Patent Description:
While pain is fundamentally subjective, objective evaluation thereof is desired for treatment. Patients often suffer disadvantages by underestimating pain. In this regard, methods for objective measurement of pain have been proposed (see, for example, Patent Literature <NUM>).

US patent application with publication number <CIT> discloses a method of detecting pain in a subject, comprising the steps of generating brain wave data based on brain wave activity of the subject and comparing the brain wave data to reference data to generate results data. [PTL <NUM>] <CIT>.

However, the above-described conventional techniques cannot correctly measure pain in some cases due to individual differences in subjects of measurement.

In this regard, the present invention provides a pain measurement device that can objectively and highly precisely measure pain being experienced bv a subject of measurement, as specified in the claims.

The pain measurement device according to one aspect of the present disclosure is a pain measurement device for measuring pain being experienced by a subject of measurement, comprising: a determination unit for determining a baseline stimulation amount corresponding to baseline pain in the subject of measurement based on a relationship between a pain level reported by the subject of measurement and a stimulation amount applied to the subject of measurement; and a measurement unit for measuring pain being experienced by the subject of measurement when brainwave data of a subject is measured by the comparing brainwave data of a subject measured from the subject of measurement, with reference brainwave data of the subject of measurement corresponding to the baseline stimulation amount.

With this configuration, the baseline stimulation amount corresponding to baseline pain in the subject of measurement can be determined, based on the relationship between the pain level reported by the subject of measurement and the stimulation amount applied to the subject of measurement. In addition, pain can be measured using reference brainwave data of the subject of measurement corresponding to the baseline stimulation amount. Thus, relative pain of the subject of measurement with respect to baseline pain can be measured using reference brainwave data suited to the individuality of the subject of measurement. As a result, pain being experienced by the subject of measurement can be objectively and highly precisely measured.

For example, in a relationship between the pain level and the stimulation amount, the determination unit may determine a representative value in a range of stimulation amounts, where a ratio of an increase in the pain level to an increase in the stimulation amount exceeds a predetermined threshold ratio, as the baseline stimulation amount.

With this configuration, the representative value in a range of stimulation amounts, where the ratio of an increase in the pain level to an increase in the stimulation amount exceeds the predetermined threshold ratio, can be determined as the baseline stimulation amount. Thus, the relationship between the pain level and the stimulation amount represented by a sigmoid curve can be utilized to attempt to normalize baseline pain. As a result, pain can be measured more objectively.

For example, the representative value may be at least one of a minimum value, a median value, and a maximum value.

With this configuration, at least one of the minimum value, the median value, and the maximum value can be used as a representative value.

For example, the measurement unit may calculate at least one characteristic value from each of the brainwave data of a subject and the reference brainwave data, and measure pain being experienced by the subject of measurement based on a result of comparison of at least one characteristic value calculated from the brainwave data of a subject, with at least one characteristic value calculated from the reference brainwave data.

With this configuration, pain being experienced by the subject of measurement can be measured, based on a characteristic value calculated from the brainwave data of a subject and a characteristic value calculated from the reference brainwave data. Thus, pain can be measured more effectively by comparing brainwave data of a subject and reference brainwave data.

For example, said at least one characteristic value may comprise a first characteristic value representing an amplitude of a brainwave's waveform induced by a stimulation.

With this configuration, a first characteristic value representing an amplitude of a brainwave's waveform can be used to compare the brainwave data of a subject with the reference brainwave data. Since the amplitude is dependent on the pain level, brainwave data can be more effectively compared, and pain can be measured with high precision.

For example, the measurement unit may determine that the subject of measurement has greater pain than the baseline pain, if a first evaluation value, indicating a relative size of a first characteristic value calculated from the brainwave data of a subject with respect to a first characteristic value calculated from the reference brainwave data, is greater than a first threshold value.

With this configuration, the subject of measurement can be determined to have greater pain than the baseline pain if the first evaluation value is greater than the first threshold value. Thus, pain can be measured with high precision by utilizing a characteristic of an amplitude being greater as pain intensifies.

For example, said at least one characteristic value may comprise a second characteristic value representing a latency in a brainwave's waveform induced by a stimulation.

With this configuration, the second characteristic value representing a latency in a brainwave's waveform can be used to compare the brainwave data of a subject with the reference brainwave data. Since a latency is dependent on the pain level, brainwave data can be compared more effectively, and pain can be measured with high precision.

