Measuring device

Abstract

Provided is a measurement device capable of improving the accuracy of reducing an ambient noise component in data segmentation factor analysis (PFA). The measurement device includes: a signal sensor unit including one or more signal sensors and having a function of measuring a measurement signal in which a target signal and a first noise are mixed, and a function of detecting a first noise signal including the first noise and in which a level of a component of the target signal is lower than a predetermined value; and a processing unit that performs data division factor analysis on the basis of measurement data, which is data of the measurement signal measured by the signal sensor unit, and control data, which is data of the first noise signal measured by the signal sensor unit. A process for reducing a component of the first noise included in the measurement data is performed.

Description

Technical Field

[0001] The present disclosure relates to a measuring device. Background Art

[0002] In order to obtain good analysis results in various measurements, it is necessary to remove various environmental noises that overlap with the desired signal.

[0003] For example, as a method for removing biologically derived environmental noise in brain magnetic field measurement, data partition factor analysis (PFA: Partitioned Factor Analysis) is disclosed (especially refer to pages 96-97 of Non-Patent Document 1 and Non-Patent Document 2).

[0004] In PFA, the signal measurement period is divided into two intervals (intervals in time): a control interval (for example, an interval that does not contain the target signal and is only so-called noise) and a measurement interval (an interval that contains the target signal). The environmental noise component is estimated based on the control interval and removed from the entire measurement data.

[0005] As a specific example, in PFA, the interval of the signal portion in the center (or near the center) during the signal measurement period is set as the interval of the target signal (measurement interval), and the interval on the past side that is sufficiently far from the target signal interval (for example, the interval on the left side of the graph) or the interval on the future side that is sufficiently far away (for example, the interval on the right side of the graph) is set as the control interval to obtain control data.

[0006] Furthermore, Patent Document 1 describes noise removal by active cancel or signal processing by SSP (Signal Space Projection) using environmental noise data acquired separately from a measurement signal (see Patent Document 1).

[0007] Prior art literature

[0008] Patent Literature

[0009] Patent Document 1: Japanese Patent Application No. 2008-538956

[0010] Non-patent literature

[0011] Non-patent document 1: SS Nagarajan, HT Attias, KE Hild II and K. Sekihara, “A probabilistic algorithm for robust interference suppression in bioelectromagnetic sensor data”, Stat. Med., vol. 26, no. 21, pp. 3886-3910, September 20, 2007.

[0012] Non-patent document 2: K. Sekihara, and SS Nagarajan, “Electromagnetic Brain Imaging: A Bayesian Perspective”, Springer, 2015 / 3 / 20, p.75-82, p.96-97

[0013] Non-patent document 3: K.Sekihara, and SSNagarajan, "Subspace-based interferenceremoval methods for a multichannel biomagnetic sensor array", Journal of Neural Engineering 14(5)(2017)051001

[0014] Non-patent document 4: Kensuke Sekigahara, “Bayesian Signal Processing,” Kyoritsu Publishing, April 10, 2015, p. 65-72 Summary of the invention

[0015] Problems to be solved by the invention

[0016] However, in the above-mentioned conventional technology, when PFA is applied, the ambient noise component may not be completely removed but may remain, and the accuracy of reducing the ambient noise component may be insufficient.

[0017] For example, in PFA, even after the environmental noise component is removed using control data, periodic waveform fluctuations may still exist. Here, the periodic waveform fluctuations may be caused by, for example, the inherent vibration of the sensor fixture, the periodic noise of the body movement of the measured person (for example, the beating of the heart), the noise from the power supply, or the magnetic noise from the surrounding motor.

[0018] In the conventional technology, control data (control interval) is selected from a narrow area (signal measurement period) by human visual inspection, so it is sometimes unclear whether the target signal is completely excluded in the control interval.

[0019] The present disclosure has been developed in consideration of such circumstances, and an issue thereof is to provide a measuring device capable of improving the accuracy of reducing environmental noise components in PFA.

[0020] Technical solutions to solve problems

[0021] One method is a measuring device comprising: a signal sensor unit, which includes one or more signal sensors and has a function of measuring a measurement signal in which a target signal and a first noise are mixed, and a function of detecting a first noise signal whose level of a component of the target signal is lower than a specified value and includes the first noise; a processing unit, which performs processing to reduce the component of the first noise contained in the measurement data based on data of the measurement signal measured by the signal sensor unit, namely measurement data, and data of the first noise signal measured by the signal sensor unit, namely control data, through data segmentation factor analysis.

[0022] Effects of the Invention

[0023] According to the present disclosure, in the measurement device, it is possible to improve the accuracy of reducing the environmental noise component in PFA. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a diagram showing a schematic configuration of a measuring device including an information processing device according to an embodiment.

[0025] Figure 2 It is a diagram showing a schematic configuration of an information processing device according to an embodiment.

[0026] Figure 3 It is a diagram schematically showing the process flow of the first structural example of the embodiment.

[0027] Figure 4 It is a diagram schematically showing the process flow of the second structural example of the embodiment.

