviation, it is possible to evaluate the variation state of the beat interval obtained by Poincare plot with the beat interval R−R (n) and the next beat interval R−R (n + 1) as axes. Here, the degree of variation in the pulsation interval is regarded as the degree of autonomic nerve balance. As will be described later, the numerical value indicating the autonomic balance is not limited to the standard deviation after the axis conversion.

In the present embodiment, the CPU 310 performs the calculation shown in FIG. 3 for a predetermined period, for example, every few minutes, and accumulates the calculation result in the database of the memory 320 for creating a diagnostic graph to be described later.

In addition, although mentioned later in detail, the information processing system 1 concerning this Embodiment may be the form containing the server 100 with which the diagnostic terminal 300 can communicate as shown in FIG. In that case, the CPU 310 as the result output unit 313 accumulates the standard deviation and the relation table in the data storage unit 322 or uses the transmission unit 362 to transmit to the server 100 via the Internet or the like. As a result, the current output result can be used for grasping the short-term or long-term stress state of the observation target.

In the present embodiment, separately from step S108, the graph creation unit 312 determines from the correspondence table in FIG. 5 the pulsation interval RR (n) in the range used for calculating the standard deviation and the next beat. Data with the movement interval RR (n + 1) is acquired, and Poincare plot diagrams as shown in FIGS. 8 to 11 are created.

Then, the result output unit 313 displays the generated Poincare plot on an output device such as a display of the diagnostic terminal 300 or an external display. Note that the graph creation unit 312 may create and output a Poincare plot diagram after axis conversion using the result of step S108.

Here, the Poincare plot will be explained. FIG. 8 is a Poincare plot in the excited state of the dog according to the present embodiment. FIG. 9 is a Poincare plot in a state where the breathing is stable in the normal state of the dog according to the present embodiment. FIG. 10 is a Poincare plot in the normal state of the dog according to the present embodiment. FIG. 11 is a Poincare plot in the resting state of the dog according to the present embodiment.

First, in the case of an animal having a respiratory arrhythmia such as a dog, in the excited state as shown in FIG. 8, the heart rate rises (beat interval is shortened), and the fluctuation of the beat interval becomes small. It will be in the state where these points gather in a certain place.

In the normal state where the breathing is stable as shown in FIG. 9, the heart rate is not as small as in the resting state (the spread of the plot points is not as great as in the resting state), but at the center of the distribution of the plot points. There are areas with few plots (hole blanks). The reason for this shape is thought to be that the fluctuation of the pulsation changes periodically (respiratory arrhythmia) because the heartbeat of the dog is greatly affected by respiration. Therefore, although it is not a relaxed and gentle pulsation, it is considered that there is a blank space because breathing is performed stably.

In the normal state as shown in FIG. 10, the pulsation fluctuates and the variation becomes large (the plot points are widened), but the plot points are scattered.

In the resting state of FIG. 11, since the dog is relaxed, the interval between pulsations is increased, and the influence of the respiratory arrhythmia is greatly increased. Therefore, the spread of the plot points is increased, and the circular or rectangular shape is increased. It becomes a shape close to or a shape close to a triangle. In any of the shapes, in a resting state, a blank portion can be seen at the center of the distribution of plot points of the Poincare plot.

As described above, in the present embodiment, the size and shape of the distribution of the plot points of the Poincare plot is indirectly estimated based on the calculation result, and whether or not the plot is often observed or reduced in the central portion. As a result, the mental state or physical state of the animal can be predicted. As described above, the statistical processing unit 311 calculates the degree of variation of the Poincare plot, that is, the standard deviation of the pulsation interval, as a numerical value indicating the autonomic nerve balance. Here, the variation degree refers to, for example, an index for quantifying the variation degree, represented by a dispersion value or a standard deviation.
<Another form of numerical values for autonomic balance>

In the above embodiment, the diagnostic terminal 300 outputs the standard deviation along the Y = X axis of the Poincare plot or the standard deviation along the axis perpendicular to Y = X. However, the product of the two standard deviations may be calculated as a numerical value indicating the autonomic balance. Below, with reference to FIG. 12, the process sequence of the information processing system 1 concerning this Embodiment is demonstrated.

FIG. 12 is a flowchart showing a processing procedure of the information processing system 1 according to the present embodiment. Steps S102 to S108 are the same as those in FIG. 3, and therefore description thereof will not be repeated here.

The CPU 310 as the statistical processing unit 311 calculates the standard deviation for each axis after the axis conversion (step S110). Note that the statistical processing unit 311 may specify an axis that maximizes the variance and calculate a standard deviation regarding the axis and an axis perpendicular to the axis.

Then, the statistical processing unit 311 calculates the product of these two standard deviations, the square root of the product, and the like as a numerical value indicating the autonomic balance (step S112).

The result output unit 313 displays the product of the standard deviation, the square root of the product, or the like, or outputs a voice message on an output device such as a display or a speaker, for example, outside the diagnostic terminal 300 (step S114). ). More specifically, the result output unit 313 may output a standard deviation with respect to the Y = X axis, a standard deviation with respect to the Y = −X axis, the product of both, the square root of the product, and the like.