For example, the measurement unit may determine that the subject of measurement has greater pain than the baseline pain, if a second evaluation value, indicating a relative size of a second characteristic value calculated from the brainwave data of a subject with respect to a second characteristic value calculated from the reference brainwave data, is less than a second threshold value.

With this configuration, it can be determined that the subject of measurement has greater pain than the baseline pain if the second evaluation value is greater than the second threshold value. Thus, pain can be measured with high precision by utilizing a characteristic of latency being shorter for greater pain.

For example, the pain measurement device may further comprise an estimation unit for estimating a second pain level to be reported by the subject of measurement and second brainwave data to be measured from the subject of measurement, when a stimulation at a second stimulation amount that is different from a plurality of first stimulation amounts is applied to the subject of measurement, based on a first pain level reported by the subject of measurement and first brainwave data measured from the subject of measurement when stimulations at the plurality of first stimulation amounts are individually applied to the subject of measurement; wherein the determination unit determines the reference stimulation amount based on a relationship between the first pain level and the second pain level, and the first stimulation amount and the second stimulation amount.

With this configuration, the pain level and brainwave data corresponding to a stimulation amount that is not actually applied to the subject of measurement can be estimated. Thus, the number of times a stimulation is applied to the subject of measurement can be reduced, and pain generated in the subject of measurement by the stimulation can be suppressed. In particular, significant pain generated in the subject of measurement by a large stimulation can be avoided by estimating the pain level and brainwave data corresponding to a large stimulation amount.

A pain measurement system according to one aspect of the present disclosure comprises: a pain measurement device for measuring pain being experienced by a subject of measurement, a stimulation device for applying stimulations at a plurality of stimulation amounts individually to the subject of measurement; and an electroencephalograph for (i) measuring each of brainwave data of the subject of measurement when the stimulations at the plurality of stimulation amounts are applied to the subject of measurement and (ii) measuring brainwave data of a subject used in measurement of pain of the subject of measurement, wherein the pain measurement device comprises a storing unit for storing brainwave data measured when the stimulations at the plurality of stimulation amounts are applied individually to the subject of measurement, along with a stimulation amount and a pain level reported by the subject of measurement, a determination unit for determining a baseline stimulation amount corresponding to baseline pain in the subject of measurement based on a relationship between the pain level reported by the subject of measurement and the stimulation amounts applied to the subject of measurement; and a measurement unit for measuring pain being experienced by the subject of measurement when the brainwave data of a subject is measured by comparing the brainwave data of a subject measured from the subject of measurement with reference brainwave data corresponding to the baseline stimulation amount.

With this configuration, an effect similar to that of the above-described pain measurement device can be achieved.

These generic or specific embodiments may be materialized with an integrated circuit, computer program, or a recording medium such as computer-readable CD-ROM, or with any combination of an integrated circuit, computer program, and a recording medium.

According to one aspect of the present invention, pain being experienced by a subject of measurement can be objectively measured and measurement precision can be enhanced.

Hereinafter, the embodiments are explained in detail while referring to the drawings.

Each of the embodiments explained below shows either a generic or a specific example. The numerical values, shapes, materials, constituent elements, arrangement position and connection form of the constituent elements, steps, the order of steps, and the like shown in the following embodiments are one example, which is not intended to limit the Claims. Further, constituent elements in the following embodiments that are not recited in an independent claim setting forth the superordinate concept are explained as an optional constituent element.

<FIG> is a block diagram showing the configuration of the pain measurement system in Embodiment <NUM>. The pain measurement system comprises a pain measurement device <NUM>, a stimulation device <NUM>, and an electroencephalograph <NUM>.

The pain measurement device <NUM> measures pain being experienced by a subject of measurement <NUM>. A subject of measurement is a living body in which pain induces a change in brainwaves. A subject of measurement does not need to be limited to humans.

The stimulation device <NUM> applies stimulations at a plurality of stimulation amounts individually to the subject of measurement <NUM>. Specifically, the stimulation device <NUM> applies, for example, a plurality of stimulations in order while changing the stimulation amount to the subject of measurement <NUM>.

In this regard, a stimulation is applied to the subject of measurement <NUM> from the outside of the subject of measurement <NUM> to induce pain of various levels to the subject of measurement <NUM>. Specifically, a stimulation is, for example, electric stimulation or a thermal stimulation.

The subject of measurement <NUM> subjectively reports the pain level indicating the degree of pain generated by a stimulation applied by the stimulation device <NUM>. For example, the subject of measurement <NUM> reports the pain level in a visual analog scale (VAS) when a stimulation is applied. VAS is a method of reporting a pain level by indicating which position the current pain level is on a <NUM> straight line representing the pain level from <NUM> to <NUM>.

