JP6140562B2 - Respiration measurement method and respiration measurement device - Google Patents

Description

  The present invention relates to a respiratory measurement method and a respiratory measurement device. More specifically, the present invention relates to a respiration measurement method and a respiration measurement apparatus capable of obtaining a change in lung volume associated with lung respiration of a subject having a lung as a test subject.

As for this type of respiration measurement method and respiration measurement apparatus, for example, a technique disclosed in Patent Document 1 below is known. In this technique, a wiring loop is provided so as to surround the chest and abdomen of the subject, and a signal proportional to the lung volume of the subject is obtained from the measurement result of the self-inductance of each wiring loop. According to this technique, the amount of change in the lung volume of the subject can be easily measured without interfering with the exercise of the subject.
Patent Document 1 describes a technique for acquiring parameters reflecting the shape of a subject's torso in advance during respiration measurement. According to this technique, by using the above parameters, it is possible to minimize the deviation of the measurement result generated according to the shape of the torso of the subject.

Japanese Patent No. 4832289

By the way, when the subject exercises, the posture of the subject is changed by this exercise. Further, when the subject eats the meal, the state of the subject is changed from a hungry and depressed stomach to a full and stomached condition. Here, when the state of the subject is variously changed for various reasons as described above, it is conventionally known that the shape and operation of the body of the subject are variously changed according to the change of the state. . Here, in the conventional technique disclosed in Patent Document 1, in order to reduce the deviation of the measurement result caused by the shape of the torso of the subject, the parameter reflecting this shape is acquired for each shape of the torso of the subject. There is a need to do. For this reason, the above conventional technique has a problem that it is difficult to reduce the deviation of the measurement result in the respiration measurement of the subject corresponding to each of the conditions of the subject that are variously changed due to reasons such as exercise. there were.
The present invention has been devised to solve the above problems. In other words, the problem to be solved by the present invention is variously changed by enabling the deviation of the measurement result in the respiration measurement of the subject to be reduced using only one or a set of parameters regardless of the state of the subject. It is easily realized to reduce the deviation of the measurement result in the respiration measurement of the subject corresponding to each state of the subject.

In order to solve the above problems, the respiration measurement method and respiration measurement apparatus of the present invention take the following means.
First, in the first invention, a living body having a lung is used as a subject, and a change in lung volume associated with lung breathing of the subject is determined as a region length that is a length in a predetermined direction at a predetermined region on the body surface of the subject. This is a respiration measurement method that can be obtained by measuring the length over time. In this respiration measurement method, when the subject is in a predetermined first state, the amount of change in the lung volume of the subject is measured by first measurement means that obtains time-series data obtained by measuring the length of the region of the subject over time. A first measurement method that performs measurement in parallel by two measurement methods: a first measurement method that performs measurement and a second measurement method that performs measurement using a second measurement unit that has a higher measurement accuracy of the amount of change in lung volume than the first measurement unit. The change amount of the lung volume of the subject measured by the first measurement method in the first measurement step and the change amount of the lung volume of the subject measured by the second measurement method in the first measurement step. A calibration step for deriving a calibration parameter that is one or a set of parameters representing how to deviate from the reference, and when the subject is in a second state, which is any one state A second measurement step for measuring the length of the region of the first time by the first measurement means, and a second representative value representing a representative value of the time series data of the length of the portion measured by the first measurement means in the second measurement step A function dependency relationship whose value is dependent on a first representative value that is a representative value of the time-series data of the part length measured by the first measuring means in the first measurement step is shown in the second measurement step. A virtual time-series data creating step for creating virtual time-series data, which is time-series data applied to each data constituting the time-series data of the part length measured by one measuring means, and the subject's based on the virtual time-series data Deriving the amount of change in lung volume, applying the parameters of calibration performed in the calibration step to the derived amount of change in lung volume, and applying the parameters of the calibration to the lung volume The amount of variation, and an output step of outputting regarded as lung volume variation amount when the subject is in the second state.
The present inventor measures the variation in the length of the site associated with each subject's breathing over time while continuing various states for a plurality of subjects, and for each measurement result in each of the continued states, The calibration parameters were derived based on the measurement results of the length of each subject in the standing position of the subject. The inventor has found that the calibration parameters are hardly changed when one state is continued in the subject, and has reached the present invention.
That is, according to the first aspect, the measurement result of the part length in the second state, which is any one of the states that the subject can take, is the representative value of the part length of the subject in the predetermined first state. This corresponds to the measurement result of the part length in the first state, using a functional dependency relationship that represents the relationship between the first representative value that is and the second representative value that is the representative value of the part length of the subject in the second state. Convert to data. Then, by applying the calibration parameter in the first state to the fluctuation amount of the lung volume of the subject derived from the converted data, the lung volume of the subject in the second state in which the deviation of the measurement result is reduced. Output as a variable amount. For this reason, according to the first aspect of the present invention, the deviation of the measurement result of the fluctuation amount relative to the fluctuation amount of the lung volume of the subject in any state that the subject can take is one or one in the predetermined state. This can be reduced using only a set of calibration parameters. In other words, according to the first aspect, it is possible to reduce the deviation of the measurement result in the respiration measurement of the subject using only one or one set of parameters regardless of the state of the subject. Accordingly, it is possible to easily realize a reduction in the deviation of the measurement result in the amount of change in the lung volume of the subject corresponding to each of the various states of the subject that are variously changed.

Next, the second invention is the first invention described above, wherein in the virtual time series data creation step, the function dependency is a proportional relationship in which the ratio between the second representative value and the first representative value is a proportional constant. As described above, virtual time series data is created.
According to the second aspect, virtual time series data can be created by a simple calculation algorithm. Thereby, the information processing amount and information processing time in the respiration measurement method of the present invention can be reduced.

Further, the third invention is the first or second invention described above, wherein in the second measurement step, the state of the subject is measured over time in parallel with the change in the lung volume of the subject, and the virtual time In the series data creation step, the time series data of the time range in which no significant change was observed in the condition of the subject in the second measurement step from the time series data of the part length measured by the first measurement means in the second measurement step The second representative value is derived by regarding the extracted time-series data as the entire time-series data of the part length measured by the first measuring means in the second measurement step.
If a significant variation in the subject's condition is measured in one state, the second state, some event has occurred that prevents accurate measurement in the time range in which this significant variation was measured. Here, according to the third aspect of the present invention, a time range in which an event that prevents accurate measurement is not observed by measuring the state of the subject over time is specified, and the second representative is obtained from the time-series data in this time range. Deriving a value. As a result, it is possible to eliminate the phenomenon that prevents the accurate measurement from degrading the accuracy of the functional dependency relationship and deteriorating the accuracy of the entire measurement result in the respiration measurement of the subject.

Furthermore, the fourth aspect of the present invention relates to a living body having a lung as a subject, and the variation in lung volume associated with the subject's lung respiration is a length in a predetermined direction at a predetermined portion on the body surface of the subject. It is a respiration measuring device that can be obtained by measuring the length over time. The respiration measuring apparatus measures a length of a part of a subject over time, first measurement means for obtaining a fluctuation amount of the lung volume of the subject from time-series data of the measured part length, and the subject The time-series data of the part length measured by the first measuring means when in one state and the amount of change in the lung volume of the subject obtained from the time-series data of the part length are determined by the subject in the first state. 1 represents how the displacement of the lung volume of the subject measured by the second measuring means is higher than the first measuring means when the measurement accuracy is higher than the first measuring means. Alternatively, when the length of the part measured by the first measuring means when the subject is in the second state, which is one state, and the first recording unit in which a calibration parameter that is a set of parameters is recorded A second recording unit for recording the series data; The second representative value that is the representative value of the part length time-series data recorded in the recording unit is dependent on the first representative value that is the representative value of the part length time-series data recorded in the first recording part. Virtual time-series data creating means for creating virtual time-series data that is time-series data obtained by applying the function dependency relationship, which is the relationship to be performed, to each data constituting the time-series data of the part length recorded in the second recording unit And calculating the volume of the subject's lung volume based on the virtual time series data, applying the calibration parameter recorded in the first recording unit to the derived volume of lung volume, Output means for outputting the amount of change in lung volume to which the parameter is applied as the amount of change in lung volume when the subject is in the second state.
According to the fourth invention, as in the first invention described above, in the respiration measurement device, the measurement result of the fluctuation amount with respect to the fluctuation amount of the lung volume of the subject in any state that the subject can take. It is possible to reduce the deviation using only one or a set of calibration parameters in a predetermined state. In other words, according to the fourth aspect of the present invention, in the respiration measuring device, it is possible to reduce the deviation of the measurement result in the respiration measurement of the subject using only one or a set of parameters regardless of the state of the subject. It becomes. Accordingly, it is possible to easily provide a respiratory measurement device in which the deviation of the measurement result in the fluctuation amount of the lung volume of the subject is reduced corresponding to each state of the subject that is variously changed.