FIG. 13 shows the product or product of the standard deviation for the Y = X axis, the standard deviation for the axis perpendicular to Y = X, and the standard deviation as a numerical value indicating the autonomic nerve balance for each mental state or physical state of the dog. It is a table | surface which shows the standard of the square root of etc. and the ratio of standard deviation.

By calculating the product of the standard deviation, the size of the spread of the beat interval distribution obtained by Poincare plot with the beat interval R−R (n) and the next beat interval R−R (n + 1) as axes, respectively, Variations such as shape, uniform dispersion, and blank at the center can be evaluated. In addition, it is possible to effectively evaluate the variation state when the aspect ratio is the same and only the size is changed, or when the distribution spread area is the same and the variation state of the central portion is different.

Also in this case, the result output unit 313 accumulates the standard deviation, the product of the standard deviation, the square root of the product, the correspondence table, and the like in the data storage unit 322, or uses the transmission unit 362 via the Internet or the like. To the server 100. As a result, the current output result can be used for grasping the short-term or long-term stress state of the observation target.

The statistical processing unit 311 calculates a product of standard deviations of two axes, a square root of the product, etc., but calculates a product of standard deviations of three or more axes or a power root thereof. Good.

The CPU 310 performs the calculation shown in FIG. 12 for a predetermined period, for example, every few minutes, and accumulates the calculation result in the database of the memory 320 for creating a diagnostic graph to be described later.
<Calculation method of respiratory rate>

The CPU 310 of the diagnostic terminal 300 according to the present embodiment may calculate the respiratory rate of the target animal in addition to the information indicating the autonomic nerve balance of the target animal. Referring to FIG. 14, CPU 310 of diagnostic terminal 300 executes the following process, for example, by executing a program in memory 320.

CPU 310 obtains a beat interval as shown in FIG. 4 (step S204). As shown in FIG. 15, the CPU 310 mathematically interpolates (for example, spline interpolation) the relationship between the beat detection time for one minute and the beat interval (step S206). More specifically, the CPU 310 detects an electrocardiographic peak signal (R wave) by a method such as threshold detection, and calculates an interval (time) of each electrocardiographic peak. In addition to the above, the pulsation interval may be calculated by derivation of a period using an autocorrelation function or a method using a rectangular wave correlation trigger.

Then, the CPU 310 performs frequency analysis of the obtained function as shown in FIG. 16 (step S208).

The CPU 310 specifies the maximum peak of the power spectrum in an arbitrary frequency range (for example, between 0.05 and 0.5 Hz) in the power spectrum distribution as shown in FIG. 16 obtained by the frequency analysis (step S210). ). Here, as an example, if the ratio of the maximum peak compared to the second largest peak has a magnitude (for example, three times) equal to or greater than an arbitrary threshold, the CPU 310 determines that the state is “measurable”.

More specifically, for example, the RRI fluctuation after the spline interpolation of a dog in a relaxed state in an indoor quiet room is as shown in FIG. The power spectrum distribution in this case is as shown in FIG. 17B, and the ratio of the maximum peak compared to the second largest peak has a magnitude (for example, three times) greater than an arbitrary threshold value. The CPU 310 determines that the state is “measurable”.

Conversely, for example, the RRI fluctuation after spline interpolation of a dog that is not calm in an outdoor noisy environment is as shown in FIG. The power spectrum distribution in this case is as shown in FIG. 18B, and the ratio of the maximum peak compared to the second largest peak has a magnitude (for example, three times) greater than an arbitrary threshold value. Therefore, the CPU 310 determines that the measurement is impossible.

When the CPU 310 determines that the measurement is impossible, the CPU 310 repeats the processing from step S106 based on the beat interval that the signal processing device 500 has already acquired for another timing.

CPU 310 detects various vital data when it is determined as “measurable state”. For example, the CPU 310 calculates the respiration rate by calculating the reciprocal with the maximum peak in an arbitrary frequency range (for example, a range of 0.05 to 0.5 Hz) in the frequency analysis as the respiration frequency.

The CPU 310 displays the respiration rate per unit time and outputs sound through the display 330, the speaker 370, the communication interface 360 for transmitting data to the outside, and the like. Further, the CPU 310 performs the calculation shown in FIG. 14 every predetermined period, for example, every few minutes, and accumulates the calculation result in the database of the memory 320 for creating a diagnostic graph to be described later.

In the present embodiment, the CPU 310 calculates the respiration rate by calculating the reciprocal of the frequency with the maximum peak frequency in the frequency analysis as the respiration frequency. FIG. 19 shows the results of 60-minute respiration rate measurement. When the state is not discriminated, the measurement result can be output every minute as shown in FIG. 19A, but the measurement result in various states is included and it is difficult to ensure the accuracy. . On the other hand, by not calculating the data of the time determined as “unmeasurable state”, it becomes possible to calculate the respiration rate as shown in FIG. 19B, and obtain only the respiration rate in an appropriate state. be able to.

