Temperature measurement device, method, and program

Abstract

A temperature measurement device provided with: a sensor unit (1) that measures the temperature of a surface of a living body and the temperature at a position away from the living body; a temperature calculation unit (2) that calculates the observed value of an internal temperature of the living body on the basis of the measurement result of the sensor unit (1); a noise estimation unit (3) that uses the internal temperature measured by a thermometer at the start of the measurement as a reference temperature, uses the reference temperature as an initial value of an internal temperature estimation value, and, on the basis of the observed value and the estimation value, calculates the magnitude of noise mixed in the observed value; an estimation error calculation unit (4) that calculates a gain for correcting the estimation value on the basis of the magnitude of noise and calculates the difference between the observed value and the estimation value as an estimation error; and an estimation value update unit (5) that updates the estimation value on the basis of the reference temperature, the gain, and the estimation error.

Description

[Technical Field]

[0001] The present invention relates to a temperature measuring device, method and program for non-invasively and accurately measuring the internal temperature of a living body. [Background technology]

[0002] Recent research in chronobiology has revealed that the human circadian rhythm, or so-called internal clock, is closely related to various aspects of our body, including not only sleep, exercise, and work quality, but also the effectiveness of medication and the onset of disease. Circadian rhythms are generally constant, but are also known to vary significantly depending on exposure to light, exercise, diet, age, and gender.

[0003] Core body temperature is known as an index for measuring circadian rhythms, but the most common methods for measuring core body temperature are to insert a thermometer into the rectum or to measure the temperature of the eardrum with the ear sealed, which are very stressful methods for measuring core body temperature during daily activities or while sleeping.

[0004] On the other hand, there is a technology for non-invasively measuring the core body temperature of a living body, which estimates the core body temperature of a living body by replacing the heat flow with a pseudo one-dimensional equivalent circuit model (see Patent Document 1 and Non-Patent Document 1).

[0005] The method disclosed in Patent Document 1 and Non-Patent Document 1 uses a thermal equivalent circuit model of a living body 100 and a sensor 101 as shown in FIG. 11 to calculate the deep body temperature T cbt The deep body temperature T of the living body 100 is estimated. cbt is the temperature T of the surface of the sensor 101 that is in contact with the living body 100 when the sensor 101 is placed on the surface of the living body 100. skin and the temperature T of the upper surface of the sensor 101 opposite to the surface in contact with the living body 100. u Therefore, it can be estimated using equation (1). T cbt =T skin +α×H skin ···(1)

[0006] where H skin is the heat flux on the skin surface of the living body 100, and is expressed by equation (2). H skin =(T skin -T u ) / R s ···(2) In addition, α is the thermal resistance R of the living body 100 body The proportionality factor related to s is the thermal resistance of the sensor 101.

[0007] However, in the conventional methods disclosed in Patent Document 1 and Non-Patent Document 1, the flow of heat transported from the living body 100 through the sensor 101 to the outside air is assumed to be steady. Therefore, when the living body 100 is exposed to wind, when the living body 100 runs, or when the living body 100 suddenly moves from a warm place to a cold place, the deep body temperature T cbt There is a transient error in the estimation of

[0008] In addition, in the conventional method, the thermal resistance R of the living body 100 body is assumed to be constant regardless of time, and the proportionality coefficient α is also assumed to be constant. However, the state of blood flow near the skin of the living body 100 changes depending on the posture and movement of the living body 100. For this reason, the thermal resistance R body is not constant but changes from time to time.

[0009] As mentioned above, when a person moves between indoors and outdoors or lies down in daily life, the core body temperature T estimated by the conventional method cbt and true core body temperature T ref Turning over during sleep can also lead to errors. cbt and true core body temperature (tympanic membrane temperature) T measured by a tympanic membrane thermometer. ref This is shown in Figure 12.

[0010] According to Fig. 12, the estimated core body temperature T cbt and true core body temperature T ref This difference is due to the temperature T uand the temperature of the human skin surface T skin This is due to the difference in the time it takes for the blood flow to settle into a steady state, and the fact that blood flow changes transiently depending on a person's posture.