Further, the fifth invention is the above-described fourth invention, wherein the virtual time series data creating means has a proportional relationship in which the function dependency is a ratio constant between the second representative value and the first representative value. As described above, virtual time series data is created.
According to the fifth aspect, similar to the second aspect described above, in the respiratory measurement device of the present invention, virtual time series data can be created by a simple calculation algorithm. Thereby, the amount of information processing and the information processing time can be reduced in the respiration measuring device of the present invention.

Further, the sixth invention is the fourth or fifth invention described above, wherein the third measuring means measures the condition of the subject over time when the subject is in the second condition, and the third measuring means. And a third recording unit that records time series data indicating whether or not a significant variation was observed in the state of the subject measured by the virtual time series data creating means, the part recorded in the second recording unit Extract time-series data from the time-series data recorded in the third recording unit from the time-series data of the length, using the time-series data recorded in the third recording unit. The second representative value is derived by regarding the data as the entire time-series data of the part length recorded in the second recording unit.
According to the sixth aspect, as in the third aspect described above, in the respiratory measurement device, a time range in which an event that prevents accurate measurement is not observed by measuring the state of the subject over time is specified. The second representative value can be derived from the time series data in this time range. As a result, it is possible to provide a respiratory measurement device in which the event that prevents the above-described accurate measurement does not deteriorate the accuracy of the function dependency relationship and deteriorate the accuracy of the entire measurement result of the subject's respiratory measurement.

It is explanatory drawing showing the state of the 2nd measurement step in the respiration measuring method of this invention. It is explanatory drawing showing the state of the 1st measurement step in the respiration measuring method of this invention. It is a block diagram showing the structure of the principal part of the respiration measuring apparatus concerning one Embodiment of this invention. a is a box-and-whisker diagram showing calibration parameters derived on the basis of the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. a is a box-and-whisker diagram showing calibration parameters derived on the basis of the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. b is a box-and-whisker diagram showing calibration parameters derived based on the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. b is a box-and-whisker diagram showing calibration parameters derived based on the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. c is a box-and-whisker diagram showing calibration parameters derived on the basis of the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. c is a box-and-whisker diagram showing calibration parameters derived on the basis of the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. d is a box-and-whisker diagram showing calibration parameters derived on the basis of the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. d is a box-and-whisker diagram showing calibration parameters derived on the basis of the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. e is a box-and-whisker chart showing calibration parameters derived on the basis of the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. e is a box-and-whisker chart showing calibration parameters derived on the basis of the measurement result of the respiration measurement in the standing position in the respiration measurement of the subject. It is a graph showing the measurement result of the respiration measured by the 2nd measurement means in the standing state of A subject. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measurement means in the standing state of A subject. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in the sitting state of A subject. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measuring means in the sitting state of A subject. A is a graph obtained by converting the respiration measurement result measured by the first measuring means in the sitting position of the subject A into the respiration measurement result in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a sitting state to the measurement result of respiration measured by the 1st measurement means in the sitting state of A subject. It is a graph showing the measurement result of the respiration measured by the 2nd measurement means in the test subject's forward leaning position. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of the respiration measured by the 1st measurement means in the test subject's A leaning position. A is a graph obtained by converting the measurement result of respiration measured by the first measuring means in the forward tilted position of the subject A into the measurement result of respiration in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a forward leaning seat state to the measurement result of respiration measured by the 1st measurement means in the forward leaning state of A subject. It is a graph showing the measurement result of the respiration measured by the 2nd measurement means in the test subject's back tilting position. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measurement means in the back tilt position of A subject. It is the graph which converted the measurement result of the respiration measured by the 1st measurement means in the back tilt position of A subject into the measurement result of respiration in the standing position, and applied the calibration parameter in the standing position. It is the graph which applied the parameter of the calibration in a back tilt position to the measurement result of respiration measured by the 1st measurement means in the back tilt position of A subject. It is a graph showing the measurement result of the respiration measured by the 2nd measurement means in the walking state of A subject. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measurement means in the walking state of A subject. It is the graph which converted the measurement result of the respiration measured by the 1st measurement means in the walking state of A subject into the respiration measurement result in the standing state, and applied the calibration parameter in the standing state. It is the graph which applied the parameter of the calibration in a walk state to the measurement result of respiration measured by the 1st measurement means in the walk state of A subject. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in the test subject's standing position. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measurement means in the standing state of B subject. It is a graph showing the measurement result of the respiration measured by the 2nd measurement means in B subject's sitting state. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measurement means in the sitting state of B subject. B is a graph obtained by converting the respiration measurement result measured by the first measuring means in the sitting position of the subject B into the respiration measurement result in the standing position and applying the calibration parameters in the standing position. B is a graph in which calibration parameters in the sitting position are applied to the respiration measurement results measured by the first measuring means in the sitting position of the subject B. It is the graph showing the measurement result of the respiration measured by the 2nd measuring means in the test subject's B leaning position. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measurement means in the forward leaning position of B subject. B is a graph obtained by converting the measurement result of respiration measured by the first measuring means in the forward tilted position of the subject B into the measurement result of respiration in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a forward leaning position to the measurement result of respiration measured by the 1st measurement means in the forward leaning state of B subject. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in the back tilting position of B subject. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measurement means in the back tilting position of B subject. B is a graph obtained by converting the measurement result of respiration measured by the first measuring means in the backward tilted position of the subject B into the measurement result of respiration in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a back tilt position to the measurement result of respiration measured by the 1st measurement means in the back tilt position of B subject. It is a graph showing the measurement result of the respiration measured by the 2nd measuring means in the test subject's B walk state. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measurement means in the walking state of B subject. B is a graph obtained by converting the respiration measurement result measured by the first measuring means in the walking state of the subject B into the respiration measurement result in the standing state and applying the calibration parameters in the standing state. It is the graph which applied the parameter of the calibration in a walk state to the measurement result of respiration measured by the 1st measurement means in the walk state of B subject. It is a graph showing the measurement result of respiration measured by the 2nd measurement means in the standing state of C subject. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measurement means in the standing state of C subject. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in C subject's sitting state. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measurement means in the sitting position of C subject. C is a graph obtained by converting the respiration measurement result measured by the first measurement means in the sitting state of the C subject into the respiration measurement result in the standing state and applying the calibration parameters in the standing state. It is the graph which applied the parameter of the calibration in a sitting position to the measurement result of respiration measured by the 1st measurement means in the sitting position of C subject. It is a graph showing the measurement result of the respiration measured by the 2nd measurement means in the C subject's forward leaning position state. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measuring means in the C subject's leaning position. C is a graph obtained by converting the measurement result of respiration measured by the first measurement means in the forward tilted position of the C subject into the measurement result of respiration in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a forward leaning position to the measurement result of respiration measured by the 1st measurement means in the forward leaning state of C subject. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in C subject's back tilt position. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measuring means in the back tilt position of C subject. C is a graph obtained by converting the measurement result of respiration measured by the first measuring means in the backward tilted position of the C subject into the measurement result of respiration in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a back tilt position to the measurement result of respiration measured by the 1st measuring means in the back tilt position of C subject. It is a graph showing the measurement result of the respiration measured by the 2nd measurement means in the walking state of C subject. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measurement means in the walking state of C subject. C is a graph obtained by converting the respiration measurement result measured by the first measuring means in the walking state of the C subject into the respiration measurement result in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a walk state to the measurement result of respiration measured by the 1st measurement means in the walk state of C subject. It is the graph showing the measurement result of the respiration measured by the 2nd measuring means in the standing state of D subject. D is a graph in which calibration parameters in the standing state are applied to the respiration measurement results measured by the first measuring means in the standing state of the subject D. It is the graph showing the measurement result of the respiration measured by the 2nd measuring means in the sitting state of D subject. D is a graph in which calibration parameters in the standing position are applied to the respiration measurement results measured by the first measuring means in the sitting position of the subject D. D is a graph obtained by converting the respiration measurement result measured by the first measuring means in the sitting position of the subject to the respiration measurement result in the standing position and applying the calibration parameters in the standing position. D is a graph in which calibration parameters in the sitting position are applied to the respiration measurement results measured by the first measuring means in the sitting position of the subject D. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in the test subject's leaning position of D subject. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of the respiration measured by the 1st measurement means in the test subject's forward leaning position. D is a graph obtained by converting the measurement result of respiration measured by the first measuring means in the forward tilted sitting state of the subject to the measurement result of respiration in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a forward leaning position to the measurement result of respiration measured by the 1st measuring means in the forward leaning state of D subject. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in the back tilting position of D subject. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measurement means in the back tilting sitting state of D subject. D is a graph obtained by converting the measurement result of respiration measured by the first measuring means in the backward tilted position of the subject D into the measurement result of respiration in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a back tilt position to the measurement result of respiration measured by the 1st measurement means in the back tilt position of D subject. It is the graph showing the measurement result of respiration measured by the 2nd measurement means in the walking state of D subject. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measurement means in the walking state of D subject. D is a graph obtained by converting the respiration measurement result measured by the first measurement means in the walking state of the subject to the respiration measurement result in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a walk state to the measurement result of respiration measured by the 1st measurement means in the walk state of D subject. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in the standing state of E subject. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measuring means in the standing state of E subject. It is the graph showing the measurement result of the respiration measured by the 2nd measuring means in the sitting state of E subject. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measuring means in the sitting state of E subject. E is a graph obtained by converting the respiration measurement result measured by the first measurement means in the sitting position of the subject to the respiration measurement result in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a sitting state to the measurement result of respiration measured by the 1st measurement means in the sitting state of E subject. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in the test subject's forward leaning position. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of the respiration measured by the 1st measurement means in the forward leaning state of E subject. E is a graph in which the measurement result of respiration measured by the first measuring means in the forward tilted position of the subject is converted into the respiration measurement result in the standing position, and the calibration parameters in the standing position are applied. It is the graph which applied the parameter of the calibration in a forward leaning position to the measurement result of respiration measured by the 1st measuring means in the forward leaning state of E subject. It is the graph showing the measurement result of the respiration measured by the 2nd measuring means in the back tilting position of E subject. It is the graph which applied the parameter of the calibration in a standing position to the measurement result of respiration measured by the 1st measurement means in the back tilting position of E subject. E is a graph obtained by converting the measurement result of respiration measured by the first measuring means in the backward tilted position of the subject E into the measurement result of respiration in the standing position and applying the calibration parameters in the standing position. It is the graph which applied the parameter of the calibration in a back tilt position to the measurement result of respiration measured by the 1st measurement means in the back tilt position of E subject. It is the graph showing the measurement result of the respiration measured by the 2nd measurement means in the walking state of E subject. It is the graph which applied the parameter of the calibration in a standing state to the measurement result of respiration measured by the 1st measurement means in the walking state of E subject. E is a graph obtained by converting the respiration measurement result measured by the first measurement means in the walking state of the subject to the respiration measurement result in the standing state and applying the calibration parameters in the standing state. It is the graph which applied the parameter of the calibration in a walk state to the measurement result of respiration measured by the 1st measurement means in the walk state of E subject. FIG. 32 is a bar graph showing the estimation error included in each graph of FIGS. 14 to 31 in comparison. FIG. 50 is a bar graph showing the estimation error included in each graph of FIGS. 32 to 49 in comparison. 68 is a bar graph showing the estimation errors included in the graphs of FIGS. 50 to 67 in comparison with each other. FIG. 96 is a bar graph showing the estimation errors included in the graphs of FIGS. FIG. 104 is a bar graph showing the estimation error included in each graph of FIGS. 96 to 103 in comparison.