More specifically, it is important medically to accumulate vital data, but it is necessary to compare and analyze data measured in a certain environment (for example, at rest). In particular, when comparing data over a long period of time, or when the person being measured (for example, a dog) is unable to maintain a certain state of its own, in order to reliably record vital data, It is necessary to determine the state of the measurer. In particular, since the respiration rate fluctuates arbitrarily, it is difficult for the measurement subject to create a state that can be consciously measured. At present, no means has been established for automatically determining whether the measurement is possible.

However, the state of the measurement subject is determined by analyzing the measurement data (for example, an electrocardiogram signal), and vital data (for example, the respiratory rate derived from the electrocardiogram signal) is calculated based on the determination result of the state. , Can be recorded. In particular, as a means for determining the state, it is determined whether or not an appropriate state has been maintained for a certain time (for example, 1 minute) during measurement. The determination criterion of “whether or not an appropriate state has been maintained” is defined from the fluctuation cycle due to respiration using, for example, heart rate variability analysis. An animal such as a dog has a change in heart rate and respiration rate even when no movement is observed, and this discrimination criterion can discriminate an appropriate state with higher accuracy than analysis of movement using an acceleration sensor or the like. Further, by performing both state determination and vital data detection from a single measurement data such as an electrocardiogram signal, the measurement apparatus can be made small and simple. By reducing the size of the apparatus and system, it is possible to reduce the stress and load on the measurer and to perform measurement in a more natural state.

In step S110 of FIG. 14, the CPU 310 searches for the maximum peak of the power spectrum in an arbitrary frequency range (for example, between 0.05 Hz and 0.5 Hz) in the power spectrum distribution obtained by the frequency analysis. When the ratio of the integral value of the power spectrum from the peak to its half-value width is greater than or equal to the set threshold value, it may be determined that the respiratory rate is measurable. More specifically, if it can be determined whether or not the maximum peak in an arbitrary frequency range (for example, between 0.05 and 0.5 Hz) is prominent in the power spectrum distribution as compared with other power spectra. The CPU 310 may determine the “measurable state” by another method.

Alternatively, as shown in FIG. 20, based on the Poincare plot of the beat interval, the CPU 310 determines that the target animal is in a resting state when the standard deviation, the product of the standard deviation, its square root, or the like is larger than a predetermined value. It may be judged (steps S302 to 312). Then, when it is determined as “measurable state”, the CPU 310 may calculate the number of maximum (or minimum) points in the time series change of the pulsation interval as the respiration rate, as shown in FIG. The CPU 310 performs the calculation shown in FIG. 20 for a predetermined period, for example, every few minutes, and accumulates the calculation result in the database of the memory 320 for creating a diagnostic graph to be described later.
<Result output method>

As described above, in the present embodiment, the CPU 310 of the diagnostic terminal 300 displays various graphs on the display 330 based on the signal as shown in FIG. For example, as shown in FIG. 22, the CPU 310 shows, for each individual, a first graph in which the pulsation interval is spline-interpolated, a second graph showing the ECG peak signal itself, and a Poincare plot of the pulsation interval. A third graph of interpolation, a fourth graph obtained by frequency analysis of the first graph, and the like are displayed on the display 330. FIG. 22 shows (a) a first graph in which the beat interval is spline-interpolated, (b) a second graph showing the electrocardiographic peak signal itself, and (c) regarding an individual in a normally relaxed state. FIG. 5 shows a third interpolated graph showing a Poincare plot of pulsation intervals, and (d) a fourth graph obtained by frequency analysis of the first graph. On the other hand, FIG. 23 shows (a) a first graph showing a signal itself when an electrocardiographic peak signal cannot be acquired correctly, (b) a second graph showing a Poincare plot of a beat interval, and (c 3) A third graph in which the pulsation intervals are spline-interpolated, and (d) a fourth graph in which the third graph is frequency-analyzed. In FIG. 23, the second graph showing the electrocardiographic peak signal itself at the lower right is marked as “not adopted” in the time zone when it was not correctly acquired. The “non-adopted” period refers to a period in which it is determined that the R wave cannot be detected correctly or is likely not to be detected correctly. An example of the determination method will be described later. The 2nd graph of this embodiment may show transition of the environmental data of the environment which is measuring the pulsation or pulse of the animal individual for every animal individual or every timing instead of the graph which shows the ECG peak signal itself. good. The environmental data may be, for example, changes in temperature, humidity, noise, and the like.

In the present embodiment, as shown in FIG. 24, the CPU 310 can select a mode in which any kind of graph relating to each of a plurality of individuals is arranged and displayed on the display 330. In particular, in the present embodiment, CPU 310 makes the display mode of the graph related to the measurement determined to be highly likely to be different from the display mode of the graph related to the measurement determined to be normal. For example, the CPU 310 displays the second graph of a plurality of individuals side by side on the display 330 and displays the original first graph together with the second graph for the measurement determined to be abnormal. It is. Here, the second graph and the first graph may be displayed simultaneously for a predetermined period. For example, the first graph may be displayed after a while after the second graph is displayed. If the first graph and the second graph are simultaneously displayed for a predetermined period, the first graph is displayed. Either the second graph or the second graph may not be displayed on the display first.

This makes it easier for a user such as a veterinarian to determine whether or not an abnormal graph should be adopted or taken into consideration.