[0011] When measuring biosignals in daily life, various noises, such as environmental noise that is applied to the human body and the sensor through the external environment and noise caused by the human's active body movements, can cause transient errors in the measurement of biosignals. Therefore, signal processing technology that is robust against noise is required. Methods such as the Kalman filter have been proposed to suppress noise mixed into biosignals.

[0012] The method using the Kalman filter can reduce the effects of minute body movements and changes in blood flow. However, if the error of the model used in the Kalman filter is large, there is a problem in that it is not possible to reduce noise that gets mixed into the estimated core body temperature when the person is exposed to wind or when body movements occur that involve changes in posture. [Prior art documents] [Patent documents]

[0013] [Patent Document 1] Japanese Patent Application Publication No. 2020-003291 [Non-patent literature]

[0014] [Non-Patent Document 1] Y. Tanaka, D. Matsunaga, T. Tajima, and M. Seyama, “Robust Skin Attachable Sensor for Core Body Temperature Monitoring”, IEEE SENSORS JOURNAL, VOL. 21, NO. 14, pp. 16118-16123, JULY 15, 2021 Summary of the Invention [Problem to be solved by the invention]

[0015] The present invention has been made to solve the above-mentioned problems, and aims to provide a temperature measurement device, method, and program that can eliminate noise caused by the state of the living body being measured and accurately measure the internal temperature of the living body. [Means for solving the problem]

[0016] The temperature measuring device of the present invention comprises a sensor unit configured to measure the temperature of the surface of a living body and the temperature at a position away from the living body; a temperature calculation unit configured to calculate an observed value of the internal temperature of the living body based on the measurement results of the sensor unit; a noise estimation unit configured to use the internal temperature measured by a thermometer at the start of measurement as a reference temperature and the reference temperature as an initial value of an estimated value of the internal temperature, and to calculate the magnitude of noise mixed into the observed value based on the observed value and the estimated value; an estimation error calculation unit configured to calculate a gain for correcting the estimated value based on the magnitude of the noise and calculate the difference between the observed value and the estimated value as an estimation error; and an estimation value update unit configured to update the estimated value based on the reference temperature, the gain, and the estimation error, and is characterized in that the temperature measurement by the sensor unit, calculation of the observed value, the magnitude of the noise, the gain, and the estimation error, and updating the estimated value are repeatedly performed.

[0017] In addition, the temperature measurement method of the present invention includes a first step of using the internal temperature of the living body measured by a thermometer at the start of measurement as a reference temperature and setting the reference temperature as an initial value of an estimated value of the internal temperature; a second step of measuring the temperature of the surface of the living body and the temperature at a position away from the living body; a third step of calculating an observed value of the internal temperature of the living body based on the measurement results of the second step; a fourth step of calculating the magnitude of noise mixed into the observed value based on the observed value and the estimated value; a fifth step of calculating a gain for correcting the estimated value based on the magnitude of the noise; a sixth step of calculating the difference between the observed value and the estimated value as an estimated error; and a seventh step of updating the estimated value based on the reference temperature, the gain, and the estimated error, and is characterized by repeatedly performing the second to seventh steps. [Effects of the Invention]

[0018] According to the present invention, a sensor unit, a temperature calculation unit, a noise estimation unit, an estimation error calculation unit, and an estimation value update unit are provided, and the noise estimation unit estimates the magnitude of noise mixed into the observation value using the observed value of the internal temperature calculated by the temperature calculation unit and the previous estimated value, thereby making it possible to remove environmental noise and noise associated with the active body movements of the living body, and to accurately measure the internal temperature of the living body. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a block diagram showing the configuration of a temperature measuring device according to a first embodiment of the present invention. [Figure 2] FIG. 2 is a cross-sectional view of a sensor portion of a temperature measuring device according to a first embodiment of the present invention. [Figure 3] FIG. 3 is a flowchart illustrating the operation of the temperature measuring device according to the first embodiment of the present invention. [Figure 4] FIG. 4 is a diagram showing the temperature of the skin surface and the temperature above the sensor unit measured while a person is sleeping. [Figure 5]Figure 5 is a diagram showing an example of the observed value of deep body temperature calculated by the temperature calculation unit in the first embodiment of the present invention, the estimated value of deep body temperature calculated by the estimated value update unit, and the true deep body temperature measured by a tympanic thermometer. [Figure 6] FIG. 6 is a block diagram showing the configuration of a temperature measuring device according to a second embodiment of the present invention. [Figure 7] FIG. 7 is a flowchart illustrating the operation of the temperature measuring device according to the second embodiment of the present invention. [Figure 8] FIG. 8 is a block diagram showing the configuration of a temperature measuring device according to a third embodiment of the present invention. [Figure 9] FIG. 9 is a flowchart illustrating the operation of the temperature measuring device according to the third embodiment of the present invention. [Figure 10] FIG. 10 is a block diagram showing an example of the configuration of a computer that realizes the temperature measuring devices according to the first to third embodiments of the present invention. [Figure 11] FIG. 11 is a diagram showing a thermal equivalent circuit model of a living body and a sensor. [Figure 12] FIG. 12 shows an example of a deep body temperature estimated by a conventional method and a true deep body temperature measured by a tympanic thermometer while a person is sleeping. DETAILED DESCRIPTION OF THE INVENTION