EMBODIMENT OF THE INVENTION Below, the form for implementing this invention is demonstrated using drawing. As shown in FIG. 1, a respiratory measurement device 10 according to an embodiment of the present invention uses a human (that is, “an organism having a lung” in the present invention) as a subject 90 to perform breathing in the daily life of the subject 90. This is a wearable respiratory measurement device for measuring without placing a burden on the subject 90 (that is, in a minimally invasive state). The respiration measurement device 10 includes first measurement means 11 controlled by a control computer 12 so that the respiration of the subject 90 can be measured by the first measurement means 11.
The respiration measurement method according to the embodiment of the present invention is a respiration measurement apparatus in which a respiration measurement program causes the control computer 12 of the respiration measurement apparatus 10 to function as control means for executing each step of the present invention. 10 is a method of measuring the respiration of the subject 90. Here, the respiration measurement program is recorded in advance in a computer-readable manner in a recording device (not shown) of the control computer 12.

In addition, in this specification, the detailed description is abbreviate | omitted about incidental structures, such as a cable and a radio | wireless communication apparatus which implement | achieve the exchange of the information between each structure among each structure of the respiration measuring apparatus 10. FIG.
Further, among the steps of the respiration measurement method, it is incidental and conventionally used, such as an error detection step for detecting an error included in input or calculated data and outputting an error message. Detailed description of the steps is omitted. The function used in the respiration measurement method is represented by adding “<>”, and the function parameters are included in the “<>”.

As shown in FIGS. 1 and 2, the first measuring means 11 has a configuration in which tensile deformation detection cloths 11 </ b> A and 11 </ b> B are sewn on a clothing 11 </ b> C (T-shirt in this embodiment) worn on the body of the subject 90. It has become. The tensile deformation detection cloth 11 </ b> A is arranged corresponding to the umbilicus in the abdomen of the subject 90, and detects circumferential tensile deformation passing through the umbilicus in the abdomen of the subject 90 as needed. The tensile deformation detection cloth 11 </ b> B is disposed corresponding to the xiphoid process in the chest of the subject 90, and detects circumferential tensile deformation passing through the xiphoid process in the subject 90 's chest as needed.
Here, each of the tensile deformation detection cloths 11A and 11B can be expanded and contracted in the circumferential direction of the circumferential length in which the tensile deformation should be detected by a cloth structure including a plurality of conductive yarns (not shown) insulated from each other. It becomes the composition which was made. The tensile deformation detection cloths 11A and 11B detect the tensile deformation in the circumferential direction based on a change in capacitance between the conductive yarns resulting from a change in the distance between adjacent conductive yarns due to the expansion and contraction. It is supposed to be.

Based on the detection results of the respective tensile deformation detection cloths 11 </ b> A and 11 </ b> B, the first measurement unit 11 calculates the circumference passing through the navel in the abdomen of the subject 90 (hereinafter also referred to as X) and the xiphoid process in the chest of the subject 90. The circumferential length (hereinafter also referred to as Y) is measured over time. Here, said X and said Y are respectively corresponded to the "part length" in this invention.
Then, as shown in FIG. 3, the first measuring means 11 performs the data processing equivalent to the following (Equation 1) on the X and Y measured over time, thereby breathing and ventilating the subject 90. A quantity (hereinafter also referred to as V) is derived, and this V is transmitted to the control computer 12 over time together with X and Y. In other words, the first measuring means 11 measures the respiratory ventilation volume V, which is the amount of change in the lung volume of the subject 90, as time series data from the time series data of the measured site lengths X and Y. The respiratory ventilation volume V is output to the control computer 12 together with the part lengths X and Y.

ここで、Ｚ_０、Ｚ_１、Ｚ_２、Ｚ_３は、被験者９０の各状態における校正のパラメータが適用されることで随時変更される係数である。なお、上記（式１）は、本発明者が前方ステップワイズ法に基づいたフィッティングの試行錯誤を繰り返すことによって、本発明者が独自に見出した呼吸換気量の計算式である。

Here, Z ₀ , Z ₁ , Z ₂ , and Z ₃ are coefficients that are changed as needed by applying calibration parameters in each state of the subject 90. In addition, the above (Formula 1) is a formula for calculating the respiratory ventilation, which the inventor originally found by repeating the trial and error of the fitting based on the forward stepwise method.