As shown in FIG. 24, the horizontal axes of the first graph and the second graph both indicate the measurement time. It is preferable that the measurement interval, length, and scale on the horizontal axis of the first graph and the second graph are aligned. Furthermore, the horizontal axis of the first graph and the horizontal axis of the second graph are preferably arranged in parallel to each other. By aligning the horizontal axes of the first graph and the second graph, it is easy to confirm the correspondence between the data included in both graphs when visually comparing the two graphs.

It should be noted that the original first graph together with the second graph is displayed smaller than the graph related to the measurement determined to be normal so that the position where the graph related to the measurement determined to be normal is not changed.

Hereinafter, a process for determining whether or not various types of acquired data are normal in the diagnostic terminal 300 will be described. As an example, FIG. 25 is a flowchart for determining whether or not the obtained electrocardiographic data is sufficient to detect the R wave, that is, whether or not the R wave cannot be detected correctly or is likely not to be detected correctly. is there.

Referring to FIG. 25, the CPU 310 first acquires the electrocardiographic voltage value Et for the latest t seconds (eg, t = 1). If the sampling frequency for voltage acquisition is 100 Hz, Et is composed of 100 numerical values (step S402). CPU110 determines the maximum value Em of Et (step S404).

In the present embodiment, the determination is divided into two stages. The first stage is a stage for determining whether or not the amplitude of the R wave is sufficient, and the second stage is a stage for determining depending on whether or not there is more noise than or equal to the R wave. Hereinafter, the first stage is referred to as flat determination (second determination means, step S410), and the second stage is referred to as multi-noise determination (first determination means).

As shown in FIG. 26, the CPU 310 obtains an average Et_ave of Et as a flat determination (step S412), and obtains a difference from the maximum value Em of Et (step S414). If the difference exceeds a predetermined threshold value Jflat (for example, 30), the CPU 310 sets the flat determination result to FALSE (step S416), and sets the difference to TRUE (step S416). CPU310 determines that this area Et cannot be employ | adopted when it becomes TRUE by flat determination (1st result, step S452). The threshold value Jflat may be changed according to the size of the dog breed or the contact resistance of the skin, or may be changed according to the ambient temperature and humidity.

25, in addition to Et, the CPU 310 also acquires the voltage value Eref for the latest ref seconds (for example, ref = 15) (step S426). The CPU 310 obtains dispersion values Dt and Dref for Et and Eref, respectively (step S434). When Dt exceeds Dref, the CPU 310 determines that this section Et is not adopted because there is too much noise (first result, step S446). Conversely, if Dt is lower than Dref, the CPU 310 determines that Et can be adopted (second result, step S442). The t seconds and ref seconds may be changed according to the size of the dog breed and the contact resistance of the skin, or may be changed depending on the ambient temperature and humidity. Moreover, you may change according to the activeness of the dog under measurement. For example, the activity can be measured by an acceleration sensor or the like.

In the present embodiment, in this multi-noise determination, in order to consider the magnitude of noise, each maximum value is determined depending on whether or not a predetermined threshold EMAX (for example, 150) is exceeded when Et and Eref are acquired. Normalization (step S422, step S424, step S430, step S432). This predetermined threshold EMAX is desirably adjusted according to the resolution of the voltage value to be detected.

In addition, the numerical value indicating the autonomic balance is not limited to the product of the standard deviation or standard deviation of the Poincare plot, but the average of the distances between two consecutive Poincare plots can be used, and other Poincare blot variations The numerical value shown may be used, or another calculation method other than the Poincare plot may be used.

In the above embodiment, the pulsation interval is calculated using the electrodes 401, 402, and 403 for acquiring electrocardiograms. However, the present invention is not limited to such a form. For example, a pulse wave signal may be acquired by a photoelectric pulse wave type pulse wave meter or a pulse oximeter, and a pulsation interval may be calculated from the pulse wave signal. In this case, the pulse wave measurement site is preferably the site where the skin, including the tongue and ears, is exposed. Alternatively, a heart sound signal may be acquired by an electronic stethoscope or the like, and the heart sound signal or the beat interval may be calculated. In these cases, measurement can be performed by a method that does not use an electrode. A pulse wave signal may be acquired using a pulse wave acquisition sensor such as a microwave Doppler sensor, and the pulsation interval may be calculated from the pulse wave signal. For example, a microwave transmission device is installed on the ceiling or the like, and a form of acquiring a pulse wave from an animal such as a dog without contact is conceivable. In this case, non-contact measurement is possible and there is an effect of further reducing the load on the subject.
<Second Embodiment>

The output method of the result is not limited to that of the above embodiment. For example, the CPU 310 of the diagnostic terminal 300 acquires the average Et_ave of Et as the flat determination shown in FIG. 26 (step S412), and obtains the difference from the maximum value Em of Et (step S414). Then, the CPU 310 may not arrange the graph itself on the display 330 when the difference does not exceed the second predetermined threshold value Jflat (for example, 15).

In step S446 in FIG. 25, if Dt exceeds a predetermined value (for example, twice) of Dref, the CPU 310 may not arrange this graph on the display 330 because there is too much noise. Good.