[0020] [First Example] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Fig. 1 is a block diagram showing the configuration of a temperature measuring device according to a first embodiment of the present invention. The temperature measuring device includes a sensor unit 1 that measures the temperature of the skin surface of a living body and the temperature at a position away from the living body, a temperature calculation unit 2 that calculates an observed value of the deep body temperature (internal temperature) of the living body based on the measurement results of the sensor unit 1, a noise estimation unit 3 that calculates the magnitude of noise mixed into the observed value based on the observed value of the deep body temperature and the estimated value of the deep body temperature, an estimation error calculation unit 4 that calculates a gain for correcting the estimated value based on the magnitude of the noise and calculates the difference between the observed value and the estimated value as an estimation error, an estimate value update unit 5 that updates the estimated value of the deep body temperature based on a reference temperature measured by a thermometer at the start of measurement, the gain, and the estimation error, and an output unit 6 that outputs the estimation result by the estimate value update unit 5.

[0021] 2 is a cross-sectional view of the sensor unit 1. The sensor unit 1 includes a thermal resistor 10 arranged to be in contact with the living body 100, and a temperature sensor 12 arranged on the surface of the thermal resistor 10 that is in contact with the skin of the living body 100, which measures the temperature T skin The temperature sensor 11 measures the temperature T u and a temperature sensor 12 for measuring the temperature.

[0022] The sensor unit 1 is attached so that the thermal resistor 10 comes into contact with the skin of the living body 100. For example, it is desirable to attach the sensor unit 1 to the living body 100 using double-sided tape or silicone rubber that has excellent biocompatibility.

[0023] The temperature sensors 11 and 12 may be, for example, a thermistor, a thermocouple, a platinum resistor, or an IC (Integrated Circuit) temperature sensor. The thermal resistor 10 holds the temperature sensors 11 and 12 and acts as a resistor against heat flowing into the temperature sensors 11 and 12. If the distance between the temperature sensors 11 and 12 changes during temperature measurement, the deep body temperature T cbt Since an error occurs in the estimation of the temperature, the temperature sensors 11 and 12 are supported by a thermal resistor 10.

[0024] The material of the thermal resistor 10 is preferably a material with a thermal conductivity similar to that of the living body 100. The material of the thermal resistor 10 can be various resins including silicone-based resins.

[0025] 3 is a flowchart explaining the operation of the temperature measuring device of this embodiment. Initial parameters are set in advance in the temperature measuring device before starting measurement (step S100 in FIG. 3). The initial parameters include an initial value P0 of the variance of the estimation error, a constant A, and a variance Q of the system noise. The values ​​of these initial parameters are used to calculate the temperature T skin ,T u The optimal values ​​vary depending on the sampling rate or the update frequency of the estimated core body temperature. The values ​​of these initial parameters can be determined by prior experiments.

[0026] Next, the person (the person wearing the sensor unit 1 or a third party) who intends to measure the deep body temperature of the living body 100, at the start of the measurement, determines the axillary temperature of the living body 100 measured by an axillary thermometer, the sublingual temperature of the living body 100 measured by a sublingual thermometer, or the tympanic temperature of the living body 100 measured by a tympanic thermometer as the reference temperature T cbt _ ref (Step S101 in FIG. 3).