Meanwhile, as shown in FIGS. 1 and 2, the clothing 11C of the first measuring means 11 measures the state of acceleration (hereinafter also referred to as W) applied to the subject 90 wearing the clothing 11C over time. A third measuring means 10A, which is an acceleration sensor, is attached. The third measuring unit 10A transmits the W measured over time to the control computer 12 through the first measuring unit 11 over time.
Information exchange such as data transmission is performed by wireless communication using the radio wave 91 between the first measuring unit 11 and the control computer 12. Thereby, when the respiration of the subject 90 is measured only by the first measuring means 11 (see FIG. 1), the restriction on the action range and the exercise state of the subject 90 can be eliminated.

As shown in FIG. 3, the control computer 12 obtains the respiratory ventilation volume V, which is the amount of change in the lung volume of the subject 90, from each data output from the first measurement means 11 and the third measurement means 10A. The respiratory ventilation volume V is output from the output means 12E. In addition, the control computer 12 is connected to the second measuring means 20 that can measure the amount of change in the lung volume of the subject 90 separately from the first measuring means 11. The breathing ventilation volume V can be taken in as time series data.
Here, the second measuring means 20 is a device different from the respiration measuring device 10. For this reason, the 2nd measurement means 20 can be suitably removed from the respiration measuring apparatus 10, and can be abbreviate | omitted (refer FIG. 1). Further, the second measuring means 20 measures the respiratory ventilation volume V, which is the amount of change in the lung volume of the subject 90, as time series data in a state independent of the respiratory measuring apparatus 10, and the measurement result is the second measuring means. It is also possible to record in 20 recording devices (not shown).

Specifically, as shown in FIG. 2, the second measuring means 20 is equipped with a nose clip 20 </ b> A that covers the nose of the subject 90 and a mouthpiece 21 that covers the mouth of the subject 90. This is a spirometer that measures the respiratory ventilation V of the subject 90 in the state. The second measuring means 20 detects the amount of exhalation or inspiration of the subject 90 passed through the mouthpiece 21 by the sensor 21A connected to the mouthpiece 21, so that the respiratory ventilation volume V is determined from the amount of exhalation or inspiration. Measure.
Here, since the second measuring means 20 needs to attach the nose clip 20A and the mouthpiece 21 to the subject 90 due to the difference in measurement, it is difficult to perform respiration measurement in the daily life of the subject 90. Have. Further, the second measuring means 20 measures the respiratory ventilation volume V with higher measurement accuracy than the first measuring means 11 in order to measure the respiratory ventilation volume V of the subject 90 from the amount of exhalation or inspiration of the subject 90. It has the feature that it can do.

A series of steps executed when realizing the respiration measurement method according to the embodiment of the present invention using the respiration measurement device 10 will be described. In the following, a person who uses the respiration measuring device 10 is also referred to as a “measuring person”, but this measuring person may be the subject 90 itself or may be different from the subject 90.
When realizing the respiration measurement method, first, the measurer prepares the respiration measurement device 10 in a state where the second measurement means 20 is connected, and wears the clothing 11C of the respiration measurement device 10 on the body of the subject 90. The power switch of the control computer 12 is turned on. At this time, the control computer 12 activates the above-described respiration measurement program, and the first recording unit 12A, the second recording unit 12B, the third recording unit 12C, and the virtual time series data creating unit 12D shown in FIG. Each is set by allocating hardware resources (not shown) of the control computer 12.

Next, as shown in FIG. 2, the measurer puts the subject 90 in a standing and stationary state (also referred to as a “standing position” in this specification), and the subject 90 in the standing position takes the second position. 2 The nose clip 20A and the mouthpiece 21 of the measuring means 20 are attached. Then, the measurer measures the fluctuation amount of the lung volume of the subject 90 in the standing state of the subject 90 (that is, the respiratory ventilation volume V) in parallel by each of the first measuring means 11 and the second measuring means 20. . At this time, the control computer 12 records the lengths X and Y measured by the first measuring means 11 in the first recording unit 12A shown in FIG. 3 as time-series data corresponding to the respective measurement times. . Further, the control computer 12 records the respiratory ventilation V measured by the first measuring unit 11 and the second measuring unit 20 in the first recording unit 12A as time series data corresponding to the respective measurement times.
Here, the standing state corresponds to the “first state” in the present invention. Further, the method of performing the measurement by the first measuring means 11 corresponds to the “first measuring method” in the present invention. Further, the method of performing the measurement by the second measuring means 20 corresponds to the “second measuring method” in the present invention. That is, the above steps correspond to the “first measurement step” in the present invention.

Subsequently, the control computer 12 compares the measurement results (that is, the respiratory ventilation volume V) of the first measurement unit 11 and the second measurement unit 20 recorded in the first recording unit 12A, and the first measurement unit 11 performs measurement. One parameter or a plurality of parameters representing how the measured change in the lung volume of the subject 90 deviates with reference to the change in the lung volume of the subject 90 measured by the second measuring means 20 A calibration parameter (hereinafter also referred to as R), which is a set of parameters collected as one vector amount, is derived and recorded in the first recording unit 12A shown in FIG. This step corresponds to the “calibration step” in the present invention.
When the calibration step is completed, the control computer 12 displays to the measurer by the output means 12E that the derivation of the calibration parameter R has been completed. In response to this display, the measurer ends each measurement in the first measurement step, and removes the second measurement means 20 from the respiration measurement device 10. As a result, the subject 90 is released from the above-described standing state and the wearing state of the second measuring means 20, and can live a daily life while wearing the clothing 11C of the respiratory measurement device 10.

Thereafter, as shown in FIG. 1, when the measurer determines that the subject 90 is in the second state, which is an arbitrary one state (the standing state in FIG. 1), the subject 90 in the second state Each site length X, Y and respiratory ventilation V are measured over time by the first measuring means 11. This step corresponds to the “second measurement step” in the present invention.
As a specific example of the second state, the posture of the subject 90 indicating whether the subject 90 is in a sitting state (not shown) in which the subject 90 sits with his back stretched on a chair, or in the above-described standing state. A state of the subject 90 representing whether the subject 90 is stationary or walking, a state of the subject 90 representing whether the subject 90 is full and hungry or hungry and depressed. The state of action from the subject 90 to the clothing 11C indicating whether the subject 90 sweats and the tensile deformation detection cloths 11A, 11B of the clothing 11C worn by the subject 90 are moistened. There are combinations of states.

In the second measuring step, the control computer 12 measures each part length X, Y measured by the first measuring means 11 and the measurement of the first measuring means 11 derived from each part length X, Y. The resulting respiratory ventilation volume V is recorded in the second recording unit 12B shown in FIG. 3 as time-series data corresponding to each measurement time. Further, in parallel with the measurement by the first measurement unit 11, the control computer 12 activates the third measurement unit 10 </ b> A and measures the acceleration state W applied to the subject 90 over time.
Further, the control computer 12 determines whether or not a significant variation is observed in the measured W, and the determination result (hereinafter also referred to as U) is used as time-series data corresponding to the measurement time of the W. It records in the 3rd recording part 12C shown in FIG.

Here, the determination criterion for determining the “significant variation” is that the measurer determines in advance the control computer 12 according to the specific state of the second state in which the measurement for the subject 90 is performed. It is to set. That is, when the second state is, for example, a state in which the subject 90 is stationary, the variation of the acceleration state W applied to the subject 90 is all determined to be “significant variation”. On the other hand, when the second state is a state in which the subject 90 is walking at a constant pace, for example, the acceleration state W applied to the subject 90 is a periodic acceleration fluctuation pattern caused by the subject 90 walking. It is set so that this change is determined as a “significant change” when it is changed in a different change pattern.
It should be noted that the measurer changes the setting of the control computer 12 before the second measurement step described above, so that the measurement of the W by the third measurement means 10A and the significant variation in the measured W are observed. And the recording of the determination result U to the third recording unit 12C can be omitted.

Incidentally, the control computer 12 determines whether each part length X, Y and the respiratory ventilation V input from the first measuring means 11 are recorded in the first recording unit 12A or the second recording unit 12B. 2 It is determined and switched depending on whether or not the measuring means 20 is connected to the control computer 12.
That is, when the second measuring means 20 is connected to the control computer 12, the control computer 12 uses the first measurement described above for the lengths X and Y and the respiratory ventilation V input from the first measuring means 11. It is determined as a measurement result in the step, and each time series data of the input part length X, Y and respiratory ventilation volume V is recorded in the first recording unit 12A. On the other hand, when the second measuring means 20 is removed from the control computer 12, the control computer 12 uses the second measurement described above for the lengths X and Y and the respiratory ventilation V input from the first measuring means 11. It is determined as the measurement result in the step, and the input time length data of the part lengths X and Y and the respiratory ventilation V are recorded in the second recording unit 12B.