That is, in the present embodiment, the CPU 310 determines that there is an abnormal range in the graph when a part or all of the graph satisfies a predetermined condition by the second determination unit. The graph 330 is displayed on the display 330 with a display different from that of the graph. Then, when a part or all of the graph further satisfies a predetermined condition by the first determination means, the CPU 310 does not display the graph itself but instead displays the next graph on the display 330. To do.

As a result, a graph such as 80% or more that is highly likely to be abnormal is automatically excluded in advance, and a user such as a veterinarian may diagnose a graph that may be abnormal, such as 30% or more It becomes easier to judge whether or not to adopt or consider. It is preferable that the CPU 310 receives a setting such as a numerical value of the possibility itself or other threshold value, which serves as an index for the determination, via an operation unit such as a button or a touch panel.
<Third Embodiment>

The output method of the result is not limited to that of the above embodiment. Also in the present embodiment, CPU 310 changes the display mode of the graph related to the measurement that is determined to be highly likely to be different from the display mode of the graph related to the measurement that is determined to be normal. For example, the CPU 310 causes the display 330 to display the second graphs of a plurality of individuals side by side, and regarding the measurement result determined to be not normal, it is determined to be not normal on the screen as shown in FIG. The original first graph may be superimposed on the second graph and displayed.

This makes it easier for a user such as a veterinarian to determine whether or not an abnormal graph should be adopted or taken into consideration.

In this case, the CPU 310 preferably matches the vertical main range of the first graph and the vertical main range of the second graph to the same extent.

Alternatively, as shown in FIG. 28, the CPU 310 may change the display mode of the graph related to the measurement that is determined to be highly likely to be different from the display mode of the graph related to the measurement that is determined to be normal. That is, the CPU 310 causes the display 330 to display the second graph of a plurality of individuals side by side, and displays a frame around the second graph for the measurement result determined to be not normal. Alternatively, the CPU 310 changes the line color of the second graph, changes the back color, or adds exclamation.

Then, when the graph is selected via an operation unit such as a button or a touch panel, the CPU 310 displays the original graph together with the second graph regarding the measurement that is determined to be abnormal on the screen as shown in FIG. The first graph is also displayed side by side.

More preferably, at this time, as shown in FIG. 30, CPU 310 displays an image or text for accepting an instruction to leave or exclude a graph related to the measurement on the screen. Then, the CPU 310 returns the display mode of the measurement graph to be the same as that of the normal graph according to the “remaining command” input through the operation unit, or “input through the operation unit”. In response to the “exclusion command”, the graph of the target measurement is removed from the screen, and the next graph of another measurement is displayed in front.
<Fourth embodiment>

Alternatively, as shown in FIG. 31, regarding the graph relating to the measurement that is determined to have a high possibility of being abnormal, as shown in FIG. 31, the CPU 310 displays the first graph together with the second graph while displaying the original first graph side by side. A portion of the graph that is determined to be highly likely to be abnormal may be displayed in a display mode different from the other portions. For example, the CPU 310 displays a frame line that surrounds a portion of the first and second graphs that is determined to have a high possibility of being abnormal.

Alternatively, as shown in FIG. 32, the CPU 310 makes the back color of the area of the first and second graphs determined to be highly normal different from the other parts.

Alternatively, when a graph related to a measurement that is determined to have a high possibility of being abnormal in FIG. 27 is selected, as illustrated in FIG. 33, the CPU 310 displays three or more values related to the measurement determined to be abnormal on the screen. You may transition to a screen that displays a graph. Also in this case, the CPU 310 may display a portion of the first and second graphs that is determined to be highly likely to be abnormal in a display mode different from other portions.
<Fifth embodiment>

The output method of the result is not limited to the method of displaying the graphs of a plurality of different individuals side by side as in the above embodiment. For example, as shown in FIG. 24, the CPU 310 of the diagnostic terminal 300 may display a graph regarding each of a plurality of different timings related to a specified individual on the display 330.
<Sixth Embodiment>

In the information processing system 1 according to the above-described embodiment, the signal processing device 500 acquires the beat interval based on the electrocardiogram signals from the electrodes 401, 402, and 403, and the diagnosis terminal 300 determines the state of the animal from the beat interval. The information for judging the above or the information on the judgment result of the animal state is calculated and output. However, all or some of the roles of the one device may be played by another device or may be shared by a plurality of devices. Conversely, one device may play the role of all or part of the plurality of devices, or another device may play the role.

For example, as shown in FIG. 34, the diagnostic terminal 300 may be equipped with all or part of the functions of the signal processing device 500. In this case, the diagnostic terminal 300 acquires the electrocardiogram signals from the electrodes 401, 402, and 403 from the simple signal processing device 501 by wireless communication. An electrocardiogram signal from the electrode is converted into a digital signal by a simple electrocardiogram preprocessing unit 570 including a minimum filter device, amplification device, and A / D conversion device, and transmitted from the transmission unit 560. The diagnosis terminal 300 calculates information for determining the interval between pulsations and the state of the animal or information on the determination result of the state of the animal from the electrocardiogram signal. Then, the diagnostic terminal 300 outputs the final result information to a display or a speaker.