The electroencephalograph <NUM> measures electric activity generated in the brain of the subject of measurement <NUM> with an electrode on the scalp. In addition, the electroencephalograph <NUM> outputs results of measurement, brainwave data. Specifically, the electroencephalograph <NUM> measures each brainwave data when stimulations at a plurality of stimulation amounts are applied to the subject of measurement <NUM> by the stimulation device <NUM>. Furthermore, the electroencephalograph <NUM> measures brainwave data of a subject used in the measurement of pain of the subject of measurement <NUM>.

The stimulation amount of a stimulation applied to the subject of measurement <NUM> by the stimulation device <NUM>, the pain level reported by the subject of measurement <NUM>, and brainwave data that is output from the electroencephalograph <NUM> are input into the pain measurement device <NUM> and are used for obtaining reference brainwave data.

Next, the detailed configuration of the pain measurement device <NUM> is explained. As shown in <FIG> , the pain measurement device <NUM> comprises a storing unit <NUM>, a determination unit <NUM>, and a measurement unit <NUM>.

The storing unit <NUM> is, for example, a hard drive or a semiconductor memory. The storing unit <NUM> stores a stimulation amount of a stimulation applied to the subject of measurement <NUM> by the stimulation device <NUM>, the pain level reported by the subject of measurement <NUM>, and brainwave data output from the electroencephalograph <NUM>.

The determination unit <NUM> is materialized by, for example, a processor and a memory. The determination unit <NUM> determines a baseline stimulation amount corresponding to baseline pain in the subject of measurement <NUM>, based on the relationship between the pain level reported by the subject of measurement <NUM> and the stimulation amount applied to the subject of measurement <NUM>. For example, the determination unit <NUM> determines a representative value (e.g., the minimum value, the median value, the maximum value, or the like) in a range where a pain level increases with an increase in the stimulation amount in the relationship between the pain level reported by the subject of measurement <NUM> and the stimulation amount applied to the subject of measurement <NUM> as a baseline stimulation amount. The determination of the baseline stimulation amount is discussed in detail below.

The measurement unit <NUM> measures the pain being experienced by the subject of measurement <NUM> when brainwave data of a subject is measured by comparing the brainwave data of a subject measured from the subject of measurement <NUM> with the reference electroencephalograph data. Electroencephalograph data of a subject is electroencephalograph data measured from the subject of measurement <NUM> for measuring pain being experienced by the subject of measurement <NUM>. Further, reference electroencephalograph data is electroencephalograph data referred to for measuring pain from electroencephalograph data of a subject. In this Embodiment, reference electroencephalograph data is electroencephalograph data measured from the subject of measurement <NUM> when a stimulation at a baseline stimulation amount is applied to the subject of measurement <NUM>.

For example, at least one characteristic value calculated from each of brainwave data of a subject and reference electroencephalograph data is used for comparison of the brainwave data of a subject with the reference electroencephalograph data. The measurement of pain by comparing brainwave data of a subject with reference brainwave data is discussed in detail below.

Next, the operation of a pain measurement system with the above configuration is explained.

First, <FIG> is used to explain the process of collecting brainwave data and pain levels. <FIG> is a flow chart showing the process of collecting brainwave data and pain levels in Embodiment <NUM>.

In the stimulation device <NUM>, one stimulation amount that has not been selected is selected from a plurality of stimulation amounts (S11). For example, one stimulation amount that has not been selected is selected from electric stimulation amounts of <NUM>µA, <NUM>µA, <NUM>µA, <NUM>µA, and <NUM>µA.

Next, the stimulation device <NUM> applies a stimulation at the selected stimulation amount to the subject of measurement <NUM> (S12). When a stimulation is applied in step S12, the electroencephalograph <NUM> measures brainwave data from the subject of measurement <NUM> (S13). Furthermore, the pain level reported by the subject of measurement <NUM> in response to the stimulation applied in step S12 is obtained (S14).

The stimulation amount selected in step S11, the brainwave data measured in step S13, and the pain level obtained in step S14 are stored in the storing unit <NUM> (S15).

If all of the plurality of stimulation amounts have already been selected (Yes in S16), the process ends. If one of the plurality of stimulation amounts has not been selected (No in S16), the process returns to step S11.

As disclosed above, stimulations at a plurality of stimulation amounts are applied to the subject of measurement <NUM> in order, and brainwave data and pain level corresponding to each stimulation amount are stored in the storing unit <NUM>.