[0027] The noise estimation unit 3 calculates the reference temperature T cbt _ ref is the estimated core body temperature T cbt _ a is set as the initial value (step S102 in FIG. 3). T cbt _ a =T cbt _ ref ···(3)

[0028] The temperature sensor 11 detects the temperature T skin The temperature sensor 12 measures the temperature T u is measured (step S103 in FIG. 3).

[0029] Temperature calculation unit 2 calculates reference temperature T cbt _ ref and temperature T skin ,T u Based on this, a proportionality coefficient α relating to the thermal resistance of the living body 100 is calculated by equation (4) (step S104 in FIG. 3). α=(T cbt _ ref -T skin ) / (T skin -T u )···(4)

[0030] The temperature sensors 11 and 12 detect the temperature T skin ,T u The temperature calculation unit 2 calculates the proportionality coefficient α calculated in step S104 and the temperature T measured in step S105 again (step S105 in FIG. 3). skin ,T u Based on this, the observed value y of the core body temperature of the living body 100 is calculated by equation (5) (step S106 in FIG. 3). y=T skin +α(T skin -T u ) ···(5)

[0031] As shown in equation (5), T skin -T u Calculating the heat flux H in Eq. skin This is equivalent to calculating The estimation error calculation unit 4 updates the variance P of the estimation error (step S107 in FIG. 3). In the first update, the estimation error calculation unit 4 updates the variance P according to equation (6) using a preset initial parameter. P=P0+Q (6)

[0032] Next, the noise estimation unit 3 calculates the observed value y of the deep body temperature calculated by the temperature calculation unit 2 and the estimated value T cbt _ a Based on this, the magnitude w of the noise mixed into the observed value y is calculated (step S108 in FIG. 3). w=|y 2 -T cbt _ a 2 | (7)

[0033] The noise estimation unit 3 calculates the observed value y obtained at a certain point in time and the previous estimated value T cbt _ a For example, if we assume that the temperature change of the living body 100 is a very slow and steady phenomenon, the estimated value T of the deep body temperature at a certain time point (t-1) is expressed as follows, cbt _ a (t-1) is the estimated value T at the next time point t cbt _ a We can define a model that is the same as (t). T cbt _ a (t)=T cbt _ a (t-1) (8)

[0034] Alternatively, a moving average model or an autoregressive model may be used to explain the change in body temperature. The noise estimation unit 3 calculates the observed value y obtained at a certain point in time and the previous estimated value T cbt _ a Using and as input, the noise magnitude w is estimated using the function f. w=f(T cbt _ a ,y) (9)

[0035] In this embodiment, the noise magnitude w is calculated using, for example, equation (7). Next, the estimation error calculation unit 4 calculates the estimated value T of the core body temperature based on the variance P of the estimation error and the noise magnitude w calculated by the noise estimation unit 3. cbt _ a A gain K for correcting is calculated by equation (10) (step S109 in FIG. 3). K = P / (P + A × w) (10)

[0036] The gain K is the estimated value T cbt _ a The estimation error calculation unit 4 then updates the core body temperature observation value y and the estimated value T cbt _ a The difference between these is calculated as the estimation error e (step S110 in FIG. 3). e=yT cbt _ a ···(11)

[0037] The estimated value update unit 5 updates the reference temperature T cbt _ ref Based on the gain K and the estimation error e, the noise-removed core temperature estimate T cbt _ a By calculating the estimated value T cbt _ a is updated (step S111 in FIG. 3). T cbt _ a =T cbt _ ref +K×e (12)

[0038] The estimation error calculation unit 4 updates the variance P based on the current variance P and the gain K (step S112 in FIG. 3). Specifically, the estimation error calculation unit 4 multiplies (1-K) by the current variance P as shown in equation (13), and sets the new variance P to that value. P = (1 - K) P (13)

[0039] The output unit 6 outputs the estimated core body temperature T cbt _ a The external terminal displays the estimated value T cbt _ a are stored in memory and displayed.