Alternatively, as shown in FIG. 35, the signal processing device 500 may be equipped with all or part of the functions of the diagnostic terminal 300. In this case, based on the electrocardiogram signals from the electrodes 401, 402, and 403, the signal processing device 500 calculates information for determining the pulsation interval and the state of the animal or information on the determination result of the state of the animal. Then, the signal processing device 500 outputs the final result information to a display or a speaker.

Alternatively, as shown in FIG. 36, the server 100 may play the role of the diagnostic terminal 300. In this case, the server 100 is equipped with the function of the diagnostic terminal 300 of the above embodiment. For example, a communication terminal as the diagnostic terminal 300 transmits necessary information such as a beat interval from the signal processing device 500 to the server 100 via a router, a carrier network, the Internet, or the like. The server 100 calculates information for determining the animal state or information indicating the determination result of the animal state, and transmits the information to the diagnostic terminal 300. It is conceivable that the diagnostic terminal 300 outputs the final result information to a display or a speaker.

In this case, as a matter of course, the reception unit 161 and the transmission unit 162 of the server 100 are realized by the communication interface 160 of the server 100. The beat interval storage unit 121 and the data storage unit 122 are realized by the memory 120 of the server 100 or another device accessible from the server 100. The statistical processing unit 111, the graph creation unit 112, and the result output unit 113 are realized by the CPU 110 executing the program in the memory 120.

Alternatively, as shown in FIG. 37, the signal processing device 500 transmits necessary information such as a beat interval to the server 100 via a router, a carrier network, the Internet, or the like. The server 100 calculates information for determining the state of the animal or information on the determination result of the state of the animal, and transmits the information to a communication terminal as the diagnostic terminal 300 via the Internet, a carrier network, a router, or the like. The diagnostic terminal 300 outputs information on the final result to a display or a speaker. In this case, the signal processing device 500 and the diagnostic terminal 300 may not be connected by a wireless LAN or a wired LAN.

In this case, as a matter of course, the reception unit 161 and the transmission unit 162 of the server 100 are realized by the communication interface 160 of the server 100. The beat interval storage unit 121 and the data storage unit 122 are realized by the memory 120 of the server 100 or another device accessible from the server 100. The statistical processing unit 111, the graph creation unit 112, and the result output unit 113 are realized by the CPU 110 executing the program in the memory 120.

In the description of the above embodiment, the processing for performing “Poincare plot” and the processing for performing “axis conversion after Poincare plot processing” are described. The CPU of the apparatus 500 should not be limited to actually printing or displaying a Poincare plot image on a paper medium or a display. The process is a concept including, for example, a process in which the CPU stores or expands data that substantially indicates a Poincare plot in a memory.
<Seventh embodiment>

In the information processing system 1 according to the above embodiment, the display mode of the graph related to the measurement that is determined to be highly normal is different from the display mode of the graph related to the measurement that is determined to be normal. . However, it is not limited to such a form.

For example, at the timing when the CPU 310 of the diagnostic terminal 300 acquires data from the signal processing device 500, a determination (flat determination) is made according to whether or not the amplitude of the R wave is sufficient, or it is equal to or higher than the R wave. It may be determined (multiple noise determination) according to whether there is a lot of noise.

When the CPU 310 determines that it is normal, it does not display an error on the display 330 as shown in FIG. When the CPU 310 determines that the flat determination is not normal, the CPU 310 may output a message that “the electrodes are disconnected” to the display 330 as illustrated in FIG. When the CPU 310 determines that it is not normal in the multi-noise determination, as shown in (c) of FIG. May be output ".
<Eighth Embodiment>

In the information processing system 1 according to the above-described embodiment, in order to determine whether or not the various types of acquired data are normal, determination is made according to whether or not the amplitude of the R wave is sufficient (flat determination). Or making a determination (multiple noise determination) depending on whether there is more noise than the R wave.

However, instead of the flat determination, it may be determined whether or not the acquired various data are normal depending on whether or not the amplitude of the R wave is too large. For example, as shown in FIG. 39, the CPU 310 obtains an average Et_ave of Et (step S412), and obtains a difference from the maximum value Em of Et (step S414B). The CPU 310 determines whether or not this difference exceeds a predetermined threshold (for example, 200) (step S414B). If this difference exceeds a predetermined threshold, the determination result is TRUE (step S418B), and if not, FALSE is set (step S416B). If the determination is TRUE, the CPU 310 determines that this section Et cannot be adopted and causes the display 330 or the speaker to output that effect (step S418B).

Or you may combine this determination and said flat determination. That is, as shown in FIG. 40, the CPU 310 obtains an average Et_ave of Et as a flat determination (step S412), and obtains a difference from the maximum value Em of Et (step S414). If the difference does not exceed a predetermined threshold value Jflat (for example, 30), CPU 310 sets TRUE (step S418). If the CPU 310 determines that the flat determination is TRUE, the CPU 310 causes the display 330 or the speaker to output the fact that the section Et cannot be adopted (step S418). On the other hand, when the flat determination is FALSE, it is determined whether or not the difference between the maximum value Em of Et exceeds a predetermined threshold (for example, 200) (step S414B). If this difference exceeds a predetermined threshold, the determination result is TRUE (step S418B), and if not, FALSE is set (step S416B). If the determination is TRUE, the CPU 310 determines that this section Et cannot be adopted and causes the display 330 or the speaker to output that effect (step S418B).
<Ninth embodiment>

There are various types of processing related to multi-noise determination. For example, as shown in FIG. 41, CPU 310 determines whether or not Dt exceeds 150% of Dref (step S436B). When Dt exceeds 150% of Dref, CPU 110 causes the display 330 and the speaker to output the fact that the section Et is not adopted because there is too much noise (step S446B). Conversely, if Dt is less than 150% of Dref, CPU 310 can adopt Et (step S442).