Next, <FIG> are used to explain the process of measuring pain. <FIG> is a flow chart showing the process of measuring pain in Embodiment <NUM>. <FIG> is a diagram showing one example of the relationship between the pain level and stimulation amount in Embodiment <NUM>. <FIG> is a diagram showing an example of a brainwave's waveform in Embodiment <NUM>.

The determination unit <NUM> determines a baseline stimulation amount corresponding to baseline pain in the subject of measurement <NUM>, based on the relationship between the pain level reported by the subject of measurement <NUM> and the stimulation amount applied to the subject of measurement <NUM> (S21).

As shown in <FIG> , the relationship between pain level and stimulation amount is represented by a sigmoid (S-shaped) curve. However, the shape of a sigmoid curve (e.g., maximum value, minimum value, and the like) is different for each subject of measurement. Thus, pain levels are normalized by utilizing a characteristic point (e.g., inflection point or the like) in a sigmoid curve in this Embodiment. Specifically, the determination unit <NUM> determines a representative value (e.g., the minimum value, the median value, the maximum value, or the like) in a range of stimulation amounts, where the pain level increases with an increase in the stimulation amount in a relationship between the pain level and the stimulation amount as a baseline stimulation amount.

The range of stimulation amounts where the pain level increases with an increase in the stimulation amount is determined by comparing the ratio of increase in the pain level to an increase in the stimulation amount with a predetermined threshold ratio. That is, the range of stimulation amounts, where the pain level increases with an increase in the stimulation amount, is a range where a ratio of increase in the pain level to an increase in the stimulation amount exceeds a predetermined threshold ratio. A predetermined threshold ratio may be experimentally or empirically determined.

The minimum value of a range of stimulation amounts, where the pain level increases with an increase in the stimulation amount, corresponds to a stimulation amount at which an increase in pain level starts. That is, the minimum value in said range is the maximum stimulation amount among stimulation amounts where the pain level does not decrease any more even with a decrease in the stimulation amount.

The maximum value in a range of stimulation amounts where the pain level increases with an increase in the stimulation amount corresponds to a stimulation amount at which the pain level stops increasing. That is, the maximum value in said range is the minimum stimulation amount among stimulation amounts where the pain level does not increase any more even with an increase in the stimulation amount.

In <FIG> , the pain level increases with an increase in the stimulation amount in the range <NUM>. In this regard, the determination unit <NUM> determines, for example, the minimum value (<NUM>µA) in the range <NUM> as the baseline stimulation amount. As another example, the determination unit <NUM> may determine the median value (<NUM>µA) in the range <NUM> as the baseline stimulation amount. As another example, the determination unit <NUM> may determine the maximum value (<NUM>µA) in the range <NUM> as the baseline stimulation amount. As another example, the determination unit <NUM> may determine all or any two of the minimum value, the median value, and the maximum value in the range <NUM> as the baseline stimulation amounts.

Next, the measurement unit <NUM> obtains reference brainwave data from the storing unit <NUM> (S22). That is, the measurement unit <NUM> obtains brainwave data measured from the subject of measurement <NUM> when a stimulation at the baseline stimulation amount is applied to the subject of measurement <NUM> from the storing unit <NUM> as reference brainwave data.

Subsequently, the measurement unit <NUM> calculates a reference characteristic value from the reference brainwave data (S23). Specifically, the measurement unit <NUM> calculates reference characteristic values comprising a first characteristic value and a second characteristic value from the reference brainwave data.

In this Embodiment, the first characteristic value represents an amplitude of a brainwave's waveform induced by a stimulation. Specifically, the first characteristic value is, for example, the difference between the maximum peak value and the minimum peak value (i.e., peak to peak value). For example in <FIG> , the measurement unit <NUM> calculates the maximum difference (N1-P1) among three differences (N1-P1, N2-P2, and N1-P2) as the first characteristic value.

In this Embodiment, the second characteristic value represents a latency in a brainwave's waveform induced by a stimulation. A latency is the time period between application of a stimulation and a reaction. Specifically, the second characteristic value is, for example, a time period between application of a stimulation and a first peak of a brainwave's waveform induced by the stimulation. For example in <FIG> , the measurement unit <NUM> calculates the time period (T1-T0) from time T0 at which a stimulation is applied to time T1 at which the first peak appears as the second characteristic value.

Next, the measurement unit <NUM> obtains brainwave data of a subject (S24). That is, the measurement unit <NUM> obtains brainwave data measured from the subject of measurement <NUM> as brainwave data of a subject for measuring the pain being experienced by the subject of measurement <NUM>.