[0028] Figure 5 It is a diagram schematically showing the process flow of the third structural example of the implementation method.

[0029] Figure 6 It is a diagram schematically showing the process flow of the fourth structural example of the implementation method.

[0030] Figure 7 This is a diagram showing an example of a waveform group of measurement data before noise removal according to the embodiment.

[0031] Figure 8 This is a diagram showing an example of a waveform group of measurement data after noise removal according to the embodiment.

[0032] Fig. 9 This is a diagram showing an example of a waveform group of control data before noise removal according to the embodiment.

[0033] Fig.10 This is a diagram showing an example of a waveform group of control data after noise removal according to the embodiment.

[0034] Fig.11 This is a diagram showing an example of a waveform group of control data after preprocessing according to the embodiment.

[0035] Fig.12 It is a diagram showing an example of a waveform group of a PFA processing result according to the embodiment.

[0036] Fig.13 This is a diagram showing an example of a waveform of one channel before PFA processing according to the embodiment.

[0037] Fig.14 This is a diagram showing an example of a waveform of one channel of a PFA processing result according to the embodiment.

[0038] Fig.15 It is a diagram showing an example of a control period and a measurement period in PFA.

[0039] Fig.16 It is a diagram schematically showing the algorithm of PFA. DETAILED DESCRIPTION

[0040] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

[0041] [Measurement device]

[0042] Figure 1 1 is a diagram showing a schematic configuration of a measurement device 1 including an information processing device 21 according to the embodiment.

[0043] exist Figure 1 In FIG. 1 , for convenience of explanation, an XYZ orthogonal coordinate system is shown as a three-dimensional orthogonal coordinate system.

[0044] The measuring device 1 includes a plurality of L signal sensors A1 to AL, a plurality of M reference sensors B1 to BM, and an information processing device 21 .

[0045] exist Figure 1 In the example of FIG. 1 , the area where the signal sensors A1 to AL are arranged is schematically represented as the signal sensor arrangement portion 11 .

[0046] Furthermore, the measuring device may also be referred to as a measuring system, for example.

[0047] Here, in this embodiment, a case where L=16 and M=20 will be described as an example.

[0048] Furthermore, the number of the signal sensors A1 to AL may be any number greater than 2. In addition, in the present embodiment, a case where the number of the signal sensors A1 to AL is plural is shown, but the number of the signal sensor may be one.

[0049] The number of reference sensors B1 to BM may be any number greater than 2. In the present embodiment, a case where the number of reference sensors B1 to BM is plural is shown, but the number of reference sensors may be one.

[0050] exist Figure 1 3A and 3B also show a measurement object 31. The measurement object is also referred to as a measurement object or the like.

[0051] Any object may be used as the measurement object 31, for example, the whole or a part of a living being may be used. As a specific example, the measurement object 31 may be a human heart or a human brain.

[0052] Furthermore, when there are a plurality of signal sensors A1 to AL, for example, a device (for example, a signal sensor unit or the like) that integrally includes the plurality of signal sensors A1 to AL may be configured.

[0053] In addition, when there are a plurality of reference sensors B1 to BM, for example, a device (for example, a reference sensor unit, etc.) that integrally includes these plurality of reference sensors B1 to BM may be configured.

[0054] In addition, as another example, a device (for example, a sensor unit, etc.) may be configured to integrally include both the signal sensors A1 to AL and the reference sensors B1 to BM.

[0055] <Configuration of signal sensors>

[0056] exist Figure 1 In the example shown in FIG. 2 , the signal sensor arrangement portion 11 is a square surface area parallel to the XY plane.

[0057] exist Figure 1 In the example, inside the signal sensor configuration unit 11, 16 signal sensors A1 to A16 are arranged at equal intervals in a direction parallel to one side of the square (a direction parallel to the X-axis), and 16 signal sensors A1 to A16 are arranged at equal intervals in a direction perpendicular to the direction (a direction parallel to the Y-axis).

[0058] Specifically, four signal sensors A1 to A4 are arranged at equal intervals in a direction parallel to the Y axis, four signal sensors A5 to A8 are arranged at equal intervals in a direction parallel to the Y axis, four signal sensors A9 to A12 are arranged at equal intervals in a direction parallel to the Y axis, and four signal sensors A13 to A16 are arranged at equal intervals in a direction parallel to the Y axis.

[0059] In addition, four signal sensors A1, A5, A9, and A13 are arranged at equal intervals in a direction parallel to the X-axis, four signal sensors A2, A6, A10, and A14 are arranged at equal intervals in a direction parallel to the X-axis, four signal sensors A3, A7, A11, and A15 are arranged at equal intervals in a direction parallel to the X-axis, and four signal sensors A4, A8, A12, and A16 are arranged at equal intervals in a direction parallel to the X-axis.

[0060] exist Figure 1 In the example, the equal intervals in the direction parallel to the X-axis and the equal intervals in the direction parallel to the Y-axis are the same intervals. Figure 1 In the example of FIG. 1 , a plurality of signal sensors A1 to AL are arranged in an array.