This makes it possible to output an error when the potential in the frame as shown in FIG. 42 is obtained. In FIG. 42, an error flag “1” is added during a period when an error is determined in the multiple noise determination, and a normal flag “0” is added during a period when the error is not determined in the multiple noise determination.

Alternatively, as shown in FIG. 43, the CPU 310 may determine whether Dt is 70% or less of Dref (step S436C). When Dt is 70% or less of Dref, CPU 110 causes the display 330 and the speaker to output the fact that the section Et is not adopted because the voltage value is too low (step S446B). Conversely, when Dt exceeds 70% of Dref, the CPU 310 can adopt Et (step S442).

Alternatively, as shown in FIG. 44, these determinations may be combined. That is, CPU 310 determines whether or not Dt exceeds 150% of Dref (step S436B). When Dt exceeds 150% of Dref, CPU 110 causes the display 330 and the speaker to output the fact that the section Et is not adopted because there is too much noise (step S446B). Conversely, if Dt is less than 150% of Dref, it is determined whether Dt is 70% or less of Dref (step S436C). When Dt is 70% or less of Dref, CPU 110 causes the display 330 and the speaker to output the fact that the section Et is not adopted because the voltage value is too low (step S446B). Conversely, when Dt exceeds 70% of Dref, the CPU 310 can adopt Et (step S442).
<Tenth Embodiment>

Also regarding the seventh to ninth embodiments, all or a part of the roles of the one device may be played by another device or may be shared by a plurality of devices. Conversely, one device may play the role of all or part of the plurality of devices, or another device may play the role.

Specifically, as shown in FIG. 45, the CPU 510 of the signal processing device 500 may execute the above various determinations. That is, the CPU 510 executes the processing of FIG. 25, FIG. 26, FIG. 39 to FIG. 44, and outputs the display as shown in FIG. 38 to the display 530 of the signal processing device 500 and the display 330 of the diagnostic terminal 300. Also good. Alternatively, when the CPU 510 determines that an error has occurred, the light 531 of the signal processing device 500 and the light 331 of the diagnostic terminal 300 shine red, or when it is determined to be normal, the light 531 of the signal processing device 500 and the diagnostic terminal 300 The light 331 may be lit in green. Alternatively, the CPU 510 may cause the speaker 532 of the signal processing device 500 or the speaker 332 of the diagnostic terminal 300 to output the determination result. For example, as shown in FIG. 1, the signal processing device 500 is a wearable terminal for wearing on an animal such as a dog, and determines whether data can be normally acquired in the wearable terminal. As shown in FIG. 47, the display 530, the light 531 and the speaker 532 of the wearable terminal may output error information and the like.

More specifically, as shown in FIGS. 46 and 47, the signal processing device 500 is provided in an appliance (for example, a wear, a harness, etc.) for wearing on an animal such as a dog. Note that the signal processing device 500 may be configured to be detachable with respect to the appliance by hooks, buttons, cables, or the like. When the electrodes 401, 402, and 403 are fixed to the appliance and the signal processing device 500 is configured to be detachable, the signal processing device 500 is electrically connected to the electrodes 401, 402, and 403 via hooks, buttons, and cables. Connect. The signal processing device 500 is electrically insulated from the electrodes 401, 402, and 403 by detaching from the equipment connected by hooks, buttons, and cables. By providing such a configuration, it is possible to remove the signal processing device 500 and wash the brace when washing the brace. In yet another method, the electrodes 401, 402, 403 can also be configured to be removable from the appliance. In this case, the electrodes 401, 402, and 403 are attached to the appliance by means of hook-and-loop fasteners, buttons, hooks, and the like, and the signal processing device 500 is also connected to the appliance so that it can be configured as a wearable terminal as a whole. It becomes.
<Eleventh embodiment>

In the above embodiment, the “electrocardiogram data Et” of “most recent t seconds” is referred to in the flat determination and the noise determination (after S422 in FIG. 25), but this “most recent t seconds” is not the same. May be. FIG. 48 shows an example in which the reference periods are different in flat determination and noise determination.

48 is an example in which the periods used for evaluation in S410 and S436 in FIG. 25 are different. First, for flat determination, electrocardiogram data Es (third period) in the latest s seconds are acquired (S402B), and the maximum value Em in Es is acquired (S404B). In the flat determination process shown in FIG. 26, Es is used instead of Et, and in the same drawing, Et can be read as Es, so that periods used in both determination processes can be made different.