Subsequently, the measurement unit <NUM> calculates brainwave data of a subject from a characteristic value of a subject (S25). Specifically, the measurement unit <NUM> calculates characteristic values of a subject comprising a first characteristic value and a second characteristic value from brainwave data of a subject as in step S23.

The measurement unit <NUM> then compares the characteristic value of a subject with the reference characteristic value (S26). Specifically, the measurement unit <NUM> compares the first characteristic value comprised in the characteristic value of a subject, with the first characteristic value comprised in the reference characteristic value. In this Embodiment, the measurement unit <NUM> calculates a first evaluation value indicating the relative size of the first characteristic value comprised in the characteristic value of a subject with respect to the first characteristic value comprised in the reference characteristic value, as a result of comparison of the first characteristic values. The first evaluation value is calculated using, for example, the following equation (<NUM>).

Wherein E1 represents the first evaluation value; Ax represents the first characteristic value comprised in the characteristic value of a subject; and Ar represents the first characteristic value comprised in the reference characteristic value.

Furthermore, the measurement unit <NUM> compares the second characteristic value comprised in the characteristic value of a subject, with the second characteristic value comprised in the reference characteristic value. In this Embodiment, the measurement unit <NUM> calculates a second evaluation value, indicating the relative size of the second characteristic value comprised in the characteristic value of a subject with respect to the second characteristic value comprised in the reference characteristic value, as a result of comparison of the second characteristic values. The second evaluation value is calculated using, for example, the following equation (<NUM>).

Wherein E2 represents the second evaluation value; Bx represents the second characteristic value comprised in the characteristic value of a subject; and Br represents the second characteristic value comprised in the reference characteristic value.

In this manner, the measurement unit <NUM> calculates the first evaluation value and the second evaluation value as a result of comparison of the characteristic value of a subject with the reference characteristic value of a subject.

Next, the measurement unit <NUM> measures pain being experienced by the subject of measurement <NUM>, based on the result of comparison of the characteristic value of a subject with the reference characteristic value of a subject (S27). In this Embodiment, the measurement unit <NUM> determines that the subject of measurement <NUM> has greater pain than pain corresponding to the baseline stimulation amount if the first evaluation value and the second evaluation value meet a predetermined condition.

Specifically, the measurement unit <NUM> determines that the subject of measurement <NUM> has greater pain than pain corresponding to the baseline stimulation amount if, for example, the first evaluation value is greater than the first threshold value and the second evaluation value is less than the second threshold value. In this case, the predetermined condition is represented by the following (<NUM>).

Wherein Th1 is the first threshold value; and Th2 is the second threshold value.

For instance, if the minimum value in the range <NUM> is used as the baseline stimulation amount, the measurement unit <NUM> determines that "there is pain" if condition (<NUM>) is met. If condition (<NUM>) is not met, it determines that "there is no pain". Further, if the median value in the range <NUM> is used as the baseline stimulation amount, the measurement unit <NUM> determines that "there is medium level or greater pain" if condition (<NUM>) is met, and determines that "there is no pain" or "there is low level of pain" if condition (<NUM>) is not met. Further, if the maximum value in the range <NUM> is used as the baseline stimulation amount, the measurement unit <NUM> determines that "there is high level of pain" if condition (<NUM>) is met, and determines that "there is no pain" or "there is a medium level or less pain" if condition (<NUM>) is not met. The measurement unit <NUM> can distinguish the degree of pain being experienced by the subject of measurement <NUM> into one of "none", "low level", "medium level", and "high level" by using these three baseline stimulation amounts in combination.

In view of the above, with the pain measurement device <NUM> according to this Embodiment, the determination unit <NUM> can determine the baseline stimulation amount corresponding to baseline pain in the subject of measurement <NUM>, based on the relationship between the pain level reported by the subject of measurement <NUM> and the stimulation amount applied to the subject of measurement <NUM>. In addition, the measurement unit <NUM> can measure pain using reference brainwave data of the subject of measurement <NUM> corresponding to the baseline stimulation amount. Thus, the pain measurement device <NUM> can measure relative pain of the subject of measurement <NUM> with respect to the baseline pain using reference brainwave data suited to the individuality of the subject of measurement <NUM>. As a result, the pain measurement device <NUM> can objectively and highly precisely measure pain being experienced by the subject of measurement <NUM>.