[0040] The temperature measurement device performs the processes of steps S105 to S113 at regular time intervals. In the process of step S107 from the second time onwards, the estimated error calculation unit 4 updates the variance P using the current variance P and the value of the variance Q of the system noise set as an initial parameter. Specifically, the estimated error calculation unit 4 sets the new variance P to the value obtained by adding the variance Q of the system noise to the current variance P as shown in equation (14). P=P+Q (14)

[0041] Figure 4 shows the skin surface temperature T measured during sleep. skin and the temperature T at the top of the sensor part 1 u 4. The temperature T skin ,T u The temperature calculation unit 2 calculates the observed value y of the deep body temperature based on the above, and the estimated value update unit 5 calculates the estimated value T of the deep body temperature based on the above. cbt _ a and true core body temperature (reference temperature) T measured by a tympanic thermometer cbt _ ref This is shown in Figure 5.

[0042] According to Fig. 5, the reference temperature T cbt _ ref Estimated value T for cbt _ a The accuracy and tracking of the reference temperature T cbt _ ref It can be seen that the present embodiment provides an estimation result close to the above.

[0043] As described above, in this embodiment, the noise estimation unit 3 calculates the observed value y and the previous estimated value T cbt _ a By using this to estimate the magnitude of noise w mixed into the observed value y, it is possible to remove environmental noise and noise caused by the active body movement of the living body, and to measure the deep body temperature of the living body with high accuracy.

[0044] [Second Example] Next, a second embodiment of the present invention will be described. Fig. 6 is a block diagram showing the configuration of a temperature measuring device according to the second embodiment of the present invention. The temperature measuring device of this embodiment comprises a sensor unit 1, a temperature calculation unit 2, a noise estimation unit 3a, an estimation error calculation unit 4, an estimated value update unit 5, and an output unit 6. The configuration of the sensor unit 1 is the same as in the first embodiment.

[0045] 7 is a flowchart illustrating the operation of the temperature measurement device of this embodiment. As in the first embodiment, initial parameters (P0, A, Q) are set in advance in the temperature measurement device before starting measurement (step S100 in FIG. 7).

[0046] Next, a person who is going to measure the deep body temperature of the living body 100 should take the axillary temperature, sublingual temperature, or tympanic temperature of the living body 100 as a reference temperature T cbt _ ref (Step S101 in FIG. 7).

[0047] The noise estimation unit 3 calculates the reference temperature T cbt _ ref is the estimated core body temperature T cbt _ a is set as the initial value (step S102 in FIG. 7).

[0048] The temperature sensor 11 of the sensor unit 1 detects the temperature T skin The temperature sensor 12 measures the temperature T u is measured (Step S103 in FIG. 7).

[0049] Temperature calculation unit 2 calculates reference temperature T cbt _ ref and temperature T skin ,T u Based on this, the proportionality coefficient α is calculated using equation (4) (step S104 in FIG. 7).

[0050] The temperature sensors 11 and 12 detect the temperature T skin ,T u The temperature calculation unit 2 calculates the proportionality coefficient α calculated in step S104 and the temperature T measured in step S105 again (step S105 in FIG. 7). skin ,T u Based on this, the observed value y of the deep body temperature of the living body 100 is calculated by equation (5) (step S106 in FIG. 7).

[0051] The estimation error calculation unit 4 updates the variance P of the estimation error (step S107 in FIG. 7). In the first update, the estimation error calculation unit 4 updates the variance P according to equation (6) using a preset initial parameter.

[0052] Next, the noise estimation unit 3a calculates the observed value y of the deep body temperature calculated by the temperature calculation unit 2 and the estimated value T cbt _ a Based on this, the magnitude w of the noise mixed into the observed value y is calculated using equation (15) (step S108a in FIG. 7). w=exp|y 2 -T cbt _ a ×y| ···(15)

[0053] The estimation error calculation unit 4 calculates the gain K using equation (10) based on the variance P of the estimation error and the noise magnitude w calculated by the noise estimation unit 3a (step S109 in FIG. 7). Next, the estimation error calculation unit 4 calculates the gain K using equation (11) based on the observed value y of the core body temperature and the estimated value T cbt _ a The difference between these is calculated as the estimated error e (step S110 in FIG. 7).