Thereby, in the flat determination and the noise determination, it is possible to select an optimum period and perform a more accurate determination.
<Other application examples>

Needless to say, the present disclosure can also be applied to a case where the present disclosure is achieved by supplying a program to a system or apparatus. Then, a storage medium (or memory) storing a program represented by software for achieving the present disclosure is supplied to the system or apparatus, and the computer (or CPU or MPU) of the system or apparatus stores it in the storage medium. The effect of the present disclosure can also be enjoyed by reading and executing the program code.

In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the storage medium storing the program code constitutes the present disclosure.

Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (operating system) running on the computer based on the instruction of the program code However, it is needless to say that a case where the function of the above-described embodiment is realized by performing part or all of the actual processing and the processing is included.

Furthermore, after the program code read from the storage medium is written to another storage medium provided in the function expansion board inserted into the computer or the function expansion unit connected to the computer, based on the instruction of the program code, It goes without saying that the CPU of the function expansion board or function expansion unit performs part or all of the actual processing and the functions of the above-described embodiments are realized by the processing.

The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present disclosure is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

1: Information processing system 100: Server 110: CPU
111: statistical processing unit 112: graph creation unit 113: result output unit 120: memory 121: pulsation interval storage unit 122: data storage unit 160: communication interface 161: reception unit 162: transmission unit 300: diagnostic terminal (information processing apparatus) )
310: CPU
311: Statistical processing unit 312: Graph creation unit 313: Result output unit 320: Memory 321: Beat interval storage unit 321A: Correspondence table 322: Data storage unit 330: Display 331: Light 332: Speaker 360: Communication interface 361: Receiver 362: Transmitter 370: Speaker 401: Electrode 402: Electrode 403: Electrode 500: Signal processor 501: Simple signal processor 511: Electrocardiogram preprocessor 512: Pulsation interval calculator 530: Display 531: Light 532 : Speaker 560: Transmission unit 570: Simple electrocardiogram preprocessing unit

Claims (17)

1. A plurality of electrodes;
   The variance or standard deviation of the potential difference in the first period and the variance or standard deviation of the potential difference in the second period including the period before the first period, which are obtained through the plurality of electrodes. And a processor having first determination means for determining whether a predetermined condition is satisfied based on the information processing apparatus.
2. The first determination means is configured when the variance or standard deviation of the potential difference in the first period differs from the variance or standard deviation of the potential difference in the second period by a predetermined ratio or more than a predetermined value. The information processing apparatus according to claim 1, wherein the predetermined condition is satisfied.
3. The information processing apparatus according to claim 1 or 2, wherein the second period is longer than the first period.
4. The processor compares the variance or standard deviation of the potential difference in the third period obtained through the plurality of electrodes with a predetermined threshold value,
   4. The information processing according to claim 1, further comprising: a second determination unit configured to determine that the predetermined condition is satisfied when the potential difference in the third period is greater than the predetermined threshold. 5. apparatus.
5. The information processing apparatus according to claim 4, wherein the second determination unit is performed before the first determination unit.
6. The information processing apparatus according to claim 4 or 5, wherein the third period is the same period as the first period.
7. The processor outputs a first result when the predetermined condition is satisfied;
   The information processing apparatus according to any one of claims 1 to 6, wherein a second result is output when the predetermined condition is not satisfied.
8. The processor further comprises output means for outputting the first result or the second result,
   The information processing apparatus according to claim 7.
9. The output means is means for displaying on a display device,
   The information processing apparatus according to claim 7, wherein the output unit displays the second result on the display device.
10. The information processing apparatus according to claim 7, wherein the output unit displays the first result and the second result on the display device in parallel or in a superimposed manner.
11. The information processing apparatus according to claim 7, wherein the output means displays the first result on the display device in a display form different from the second result.
12. The output means is means for outputting to a speaker,
    The information processing apparatus according to claim 7, wherein the processor causes the speaker to output sound as the first result.
13. The output means is means for lighting a lamp,
    The information processing apparatus according to claim 7, wherein the processor turns on the lamp as the first result.
14. A plurality of electrodes;
    A processor for processing the measurement results of the plurality of electrodes, and an output unit for outputting the measurement results,
    The processor obtains a variance or standard deviation of a potential difference in a first period and a variance or standard of a potential difference in a second period including a period before the first period, which are obtained through the plurality of electrodes. Based on the deviation, a wearable terminal that causes the output unit to output a first result when a predetermined condition is satisfied, and causes the output unit to output a second result when the predetermined condition is not satisfied .
15. The output unit is a speaker that outputs sound;
    The wearable terminal according to claim 14, wherein the processor causes the speaker to output a sound as the first result when the predetermined condition is satisfied.
16. The output unit is a lamp including a light emitter,
    The wearable terminal according to claim 14, wherein the processor causes the lamp to light or blink as the first result when the predetermined condition is satisfied.
17. A communication interface;
    A transition of a potential difference measured at a plurality of electrodes is acquired via the communication interface, and a second period including a variance or standard deviation of the potential difference in the first period and a period before the first period. A processor having first determination means for determining whether a predetermined condition is satisfied based on the variance or standard deviation of the potential difference of
    The information processing apparatus, wherein the processor outputs a first result when the predetermined condition is satisfied, and outputs a second result when the predetermined condition is not satisfied.

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