With the pain measurement device <NUM> according to this embodiment, the determination unit <NUM> can determine the representative value in the range of stimulation amounts, where the pain level increases with an increase in the stimulation amount, as the baseline stimulation amount. Thus, the determination unit <NUM> can achieve normalization of the baseline pain by utilizing the relationship between the pain level and a plurality of stimulation amounts represented by a sigmoid curve. As a result, the pain measurement device <NUM> can measure pain more objectively.

With the pain measurement device <NUM> according to this embodiment, the measurement unit <NUM> can measure pain being experienced by a subject of measurement, based on a result of comparison of the characteristic value calculated from the brainwave data of a subject and the characteristic value calculated from the reference brainwave data. Thus, the measurement unit <NUM> can compare brainwave data of a subject with reference brainwave data more effectively.

With the pain measurement device <NUM> according to this embodiment, the measurement unit <NUM> can compare brainwave data of a subject with reference brainwave data using the first characteristic value representing an amplitude of a brainwave's waveform. Since amplitude is dependent on pain level, the measurement unit <NUM> can compare brainwave data more effectively and measure pain with high precision.

With the pain measurement device <NUM> according to this embodiment, the measurement unit <NUM> can determine that a subject of measurement has greater pain than baseline pain if the first evaluation value is greater than the first threshold value. Thus, the measurement unit <NUM> can measure pain with high precision by utilizing a characteristic of an amplitude being greater for greater pain.

The inventor actually conducted an experiment using "<NUM>" as the first threshold value on <NUM> subjects. As a result, it was possible to correctly distinguish the presence/absence of pain in <NUM> subjects.

With the pain measurement device <NUM> according to this embodiment, the measurement unit <NUM> can compare brainwave data of a subject with reference brainwave data using the second characteristic value representing a latency in a brainwave's waveform. Since a latency is dependent on the pain level, the measurement unit <NUM> can compare brainwave data more effectively and measure pain with high precision.

With the pain measurement device <NUM> according to this embodiment, the measurement unit <NUM> can determine that a subject of measurement has greater pain than baseline pain if the second evaluation value is greater than the second threshold value. Thus, the measurement unit <NUM> can measure pain more precisely by utilizing a characteristic of latency being shorter for greater pain.

The inventor actually conducted an experiment using "<NUM>" as the second threshold value on <NUM> subjects. As a result, it was possible to correctly distinguish the presence/absence of pain in <NUM> subjects.

The inventor actually conducted a further experiment using "<NUM>" as the first threshold value and "<NUM>" as the second threshold value on <NUM> subjects. As a result, it was possible to correctly distinguish the presence/absence of pain in <NUM> subjects.

Next, Embodiment <NUM> is explained. This embodiment is different from the above-described Embodiment <NUM> in that a pain level and brainwave data corresponding to a stimulation amount that is not actually applied to a subject of measurement are estimated, and the result of estimation is used to determine a baseline stimulation amount. This embodiment is explained hereinafter mainly with respect to the above-described difference from Embodiment <NUM>.

<FIG> is a block diagram showing a configuration of the pain measurement system in Embodiment <NUM>. In <FIG> , constituent elements that are substantially the same as <FIG> are assigned with the same symbol, and explanation thereof is omitted when appropriate. The pain measurement system according to this embodiment comprises a pain measurement device 10A, a stimulation device <NUM>, and an electroencephalograph <NUM>.

The pain measurement device 10A measures pain being experienced by a subject of measurement <NUM>. The pain measurement device 10A comprises a storing unit <NUM>, determination unit <NUM>, a measurement unit <NUM>, and an estimation unit 14A.

The estimation unit 14A estimates a pain level and brainwave data corresponding to a stimulation amount that is not actually applied to the subject of measure <NUM>, based on a pain level actually reported by the subject of measurement <NUM> and brainwave data measured from the subject of measurement <NUM>. That is, the estimation unit 14A estimates a second pain level to be reported by the subject of measurement <NUM> and second brainwave data to be measured from the subject of measurement <NUM> when stimulations at second stimulation amounts that are different from a plurality of first stimulation amounts is applied to the subject of measurement <NUM>, based on the first pain level reported by the subject of measurement <NUM> and first brainwave data measured from the subject of measurement <NUM> when stimulations at the plurality of first stimulation amounts are individually applied to the subject of measurement <NUM>. In this regard, the estimated pain level and brainwave data are stored in the storing unit <NUM> with the stimulation amounts. The brainwave data estimated by the estimation unit 14A does not need to be a brainwave's waveform and may be a characteristic value of brainwaves (e.g., amplitude, latency, or the like).