Now, the control computer 12 that has performed the second measurement step described above is a time series of the lengths X and Y of each part measured by the first measurement means 11 and recorded in the second recording unit 12B in the second measurement step. The data and the time series data of each part length X, Y measured by the first measurement means 11 and recorded in the first recording unit 12A in the first measurement step described above are respectively virtual time series shown in FIG. It inputs into the data preparation means 12D.
Further, when the time series data of the determination result U described above is recorded in the third recording unit 12C in the second measurement step, the control computer 12 also includes the time series data of the recorded determination result U together with the virtual time series data. Input to the time-series data creation means 12D.

At this time, the virtual time-series data creating unit 12D first determines whether or not the determination result U recorded in the third recording unit 12C is input to the virtual time-series data creating unit 12D. When the determination result U has not been input, the virtual time series data creation unit 12D has the individual data X _o forming the time series data of the part lengths X and Y input to the virtual time series data creation unit 12D. , _Yo is extracted.
When the determination result U is input, the virtual time-series data creating unit 12D specifies a time range in which no significant change was observed in the acceleration state W applied to the subject 90 from the determination result U. Then, the virtual time series data creation means 12D is identified from among the individual data X _o and Y _o constituting the time series data of the part lengths X and Y input to the virtual time series data creation means 12D. A process is performed in which each data in the determined time range is regarded as individual data constituting the entire time-series data of the part lengths X and Y recorded in the second recording unit 12B.

Subsequently, the virtual time series data creating unit 12D calculates the arithmetic averages N _X and N _Y of each data constituting the extracted time series data of the part lengths X and Y, respectively. Each of the arithmetic averages N _X and N _Y corresponds to a “second representative value” in the present invention.
Further, the virtual time series data creating means 12D extracts each piece of data constituting each time series data of the part lengths X and Y recorded in the first recording unit 12A, and the arithmetic average P of each extracted data _X, we calculate the _{P Y} respectively. The arithmetic averages P _X and P _Y correspond to the “first representative value” in the present invention.

Then, the virtual time series data creation means 12D uses the part of the hardware resources (not shown) of the control computer 12 assigned to the virtual time series data creation means 12D, and calculates the arithmetic mean N _X calculated respectively. The function X _t <M> shown in the following (formula 2) is derived and defined from the arithmetic mean P _X.
Here, the function X _{t <M>} is a function representing a proportional relationship to the ratio between a first representative value described above and the arithmetic mean N _X is a second representative value described above arithmetic average P _X and proportional constant is there.

ところで、関数Ｘ_ｔ〈Ｍ〉は、第１代表値である算術平均Ｐ_Ｘを入力パラメータＭとして入力した際に、第２代表値である算術平均Ｎ_Ｘを出力する関数でもある。言いかえると、関数Ｘ_ｔ〈Ｍ〉は、第２代表値である算術平均Ｎ_Ｘが第１代表値である算術平均Ｐ_Ｘに従属される関係を表した関数でもある。すなわち、関数Ｘ_ｔ〈Ｍ〉により表される関係は、本発明における「関数従属関係」に相当する。

Incidentally, the function X _{t <M>,} when you enter the arithmetic mean P _X is a first representative value as an input parameter M, is also a function for outputting the arithmetic mean N _X is a second representative value. In other words, the function X _t <M> is also a function representing a relationship in which the arithmetic average N _X that is the second representative value is subordinate to the arithmetic average P _X that is the first representative value. That is, the relationship represented by the function X _t <M> corresponds to the “function dependency” in the present invention.

Also, the virtual time series data creation means 12D uses the part of the hardware resources (not shown) of the control computer 12 assigned to the virtual time series data creation means 12D, and calculates the arithmetic mean N _Y calculated respectively. The function Y _t <L> shown in the following (formula 3) is derived and defined from the arithmetic mean P _Y.
Here, Y t _<L> is a formula representing a proportional relationship to the ratio was proportional constant between a first representative value described above and the arithmetic mean N _Y is a second representative value described above arithmetic mean P _Y .

ところで、関数Ｙ_ｔ〈Ｌ〉は、第１代表値である算術平均Ｐ_Ｙを入力パラメータＬとして入力した際に、第２代表値である算術平均Ｎ_Ｙを出力する関数でもある。言いかえると、関数Ｙ_ｔ〈Ｌ〉は、第２代表値である算術平均Ｎ_Ｙが第１代表値である算術平均Ｐ_Ｙに従属される関係を表した関数でもある。すなわち、関数Ｙ_ｔ〈Ｌ〉により表される関係は、本発明における「関数従属関係」に相当する。

By the way, the function Y _t <L> is also a function that outputs the arithmetic average _NY that is the second representative value when the arithmetic average P _Y that is the first representative value is input as the input parameter L. In other words, the function Y _t <L> is also a function that represents a relationship in which the arithmetic average _NY that is the second representative value is subordinate to the arithmetic average P _Y that is the first representative value. That is, the relationship represented by the function Y _t <L> corresponds to the “function dependency” in the present invention.

The virtual time series data creation means 12D that has defined the function X _t <M> converts each piece of data X _o forming each time series data of the part length X input to the virtual time series data creation means 12D. By inputting the function X _t <M> as an input parameter M, the value X _t = X _t <X _o > in which the function dependency is applied to each X _o is calculated. The virtual time series data generating means 12D includes a respective values X _t which is calculated is the virtual time series data obtained by associating the measurement time of imputed X _o In determining the value X _t virtual time series data (hereinafter, also expressed. as X _S) to create a. This step corresponds to the “virtual time series data creation step” in the present invention.
Further, the virtual time series data creating means 12D defining the function Y _t <L> has individual data Y _o constituting each time series data of the part length X input to the virtual time series data creating means 12D. Are input to the function Y _t <L> as input parameters L, respectively, thereby calculating the values Y _t = Y _t <Y _o > in which the above function dependency is applied to each Y _o . The virtual time series data creating means 12D is virtual time series data in which each calculated value Y _{t is associated} with the measurement time of Y _o substituted when calculating the value Y _t. virtual time series data (hereinafter, also denoted Y _S.) to create a. This step corresponds to the “virtual time series data creation step” in the present invention.

Subsequently, the virtual time series data creating unit 12D outputs the created virtual time series data X _S and Y _S to the output unit 12E shown in FIG.
In response to this output, the output unit 12E first performs data processing equivalent to the following (Equation 4), thereby calibrating the fluctuation amount of the lung volume based on the virtual time series data X _S and Y _S. Conversion to time-series data composed of a function V <R> of a parameter R.

ここで、Ｘ_ｔ、Ｙ_ｔは、それぞれ仮想時系列データＸ_Ｓ、Ｙ_Ｓをなす個々のデータであり、それぞれ上述した仮想時系列データ作成ステップにおいて算定された値を使用する。すなわち、上記関数Ｖ〈Ｒ〉は、上述した呼吸換気量の計算式である（式１）における各係数Ｚ_０、Ｚ_１、Ｚ_２、Ｚ_３を、それぞれ校正のパラメータＲの関数であるＺ_０〈Ｒ〉、Ｚ_１〈Ｒ〉、Ｚ_２〈Ｒ〉、Ｚ_３〈Ｒ〉に置き換えたものであり、その意味は上述した（式１）と同じである。

Here, X _t and Y _t are individual data forming the virtual time series data X _S and Y _S , respectively, and the values calculated in the above-described virtual time series data creation step are used. That is, the function V <R> is a function of the calibration parameter R for each of the coefficients Z ₀ , Z ₁ , Z ₂ , and Z ₃ in the above-described formula for calculating the respiratory ventilation (Formula 1). ₀ <R>, Z ₁ <R>, Z ₂ <R>, Z ₃ <R> are substituted, and the meaning is the same as in the above-described (Formula 1).

Next, the output unit 12E acquires the calibration parameter R recorded in the first recording unit 12A shown in FIG. Then, the output unit 12E substitutes the acquired calibration parameter R for each function V <R> to obtain the amount of change in lung volume derived as time series data composed of each function V <R>. Substitute the parameter R for calibration and apply it.
Then, the output unit 12E estimates the amount of change in lung volume to which the calibration parameter R is applied as an estimate of the respiratory volume V, which is the amount of change in lung volume when the subject 90 is in the second state described above. Output as a result. That is, each of the above steps corresponds to an “output step” in the present invention.