[0054] The estimated value update unit 5 updates the reference temperature T cbt _ ref Based on the gain K and the estimation error e, the estimated core body temperature T is calculated as shown in equation (12). cbt _ a is updated (step S111 in FIG. 7).

[0055] The estimation error calculation unit 4 updates the variance P using equation (13) based on the current variance P and the gain K (step S112 in FIG. 7).

[0056] The output unit 6 outputs the estimated core body temperature T cbt _ a is displayed or transmitted to an external terminal (step S113 in FIG. 7).

[0057] The temperature measurement device performs the processes of steps S105 to S107, S108a, and S109 to S113 at regular time intervals. In the process of step S107 from the second time onwards, the estimation error calculation unit 4 updates the variance P according to equation (14) using the current variance P and the value of the variance Q of the system noise. In this way, the present embodiment can achieve the same effects as the first embodiment.

[0058] [Third Example] Next, a third embodiment of the present invention will be described. Fig. 8 is a block diagram showing the configuration of a temperature measuring device according to the third embodiment of the present invention. The temperature measuring device of this embodiment comprises a sensor unit 1, a temperature calculation unit 2, a noise estimation unit 3b, an estimation error calculation unit 4, an estimated value update unit 5, and an output unit 6. The configuration of the sensor unit 1 is the same as in the first embodiment.

[0059] 9 is a flowchart illustrating the operation of the temperature measurement device of this embodiment. As in the first embodiment, initial parameters (P0, A, Q) are set in advance in the temperature measurement device before measurement begins (step S100 in FIG. 9).

[0060] Next, a person who is going to measure the deep body temperature of the living body 100 should take the axillary temperature, sublingual temperature, or tympanic temperature of the living body 100 as a reference temperature T cbt _ ref (Step S101 in FIG. 9).

[0061] The noise estimation unit 3 calculates the reference temperature T cbt _ ref is the estimated core body temperature T cbt _ a is set as the initial value (step S102 in FIG. 9).

[0062] The temperature sensor 11 of the sensor unit 1 detects the temperature T skin The temperature sensor 12 measures the temperature T u is measured (step S103 in FIG. 9).

[0063] Temperature calculation unit 2 calculates reference temperature T cbt _ ref and temperature T skin ,T u Based on this, the proportionality coefficient α is calculated by equation (4) (step S104 in FIG. 9).

[0064] The temperature sensors 11 and 12 detect the temperature T skin ,T uThe temperature calculation unit 2 measures the proportionality coefficient α calculated in step S104 and the temperature T measured in step S105 again (step S105 in FIG. 9). skin ,T u Based on this, the observed value y of the deep body temperature of the living body 100 is calculated by equation (5) (step S106 in FIG. 9).

[0065] The estimation error calculation unit 4 updates the variance P of the estimation error (step S107 in FIG. 9). In the first update, the estimation error calculation unit 4 updates the variance P according to equation (6) using a preset initial parameter.

[0066] Next, the noise estimation unit 3b calculates the observed value y of the deep body temperature calculated by the temperature calculation unit 2 and the estimated value T cbt _ a Based on this, the magnitude w of the noise mixed into the observed value y is calculated using equation (16) (step S108b in FIG. 9). w=|y 2 -T cbt _ a ×y| ···(16)

[0067] The estimation error calculation unit 4 calculates the gain K using equation (10) based on the variance P of the estimation error and the noise magnitude w calculated by the noise estimation unit 3b (step S109 in FIG. 9). Next, the estimation error calculation unit 4 calculates the gain K using equation (11) based on the observed value y of the core body temperature and the estimated value T cbt _ a The difference between these is calculated as the estimated error e (step S110 in FIG. 9).

[0068] The estimated value update unit 5 updates the reference temperature T cbt _ ref Based on the gain K and the estimation error e, the estimated core body temperature T is calculated as shown in equation (12). cbt _ a is updated (step S111 in FIG. 9).

[0069] The estimation error calculation unit 4 updates the variance P using equation (13) based on the current variance P and the gain K (step S112 in FIG. 9).

[0070] The output unit 6 outputs the estimated core body temperature T cbt _ a is displayed or transmitted to an external terminal (step S113 in FIG. 9).