A method of estimating a pain level and brainwave data by the estimation unit 14A may be any method. Such a method is not particularly limited. For example, the method of estimation may use regression analysis or machine learning. For example, the estimation unit 14A may estimate a hypothetical pain level and brainwave data of the subject of measurement <NUM> upon application of a stimulation at a stimulation amount that is not actually applied to the subject of measurement <NUM>, by applying regression analysis on a pain level reported by the subject of measurement <NUM> and brainwave data measured from the subject of measurement <NUM>, when stimulations at a plurality of stimulation amounts are applied individually to the subject of measurement <NUM>. As another example, the estimation unit 14A may estimate a pain level and brainwave data for a stimulation amount that is not actually applied to the subject of measurement <NUM>, by using a model constructed by machine learning using a pain level and brainwave data obtained by applying a stimulation to a living body that is different from the subject of measurement <NUM> as training data.

Next, the operation of a pain measurement system configured in the above manner is explained. The process of collecting brainwave data and pain levels is substantially the same as Embodiment <NUM> except for the number of stimulations applied. Thus, illustration thereof is omitted.

In this embodiment, the subject of measurement <NUM> is only applied with a stimulation in a small stimulation amount, in order to suppress pain caused by the stimulation applied to the subject of measurement <NUM>. For example, the stimulation device <NUM> applies an electric stimulation of <NUM>µA or less to the subject of measurement <NUM>. As a result, the pain level reported by the subject of measurement <NUM> and brainwave data measured from the subject of measurement <NUM> when electric stimulations of <NUM>µA or less are individually applied are stored in the storing unit <NUM> with stimulation amounts.

<FIG> is a flow chart showing the process of measuring pain in Embodiment <NUM>. In <FIG> , processing that is substantially the same as <FIG> is assigned with the same symbol, and explanation thereof is omitted when appropriate.

In this embodiment, a pain level and brainwave data for a stimulation amount that is not actually applied to the subject of measurement <NUM> are estimated before determining a baseline stimulation amount (S20A). Specifically, the estimation unit 14A estimates a pain level to be reported by the subject of measurement <NUM> (i.e., second pain level) and brainwave data to be measured from the subject of measurement <NUM> (i.e., second brainwave data), when a stimulation of unknown amount is applied to the subject of measurement <NUM>, based on the pain level (i.e., first pain level) and brainwave data (i.e., first brainwave data) stored in the storing unit <NUM> in step S15.

For example, the estimation unit 14A estimates the pain level to be reported by the subject of measurement <NUM> and brainwave data to be measured from the subject of measurement <NUM> when an electric stimulation greater than <NUM>µA is applied to the subject of measurement <NUM> using the relationship between the pain level reported by the subject of measurement <NUM> when an electric stimulation of <NUM>µA or less is actually applied to the subject of smeasurement <NUM> and the amount of electric stimulation. It should be noted that the relationship between the size of electric stimulation actually applied and the size of electric stimulation at which pain level or the like is estimated is not limited thereto. For example, an electric stimulation greater than <NUM>µA may be actually applied to the subject of measurement <NUM>, and the pain level or the like corresponding to an electric stimulation of <NUM>µA or less may be estimated. As another example, an electric stimulation of <NUM>µA to <NUM>µA may be actually applied to the subject of measurement <NUM>, and a pain level or the like corresponding to an electric stimulation less than <NUM>µA or <NUM>µA may be estimated.

Subsequently, the determination unit <NUM> determines a baseline stimulation amount corresponding to baseline pain in the subject of measurement <NUM>, based on the relationship between the stimulation amount and the pain level (S21A) stored in the storing unit <NUM>. That is, the determination unit <NUM> determines a baseline stimulation amount using both the actually reported pain level and the estimated pain level.

As discussed above, with the pain measurement device 10A according to this embodiment, the estimation unit 14A can estimate a pain level and brainwave data corresponding to a stimulation amount that is not actually applied to the subject of measurement <NUM>. Thus, a pain measurement system can reduce the number of stimulations applied to the subject of measurement <NUM> and suppress pain generated in the subject of measurement <NUM> by a stimulation. In particular, significant pain generated in the subject of measurement <NUM> with a large stimulation can be avoided by estimating a pain level and brainwave data corresponding to a large stimulation amount.

The pain measurement devices according to one or more aspects of the present invention have been explained above based on embodiments. The present invention, however, is not limited to these embodiments.

For example, the storing unit <NUM> in each of the above-described embodiments may not be included in the pain measurement device <NUM> or 10A. In this case, the storing unit <NUM> may be a storing device connected to the pain measurement device <NUM> or 10A via a communication network.