In each step described above, the measurement result of the part length in the second state which is one of the states that the subject 90 can take is the representative value of the part length of the subject 90 in the predetermined first state. A function dependency relationship (function X _t <M> and function Y) representing a relationship between one representative value P _X , P _Y and a second representative value N _X , N _Y , which is a representative value of the length of the site of the subject in the second state _t <L>), and converted into data corresponding to the measurement result of the part length in the first state. Then, by applying the calibration parameter R in the first state to the fluctuation amount of the lung volume of the subject derived from the converted data, the lungs of the subject in the second state in which the deviation of the measurement result is reduced Output as volume fluctuation.
For this reason, according to each step described above, the deviation of the measurement result of the fluctuation amount relative to the fluctuation amount of the lung volume of the subject 90 in an arbitrary state that the subject 90 can take is calculated as 1 in the predetermined first state. It is possible to reduce by using only one or one set of calibration parameters R. In other words, according to the above-described steps, it is possible to reduce the deviation of the measurement result in the respiration measurement of the subject 90 using only one or one set of parameters R regardless of the state of the subject 90. Accordingly, it is possible to easily realize a reduction in measurement result deviation in the amount of change in the lung volume of the subject 90 corresponding to each state of the subject 90 that is variously changed.

Further, according to each of the steps described above, the function dependency is a proportional relationship in which the ratio between the second representative values N _X and N _Y and the first representative values P _X and P _Y is a proportional constant (described above ( (See Equation 2) and Equation 3)), so that virtual time series data can be created by a simple calculation algorithm. Thereby, the information processing amount and information processing time in the virtual time series data creation means 12D (see FIG. 3) of the respiration measuring device 10 can be reduced.
By the way, when the subject 90 is in the second state, which is one state, when a significant variation is measured in the acceleration state W applied to the subject 90, the time variation in which the significant variation is measured is accurate. It can be considered that some kind of event that prevents the measurement is occurring. Here, according to each step described above, a time range in which an event that prevents accurate measurement is not found is identified from data obtained by measuring the acceleration state W applied to the subject 90 over time, and a time series in this time range is determined. It becomes possible to derive the second representative values N _X and N _Y from the data. As a result, it is possible to prevent the event that prevents the accurate measurement from degrading the accuracy of the functional dependency relationship and deteriorating the accuracy of the entire measurement result in the respiration measurement of the subject.

Now, the measurement result of the part length in an arbitrary state that can be taken by the subject 90 uses a functional dependency relationship between the representative value of the part length in the state and the representative value of the part length of the subject 90 in a predetermined state. Thus, the knowledge that the data can be converted into data corresponding to the measurement result of the part length in the predetermined state is a knowledge newly discovered by the present inventors through experiments. Hereinafter, an experiment that has caused the present inventor to discover the above findings will be described.
The present inventor first has five subjects, a subject, b subject, c subject, d subject, and e subject, standing, sitting, forward leaning, backward leaning, and walking. The experiment was conducted to measure the respiration of each subject over time in each of the five states.

Here, the “standing position” is a state in which the subject stands up and stands still. In addition, the “sitting position” is a state in which the subject sits still with his back stretched on the chair. In addition, the “forward tilted sitting state” is a state in which the subject sits on a chair and stands still with the body bent forward. Further, the “backward tilted position state” is a state in which the subject sits on a chair and is stationary as if the body is slid rearward. In the above experiment, the respiration of each subject was measured with the above-mentioned “state of walking” as the state where the subject was walking on the treadmill in the same direction at a constant pace.
In the experiment described above, each respiration is measured by the tensile deformation detecting cloth (tensile deformation detecting cloths 11A and 11B shown in FIG. 1) of the respiration measuring apparatus having the same configuration as the first measuring means 11 (see FIG. 1). This was done by measuring the variation of the length of the part detected as the variation of the capacitance generated in the above. Further, in the above experiment, the variation in the length of the part detected as the variation in the capacitance is measured for 10 [seconds] or more at a sampling frequency of 100 [Hz], and thus consists of 1000 or more data. Measured as time series data. The experiment was repeated twice with a time interval.

Next, the inventor makes the time series data of the capacitance measured in the standing state of each subject with respect to each of the data constituting the time series data of the capacitance measured in each of the above experiments. Calibration parameters based on the data were derived. The derivation results of the calibration parameters are shown in FIGS.
Here, FIG. 4 shows a box-and-whisker diagram in which the parameters of each calibration in the first experiment for the subject “a” are summarized for each state of the subject “a”. Further, FIG. 5 shows a box-and-whisker diagram in which parameters of each calibration in the second experiment for the subject “a” are summarized for each state of the subject “a”. FIG. 6 is a box and whisker plot in which parameters of each calibration in the first experiment for the subject b are summarized for each state of the subject b. FIG. 7 shows a box-and-whisker diagram in which parameters for each calibration in the second experiment for the subject b are summarized for each state of the subject b. Further, FIG. 8 shows a box and whisker plot in which parameters of each calibration in the first experiment for the subject c are summarized for each state of the subject c. Further, FIG. 9 shows a box-and-whisker diagram in which parameters for each calibration in the second experiment for the subject c are summarized for each state of the subject c. Further, FIG. 10 shows a box-and-whisker diagram in which the parameters of each calibration in the first experiment for the subject d are summarized for each state of the subject d. FIG. 11 is a box and whisker plot in which parameters of each calibration in the second experiment for the subject d are summarized for each state of the subject d. FIG. 12 is a box and whisker plot in which parameters of each calibration in the first experiment for the e subject are summarized for each state of the e subject. FIG. 13 shows a boxplot in which parameters for each calibration in the second experiment for the e subject are summarized for each state of the e subject.

In each boxplot of FIGS. 4 to 13, the lower and middle lines and the upper end of the box indicate the 25th percentile value, the 50th percentile value, and the 75th percentile value in each calibration parameter, respectively. Moreover, in each box whip figure of FIG.4, FIG.5, FIG.6, FIG.8, FIG.9, FIG.10, FIG.12 and FIG. Each shows the maximum and minimum values of each calibration parameter. In each boxplot of FIGS. 7 and 11, the tips of the whiskers protruding above and below the box respectively have a value that is 1.5 × Q larger than the 75th percentile value in each calibration parameter, and The value is 1.5 × Q smaller than the 25th percentile value. Here, Q is a value obtained by subtracting the 25th percentile value from the 75th percentile value in each calibration parameter. In each boxplot of FIGS. 7 and 11, the circles are included in a range from a value that is smaller by 1.5 × Q than the 25th percentile value to a value that is larger by 1.5 × Q than the 75th percentile value. It is an outlier that is not possible.
Note that the calibration parameters illustrated in FIGS. 4, 5, 6, 8, 9, 10, 12, and 13 are each 1.5 × Q smaller than the 25th percentile value. There was no outlier that was not included in the range from the value to a value 1.5 × Q greater than the 75th percentile value. Each of the calibration parameters shown in the box plots of FIGS. 7 and 11 has a range from a value 3 × Q smaller than the 25th percentile value to a value 3 × Q larger than the 75th percentile value. There was no extreme value that was not included.

Now, when comparing the box whisker charts of FIGS. 4 to 13, the derivation results of the parameters for each calibration when each subject is in a different state may vary depending on the state of each subject. I understand. In addition, it can be seen that the derivation results of the parameters for each calibration when the plurality of subjects are in the same state vary depending on the subject. It can also be seen that the derivation results of the parameters for each calibration when the same subject is in the same state with time are different from each other.
However, it can be seen that the result of deriving the parameters of each calibration when one state is continued in each subject hardly varies in any state of any subject in the number of experiments. This is because, when one state continues in the subject, each measurement result of the length of the part of the subject can be approximated with high accuracy by the representative value of each measurement result, regardless of the state. It means you can do it. Therefore, the measurement result of the part length in an arbitrary state that can be taken by the subject is determined based on the relationship between the representative value of the part length in the state and the representative value of the part length of the subject in the predetermined state. It can be said that it can be converted into data corresponding to the measurement result of the part length in the state.