[0071] The temperature measurement device performs the processes of steps S105 to S107, S108b, and S109 to S113 at regular time intervals. In the process of step S107 from the second time onwards, the estimation error calculation unit 4 updates the variance P according to equation (14) using the current variance P and the value of the variance Q of the system noise. In this way, the present embodiment can achieve the same effects as the first embodiment.

[0072] The temperature calculation unit 2, noise estimation units 3, 3a, 3b, estimation error calculation unit 4, estimated value update unit 5, and output unit 6 of the temperature measurement device described in the first to third embodiments can be realized by a computer equipped with a CPU (Central Processing Unit), a storage device, and an interface, and a program that controls these hardware resources. An example configuration of this computer is shown in Figure 10.

[0073] The computer includes a CPU 200, a storage device 201, and an interface device (I / F) 202. The I / F 202 is connected to the temperature sensors 11 and 12, the hardware of the output unit 6, and the like.

[0074] In such a computer, a temperature measurement program for realizing the temperature measurement method of the present invention is provided in a state recorded on a recording medium such as a flexible disk, CD-ROM, DVD-ROM, or memory card. The CPU 200 reads the program from the recording medium, writes it into the storage device 201, and executes the processes described in the first to third embodiments in accordance with the program stored in the storage device 201. The temperature measurement program can also be provided via a network.

[0075] Some or all of the above embodiments can be described as, but are not limited to, the following supplementary notes.

[0076] (Supplementary Note 1) The temperature measuring device of the present invention comprises a sensor unit configured to measure the temperature of the surface of a living body and the temperature at a position away from the living body; a temperature calculation unit configured to calculate an observed value of the internal temperature of the living body based on the measurement results of the sensor unit; a noise estimation unit configured to use the internal temperature measured by a thermometer at the start of measurement as a reference temperature and the reference temperature as an initial value of an estimated value of the internal temperature, and to calculate the magnitude of noise mixed into the observed value based on the observed value and the estimated value; an estimation error calculation unit configured to calculate a gain for correcting the estimated value based on the magnitude of the noise and calculate the difference between the observed value and the estimated value as an estimation error; and an estimation value update unit configured to update the estimated value based on the reference temperature, the gain, and the estimation error, and is characterized in that the temperature measurement by the sensor unit, calculation of the observed value, the magnitude of the noise, the gain, and the estimation error, and updating the estimated value are repeatedly performed.

[0077] (Supplementary Note 2) In the temperature measurement device according to Supplementary Note 1, the noise estimation unit estimates the observed value as y and the estimated value as T cbt _ a When the magnitude of the noise is |y 2 -T cbt _ a 2 |Calculated by

[0078] (Supplementary Note 3) In the temperature measurement device according to Supplementary Note 1, the noise estimation unit estimates the observed value as y and the estimated value as T cbt _ a When the magnitude of the noise is exp|y 2 -T cbt _ a Calculated by |×y|.

[0079] (Supplementary Note 4) In the temperature measurement device according to Supplementary Note 1, the noise estimation unit estimates the observed value as y and the estimated value as T cbt _ a When the magnitude of the noise is |y 2 -T cbt _ aCalculated by |×y|.

[0080] (Supplementary Note 5) In the temperature measurement device according to any one of Supplementary Notes 1 to 4, the estimated value update unit updates the reference temperature by T cbt _ ref , the gain is K, the estimation error is e, and the estimated value is T cbt _ ref Calculated by +K×e.

[0081] (Appendix 6) In the temperature measuring device described in Appendix 1, the temperature calculation unit calculates a proportionality coefficient related to the thermal resistance of the living body based on the reference temperature and the measurement result of the sensor unit at the start of measurement, and calculates the observed value based on the measurement result of the sensor unit and the proportionality coefficient after the start of measurement.