Each of the above-described embodiments explains a case where the pain level is reported by a subject of measurement in VAS, but this does not necessarily need to be limited to VAS. Pain levels do not need to be explicitly reported by a subject of measurement. For example, when the action of a subject of measurement changes in accordance with the pain level, the action may be considered as reported pain levels.

The baseline stimulation amount in each of the above-described embodiments is one example, such that the amount is not limited thereto. For example, the baseline stimulation amount can be a mean value of the minimum value and the median value in the range <NUM>.

Each of the above-described embodiments used a first characteristic value and a second characteristic value for comparing brainwave data of a subject with reference brainwave data, but these characteristic values do not need to be used. In such a case, brainwave data of a subject and reference brainwave data may be compared, for example, by pattern matching. Further, only one of the first and second characteristic values can be used.

The first characteristic value and the second characteristic valuevalue in each of the above-described embodiments are one example, such that the amounts are not limited thereto. For example, the first characteristic value may simply be a peak value, instead of a peak to peak value.

Further, the first evaluation value and the second evaluation value in each of the above-described embodiments are one example, such that the values are not limited thereto. For example, a linear distance or Mahalanobis distance may be used as the evaluation value.

Some or all of the constituent elements comprised by the pain measurement device in each of the above-described embodiments may be composed of a single system LSI (Large Scale Integration).

System LSIs are ultra-multifunctional LSIs manufactured by integrating multiple constituents on a single chip. Specifically, system LSIs are computer systems comprised of a microprocessor, ROM (Read Only Memory), RAM (Random Access Memory), and the like. A computer program is stored in the ROM. The microprocessor is operated in accordance with the computer program for the system LSI to accomplish the function thereof.

LSI is called a system LSI in this instance, but LSI may also be called an IC, LSI, super LSI, or ultra LSI depending on the difference in the degree of integration. Further, the approach of forming an integrated circuit is not limited to LSIs. This may be materialized with a dedicated circuit or all-purpose processor. After the manufacture of the LSI, a programmable FPGA (Field Programmable Gate Array) or a reconfigurable processor in which the connection or setting of a circuit cell inside an LSI can be reconfigured may be used.

Furthermore, if a technique of forming an integrated circuit that replaces LSI due to advancement in semiconductor technology or another derivative technique is developed, such a technique may certainly be used to integrate a function block. Application of biotechnology or the like is a possibility thereof.

In each of the above-described embodiments, each constituent element may be constructed with a dedicated hardware or materialized by executing a software program suited for each constituent element. Each constituent element may be materialized by a program executing unit, such as a CPU or processor, reading out and executing a software program recorded on a recording medium, such as a hard disk or a semiconductor memory. In this regard, software that materializes the pain measurement device of each of the above-described embodiments or the like includes the following programs.

Specifically, such a program makes a computer execute a pain measurement method for measuring pain being experienced by a subject of measurement, not part of the invention, comprising: a determination step for determining a baseline stimulation amount corresponding to baseline pain in the subject of measurement, based on a relationship between a pain level reported by the subject of measurement and a stimulation amount applied to the subject of measurement; and a measurement step for measuring pain being experienced by the subject of measurement, when brainwave data is measured by comparing brainwave data of a subject measured from the subject of measurement with reference brainwave data of the subject of measurement.

Claim 1:
A pain measurement device (<NUM>) for measuring pain being experienced by a subject of measurement (<NUM>), comprising:
a determination unit (<NUM>) for determining a baseline stimulation amount corresponding to baseline pain in the subject of measurement (<NUM>), based on a relationship between a pain level reported by the subject of measurement (<NUM>) and a stimulation amount applied to the subject of measurement (<NUM>); and
a measurement unit (<NUM>) for measuring pain being experienced by the subject of measurement (<NUM>) when brainwave data of a subject is measured by comparing the brainwave data of a subject measured from the subject of measurement (<NUM>), with reference brainwave data of the subject of measurement (<NUM>), wherein the reference brainwave data is measured from the subject of measurement (<NUM>) when a stimulation at the baseline stimulation amount is applied to the subject of measurement (<NUM>) and obtained from a storing unit (<NUM>);
characterized in that the determination unit (<NUM>) is configured to determine a representative value in a range (<NUM>) of stimulation amounts as said baseline stimulation amount, wherein said range (<NUM>) of stimulation amounts is a range where a ratio of increase in the pain level to an increase in the stimulation amount in a relationship between the pain level and the stimulation amount exceeds a predetermined threshold ratio.