In addition, this inventor performed the verification experiment which verifies the effectiveness of the respiration measuring method of this invention mentioned above. Hereinafter, an experimental method and experimental results of the verification experiment will be described.
In the verification experiment, the present inventor sets the standing state to which the respiration measurement device 10 and the second measurement means 20 shown in FIG. 2 are respectively attached as the first state, and the respiration measurement method of the present invention is applied to the subject. Each step up to the calibration step in was performed. Subsequently, the present inventor sets various states in which the respiration measuring device 10 and the second measuring means 20 are respectively mounted as a second state, and the second measuring step in the respiration measuring method of the present invention is performed on the subject. Each step from the output step to the output step and independent measurement of the respiratory ventilation V by the second measuring means 20 were performed in parallel. The inventor then outputs the output result in the output step, the measurement result of the first measurement unit 11 recorded in the second recording unit 12B (see FIG. 3) of the respiration measurement device 10, and the first of the respiration measurement device 10. The calibration parameter R recorded in one recording unit 12A (see FIG. 3) and the measurement result of the second measuring means 20 recorded independently by the second measuring means 20 were obtained and analyzed.

In addition, the present inventor sets the five states of the standing state, the sitting state, the forward tilted sitting state, the backward tilted sitting state, and the walking state as the “various states” in the second state. The verification experiment in each was conducted. Here, the “standing position” is a state in which the subject stands up and stands still. In addition, the “sitting position” is a state in which the subject sits still with his back stretched on the chair. In addition, the “forward tilted sitting state” is a state in which the subject sits on a chair and stands still with the body bent forward. Further, the “backward tilted position state” is a state in which the subject sits on a chair and is stationary as if the body is slid rearward. Further, in each of the verification experiments, each step was executed with the state where the subject was walking on the treadmill in the same direction at a constant pace as the “state of walking”.
In addition, the present inventor conducted verification experiments in each of the above five states for five subjects: A subject, B subject, C subject, D subject, and E subject. In addition, the present inventor determined whether or not a significant variation was observed in the measurement by the third measurement means 10A (see FIGS. 1 to 3) and the measurement result in all the verification experiments of each state for each subject. In addition, recording of the determination result in the third recording unit 12C (see FIG. 3) is omitted.

In the analysis of each verification experiment described above, the inventor sets each coefficient Z ₀ , Z ₁ , Z ₂ , Z ₃ in the above-described (Equation 1) based on the acquired calibration parameter R, and each coefficient (Equation 1) in a state where Z ₀ , Z ₁ , Z ₂ , and Z ₃ were set was applied to each measurement result of the acquired first measurement means 11 to estimate the respiratory ventilation. Here, the estimation result is the estimation result of the respiratory ventilation obtained by applying the calibration parameter R in the standing position to each measurement result of the first measurement means 11 in the individual state of the subject (hereinafter, estimated). It can also be said that it is also expressed as a result K.)
Note that the output result in the above-described output step and the estimation result K are different in the derivation method. That is, the output result in the output step is obtained by converting the measurement result in the individual state of the subject into data corresponding to the measurement result in the standing state, and applying the calibration parameter R in the standing state to the converted data. It is the estimation result of the obtained respiratory ventilation.

Further, the inventor compares the obtained measurement results of the first measurement unit 11 and the second measurement unit 20, and how the measurement result of the first measurement unit 11 is based on the measurement result of the second measurement unit 20. A calibration parameter (hereinafter also referred to as calibration parameter J) was derived.
Then, the present inventor has described on the basis of the parameter J of the derived calibration set (Equation 1) each coefficient _Z 0 _at, Z _1, Z 2, _{Z 3,} the coefficients _{Z 0, Z} 1, Z _2, Z ₃ is a state set (formula 1), was estimated respiratory ventilation volume was applied to each measurement result of the first measuring unit 11 obtained. Here, the estimation result is the estimation result of the respiratory ventilation obtained by applying the calibration parameter J in the state to each measurement result of the first measuring means 11 in the individual state of the subject (hereinafter referred to as the estimation result). I can also be said.

And this inventor made the output result in the acquired output step, the acquired measurement result of the 2nd measurement means 20, the above-mentioned presumed result K, and the above-mentioned presumed result I as a graph, and contrasted each graph. . Each of these graphs is shown in FIGS. Further, the inventor derives an estimation error based on the measurement result of the second measuring means 20 for each of the output result in the output step, the estimation result K, and the estimation result I. Each of these estimation errors was compared with a bar graph. Each bar graph is shown in FIGS.
Note that, when the above-described estimation result I is the standing state, the derivation method thereof is equivalent to the above-described estimation result K derivation method. For this reason, the inventor omitted the derivation and comparison of the estimation result I for the data of the verification experiment when the second state described above is in the standing state.

Now, comparing the graphs of FIGS. 14 to 103 in correspondence, the measurement result of the second measuring means 20 and the estimation result I are almost the same regardless of whether the set second state is any of the five states described above. It can be said that the subject exhibits the same respiratory ventilation regardless of the subject. Further, in each subject, the output result in the output step of the present invention is substantially the same respiratory ventilation volume (see, for example, FIG. 21 and FIG. 22) or respiration closer to the measurement result of the second measuring means 20 compared to the estimation result K. It can be said that the ventilation amount (see, for example, FIGS. 38 to 40) is shown.
From this, when applying the calibration parameter R in the standing state to the measurement result in the individual state to obtain the estimated result of the respiratory ventilation, the measurement result is converted into data corresponding to the respiration measurement result in the standing state in advance. A conclusion (hereinafter, also referred to as conclusion H) that the accuracy of the estimation result can be improved by conversion is obtained. Here, the conclusion H is that, among the 20 verification experiments for which the estimation result I was derived, in the 17 verification experiments, the estimation error of the respiratory ventilation is the measurement result of the respiration in the standing position. It can also be obtained from the fact that it is reduced by converting it into data corresponding to (see the respective bar graphs in FIGS. 104 to 108).

In addition, the present inventor, for each experiment result in the above-mentioned 17 verification experiments, “measurement result in individual state, measurement result of breathing in standing position before applying calibration parameters in standing position” The hypothesis that the estimation error of respiratory ventilation obtained from the above measurement results cannot be reduced by converting to the data equivalent to ”is set as a null hypothesis that should be rejected, and Wilcoxon's sign-rank sum test is performed. went. As a result, the present inventor obtained a test result that the rejection of the null hypothesis is statistically significant at a level of less than 1% for each experimental result in the 17 verification experiments. It was.
The test result means that the probability that the above-described conclusion H is wrong is less than 1%. Thus, it can be said that the respiration measurement method of the present invention has shown its effectiveness.

By the way, each experimental result in the verification experiment for three times when A subject is set in the forward tilted seated state or the backward tilted seated state (see FIG. 104) and when the B subject is put in the backward tilted seated state (see FIG. 105). In FIG. 104 and FIG. 105, when the measurement result in the second state is converted into data corresponding to the respiration measurement result in the standing state, the estimation error of the respiratory ventilation is increased.
However, the amount of increase in the estimation error is small compared to the amount of estimation error itself in the respiratory ventilation. For this reason, it can be estimated that the increase in the estimation error does not indicate a substantial difference (hereinafter also referred to as estimation G).

Therefore, the present inventor has converted “measurement results in individual states into data corresponding to respiration measurement results in the standing state” for each experimental result in the 20 verification experiments in which the estimation result I was derived. Therefore, the respiratory ventilation volume obtained by applying the calibration parameters in the standing state to the converted data and the respiratory ventilation volume obtained by applying the calibration parameters in that state to the measurement results in each state are obtained. The hypothesis that there is no difference in the estimation error included in the respiratory ventilation was set as the null hypothesis to be rejected, and Wilcoxon's sign rank sum test was performed. As a result, the present inventor verified that the rejection of the null hypothesis is not statistically significant unless the level is higher than 23% for each experimental result in the 20 verification experiments. The result was obtained.
The above-described test result means that the above-mentioned guess G has a probability of being greater than 23% and there is no data sufficient to overturn the guess G. Thereby, the respiration measurement method of the present invention is a conventional respiration measurement method for obtaining a respiratory ventilation volume by applying a calibration parameter in that state to a measurement result in each state (see, for example, Patent Document 1 described above). It can be estimated that the deviation of the measurement result can be suppressed in the same manner as.