[0082] (Appendix 7) The temperature measurement method of the present invention includes a first step of using the internal temperature of a living body measured by a thermometer at the start of measurement as a reference temperature and setting the reference temperature as an initial value of an estimated value of the internal temperature; a second step of measuring the temperature of the surface of the living body and the temperature at a position away from the living body; a third step of calculating an observed value of the internal temperature of the living body based on the measurement results of the second step; a fourth step of calculating the magnitude of noise mixed into the observed value based on the observed value and the estimated value; a fifth step of calculating a gain for correcting the estimated value based on the magnitude of the noise; a sixth step of calculating the difference between the observed value and the estimated value as an estimated error; and a seventh step of updating the estimated value based on the reference temperature, the gain, and the estimated error, and is characterized by repeatedly performing the second to seventh steps.

[0083] (Supplementary Note 8) A temperature measurement program of the present invention is characterized by causing a computer to execute each step described in Supplementary Note 7. [Industrial Applicability]

[0084] The present invention can be applied to a technique for non-invasively measuring the internal temperature of a living body. [Explanation of symbols]

[0085] 1...sensor section, 2...temperature calculation section, 3, 3a, 3b...noise estimation section, 4...estimation error calculation section, 5...estimated value update section, 6...output section, 10...thermal resistor, 11, 12...temperature sensor.

Claims

1. a sensor unit configured to measure the temperature of the surface of a living body and the temperature of a position away from the living body; a temperature calculation unit configured to calculate an observed value of the internal temperature of the living body based on the measurement result of the sensor unit; a noise estimation unit configured to use the internal temperature measured by the thermometer at the start of measurement as a reference temperature, and to calculate the magnitude of noise mixed into the observed value based on the estimated value, with the reference temperature being used as an initial value for the estimated value of the internal temperature; and an estimation error calculation unit configured to calculate a gain for correcting the estimated value based on the magnitude of the noise, and to calculate a difference between the observed value and the estimated value as an estimation error; an estimate update unit configured to update the estimate based on the reference temperature, the gain, and the estimation error; A temperature measuring device characterized by repeatedly measuring a temperature by the sensor unit, calculating the observed value, the magnitude of the noise, the gain, and the estimated error, and updating the estimated value.

2. 2. The temperature measuring device according to claim 1, The noise estimation unit estimates the observed value as y and the estimated value as T ｃｂｔ _ ａ When the magnitude of the noise is |y ２ -T ｃｂｔ _ ａ ２ A temperature measuring device characterized by calculating the temperature by |.

3. 2. The temperature measuring device according to claim 1, The noise estimation unit estimates the observed value as y and the estimated value as T ｃｂｔ _ ａ When the magnitude of the noise is exp|y ２ -T ｃｂｔ _ ａ A temperature measuring device characterized by calculating the temperature by the following formula:

4. 2. The temperature measuring device according to claim 1, The noise estimation unit estimates the observed value as y and the estimated value as T ｃｂｔ _ ａ When the magnitude of the noise is |y ２ -T ｃｂｔ _ ａ A temperature measuring device characterized by calculating the temperature by the following formula:

5. 5. The temperature measuring device according to claim 1, The estimated value update unit updates the reference temperature by T ｃｂｔ _ ｒｅｆ , the gain is K, the estimation error is e, and the estimated value is T ｃｂｔ _ ｒｅｆ +K×e.

6. 2. The temperature measuring device according to claim 1, A temperature measuring device characterized in that the temperature calculation unit calculates a proportionality coefficient related to the thermal resistance of the living body based on the reference temperature and the measurement results of the sensor unit at the start of measurement, and calculates the observed value based on the measurement results of the sensor unit and the proportionality coefficient after the start of measurement.

7. a first step of setting an internal temperature of the living body measured by the thermometer at the start of measurement as a reference temperature and setting the reference temperature as an initial value of an estimated value of the internal temperature; a second step of measuring the temperature of the surface of the living body and the temperature at a position away from the living body; A third step of calculating an observed value of the internal temperature of the living body based on the measurement result of the second step; a fourth step of calculating the magnitude of noise mixed into the observed value based on the observed value and the estimated value; a fifth step of calculating a gain for correcting the estimated value based on the magnitude of the noise; a sixth step of calculating a difference between the observed value and the estimated value as an estimation error; a seventh step of updating the estimate based on the reference temperature, the gain, and the estimation error; A temperature measurement method comprising repeatedly performing the second to seventh steps.

8. A temperature measurement program for causing a computer to execute each step of claim 7.

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