The present invention is not limited to the appearance and configuration described in the above-described embodiment, and various modifications, additions, and deletions can be made without changing the gist of the present invention. For example, the following various forms can be implemented.
(1) The functional dependency used to create the virtual time series data is measured in the first measurement step with a second representative value that is an arithmetic average of each part length measured in the second measurement step. In addition, it is not limited to the proportional relationship in which the ratio with the first representative value that is the arithmetic average of the lengths of the respective parts is a proportional constant. That is, the functional dependency relationship between the second representative value and the first representative value is, for example, a Kalman filter, a Monte Carlo filter, an expected value maximization method, a method based on an autoregressive moving average model, a method based on an autoregressive model, etc. It can be a function dependency defined by an arbitrary method. Further, the first representative value or the second representative value derived from the lengths of the respective parts is set to an arbitrary average value such as a geometric average or a weighted average, or an arbitrary representative value such as a mode value or a median value. can do.
(2) In the respiration measurement method of the present invention, the measurement of the length of the site of the subject in the second measurement step is not limited to that performed by the measurer determining that the subject is in the second state. That is, for example, the second state of the subject is defined by the acceleration condition applied to the subject and recorded in advance in the control computer of the respiratory measurement device, and the acceleration measured by the third measurement means of the respiratory measurement device matches the acceleration condition. Then, the second measuring step can be executed by the control computer.
(3) The clothes to which the tensile deformation detection cloth is attached in the first measuring means of the respiratory measurement device are not limited to T-shirts, but are clothes worn on the subject's torso, such as brassiere, corset, shorts, pants, bodysuit, blouse, etc. Anything is acceptable. Moreover, the structure which made the attachment or detachment with respect to the test subject easy to use for a test subject can also be used by making the clothes to which the tensile deformation detection cloth is attached into a band such as a belly band or a belt.
(4) The shape and configuration of each measurement means of the respiratory measurement device are not limited to the configuration of the above-described embodiment. For example, in the first measurement means, a configuration can be used in which the shape and arrangement of the tensile deformation detection cloth is changed and the length of an arbitrary part on the body surface of the subject is measured. Moreover, when measuring the length of the site | part on a test subject's body surface, the clothing to which the strain gauge was attached instead of the tension deformation | transformation detection cloth of the said embodiment can be used. In addition, a motion capture system that measures a subject by detecting a position of each marker by attaching a plurality of markers on one or both of the first measuring means and the third measuring means on the body surface of the subject. Can be used.
(5) The second measurement means for measuring the amount of change in the lung volume of the subject in the first measurement step of the respiration measurement method of the present invention is not limited to a spirometer, which is an apparatus different from the respiration measurement apparatus of the present invention. . That is, for example, when a respiration measurement device that is different from a spirometer such as a thermistor type or an impedance type and has a higher measurement accuracy than the first measurement means of the respiration measurement device of the present invention can be used. The device can be used as a second measuring means instead of a spirometer. Further, the respiration measuring device and the second measuring means of the present invention can be integrated into one device.
(6) The respiration measurement method and respiration measurement apparatus of the present invention are not limited to those intended for human subjects. That is, the present invention appropriately changes the shape and configuration of each measuring means of the respiratory measurement device and each parameter and calculation formula input to the data processing device, so that any living organism having a lung can be used as a subject. The amount of change in lung volume associated with the subject's lung breathing can be determined.

DESCRIPTION OF SYMBOLS 10 Respiration measuring apparatus 10A 3rd measurement means 11 1st measurement means 11A Tensile deformation detection cloth 11B Tensile deformation detection cloth 11C Clothing 12 Control computer 12A 1st recording part 12B 2nd recording part 12C 3rd recording part 12D Virtual time series data preparation Means 12E Output means 20 Second measuring means 20A Nose clip 21 Mouthpiece 21A Sensor 90 Subject 91 Radio wave

Claims (6)

Using a living organism having a lung as a subject, the amount of change in lung volume associated with the subject's lung respiration is measured over time by measuring the length of a portion in a predetermined direction on a predetermined surface on the body surface in the subject. In the respiratory measurement method that can be obtained by
When the subject is in a predetermined first state, the amount of change in the lung volume of the subject is measured by first measuring means for obtaining time-series data obtained by measuring the length of the part of the subject over time. A first measurement method and a second measurement method in which the measurement accuracy of the amount of change in lung volume is higher than that of the first measurement unit are measured in parallel by two measurement methods. One measurement step;
The amount of change in the lung volume of the subject measured by the first measurement method in the first measurement step is the amount of the lung volume of the subject measured by the second measurement method in the first measurement step. A calibration step for deriving a calibration parameter, which is one or a set of parameters representing how to deviate based on the amount of variation;
A second measuring step of measuring the length of the part of the subject over time by the first measuring means when the subject is in a second state, which is an arbitrary one state;
The second representative value, which is the representative value of the time-series data of the part length measured by the first measuring means in the second measuring step, is measured by the first measuring means in the first measuring step. A function dependency relationship that is a relationship dependent on a first representative value that is a representative value of the time series data of the part length is expressed as a time series of the part length measured by the first measuring means in the second measuring step. A virtual time-series data creation step for creating virtual time-series data that is time-series data applied to each data constituting the data;
Deriving the subject's lung volume fluctuation amount based on the virtual time series data, applying the calibration parameters performed in the calibration step to the derived lung volume fluctuation amount, An output step of considering and outputting the fluctuation amount of the lung volume to which the calibration parameter is applied as the fluctuation amount of the lung volume when the subject is in the second state;
With
Respiratory measurement method. The respiratory measurement method according to claim 1,
In the virtual time series data creation step, the virtual time series data is created with the function dependency as a proportional relation in which a ratio between the second representative value and the first representative value is a proportional constant;
Respiratory measurement method. The respiration measurement method according to claim 1 or 2,
In the second measurement step, the state of the subject is measured over time in parallel with the change in the lung volume of the subject,
In the virtual time series data creation step, a significant change is seen in the condition of the subject in the second measurement step from the time series data of the part length measured by the first measurement means in the second measurement step. The time series data of the time range that did not exist is extracted, and the extracted time series data is regarded as the whole time series data of the part length measured by the first measurement means in the second measurement step. Deriving a representative value,
Respiratory measurement method. Using a living organism having a lung as a subject, the amount of change in lung volume associated with the subject's lung respiration is measured over time by measuring the length of a portion in a predetermined direction on a predetermined surface on the body surface in the subject. In the respiratory measurement device that can be obtained by
First measuring means for measuring the length of the part of the subject over time, and determining the amount of change in the lung volume of the subject from time-series data of the measured part length;
Time series data of the part length measured by the first measuring means when the subject is in a predetermined first state, and the lung volume of the subject obtained from the time series data of the part length When the subject is in the first state, the lung volume of the subject measured by the second measuring means having a higher measurement accuracy of the amount of fluctuation of the lung volume than the first measuring means. A first recording unit in which a calibration parameter, which is one or a set of parameters, representing how to deviate with respect to the fluctuation amount of
A second recording unit for recording time-series data of the part length measured by the first measuring means when the subject is in a second state which is an arbitrary one state;
The second representative value, which is the representative value of the part length time series data recorded in the second recording unit, is the representative value of the part length time series data recorded in the first recording unit. Virtual time-series data that is time-series data obtained by applying a function-dependent relation, which is a relation subordinate to the first representative value, to each data constituting the time-series data of the part length recorded in the second recording unit. Virtual time series data creation means to create,
A fluctuation amount of the lung volume of the subject is derived based on the virtual time series data, and the calibration parameter recorded in the first recording unit is applied to the derived fluctuation amount of the lung volume. An output means for outputting the lung volume fluctuation amount to which the calibration parameter is applied as the lung volume fluctuation amount when the subject is in the second state;
With
Respiratory measurement device. The respiratory measurement device according to claim 4,
The virtual time-series data creating means creates the virtual time-series data with the function dependency as a proportional relation in which a ratio between the second representative value and the first representative value is a proportional constant.
Respiratory measurement device. The respiratory measurement device according to claim 4 or 5, wherein
Third measuring means for measuring the state of the subject over time when the subject is in the second state;
A third recording unit for recording time-series data indicating whether or not a significant variation was observed in the state of the subject measured by the third measuring unit;
With
The virtual time series data creating means, from the time series data of the part length recorded in the second recording unit, time series data of a time range in which no significant change was found in the state of the subject, The second representative is extracted by using the time series data recorded in the third recording unit, and the extracted time series data is regarded as the entire time series data of the part length recorded in the second recording unit. Deriving a value,
Respiratory measurement device.

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