[0061] These multiple signal sensors A1 to AL may also be called, for example, a sensor array or the like.

[0062] Here, the arrangement (overall arrangement) of the signal sensors A1 to AL is not particularly limited, and other arrangements may be adopted.

[0063] In addition, the arrangement (for example, position, direction) of each signal sensor A1 to AL is not particularly limited, and various arrangements may be adopted. Figure 1 In the example of FIG. 1 , the directions of the signal sensors A1 to AL are shown in the same manner, but the directions of the signal sensors A1 to AL may be arbitrary.

[0064] The term “signal sensor” is a name used for explanation, and the signal sensor may be called a measurement sensor, or (simply) a sensor, or other names.

[0065] <Configuration of measurement objects>

[0066] exist Figure 1 In the example of FIG. 1 , when projected onto the XY plane regardless of the positional deviation parallel to the Z axis, the measurement object 31 is arranged at the center of the signal sensor arrangement portion 11 (or in the vicinity thereof).

[0067] Here, the arrangement relationship between the measurement object 31 and the signal sensors A1 to AL is not particularly limited, and other arrangements may be adopted.

[0068] 〈Target Signal〉

[0069] Each signal sensor A1 to AL sets the desired signal (also referred to as the target signal for the sake of convenience) caused by the measurement object 31 as the object of measurement (detection). At this time, noise is superimposed on the target signal. Therefore, each signal sensor A1 to AL measures (detects) a signal in which the target signal and the noise are mixed (also referred to as the mixed signal for the sake of convenience). Then, each signal sensor A1 to AL obtains its measurement result (signal measurement result).

[0070] In addition, in this embodiment, for convenience of explanation, this mixed signal may be referred to as a measurement signal.

[0071] As the target signal, a signal of any physical quantity may be used, for example, a signal of magnetism, current, voltage, sound, light, or the like may be used.

[0072] In addition, as the target signal, for example, a signal caused by a living being (biological signal) may be used, or a signal caused by an object other than a living being may be used.

[0073] As a specific example, when the measurement object 31 is a human heart, a magnetic signal (magnetocardiogram signal) or an electrical signal (electrocardiogram signal) may be used as the target signal. As another specific example, when the measurement object 31 is a human brain, a magnetic signal may be used as the target signal.

[0074] In addition, as another example, the target signal may be used as sound and applied to a noise canceller of a speaker.

[0075] <noise>

[0076] Here, the noise is, for example, noise generated by a signal other than a target signal (interference signal), and may also be referred to as, for example, environmental noise.

[0077] As a specific example, the environmental noise may include the noise of the natural vibration of the jig of the sensor array (for example, an array composed of a plurality of signal sensors A1 to AL). This noise may be emphasized by human body movement (for example, heartbeat).

[0078] Furthermore, as a specific example, environmental noise may include noise originating from a power supply.

[0079] Furthermore, as a specific example, the environmental noise may include noise caused by the rotation of a fan of an air conditioner installed near the measuring device 1 (for example, the operation of a motor).

[0080] In the present embodiment, the information processing device 21 acquires control data including such environmental noise, and uses the control data to reduce the environmental noise component from the measurement signal (measurement data) by PFA.

[0081] 〈Refer to sensor configuration〉

[0082] exist Figure 1 In the example of FIG. 1 , the reference sensors B1 to B20 are arranged so as to surround the signal sensor arrangement portion 11 .

[0083] Specifically, six reference sensors B1 to B6 are arranged at equal intervals in a direction parallel to the Y axis on the negative side of the signal sensor arrangement portion 11 in a direction parallel to the X axis.

[0084] Furthermore, six reference sensors B6 to B11 are arranged at equal intervals in a direction parallel to the X-axis on the positive side of the signal sensor arrangement portion 11 in a direction parallel to the Y-axis.

[0085] Furthermore, six reference sensors B11 to B16 are arranged at equal intervals in a direction parallel to the Y axis on the positive side of the signal sensor arrangement portion 11 in a direction parallel to the X axis.

[0086] Furthermore, six reference sensors B16 to B20 and B1 are arranged at equal intervals in a direction parallel to the X axis on the negative side of the signal sensor arrangement portion 11 in a direction parallel to the Y axis.

[0087] exist Figure 1 In the example, the equal intervals in the direction parallel to the X-axis and the equal intervals in the direction parallel to the Y-axis are the same intervals. Figure 1 In the example of FIG. 1 , a plurality of reference sensors B1 to BM are arranged around signal sensors A1 to AL.

[0088] exist Figure 1 In the example of FIG. 1 , four reference sensors B2 to B5 parallel to the Y axis and each of four signal sensors A1 to A4 parallel to the Y axis are arranged at the same position on the Y axis.

[0089] Similarly, four reference sensors B12 to B15 parallel to the Y axis are arranged at the same positions on the Y axis as each of the four signal sensors A4 , A3 , A2 , and A1 parallel to the Y axis.

[0090] In addition, Figure 1 In the example of FIG. 1 , four reference sensors B7 to B10 parallel to the X-axis and four signal sensors A1 , A5 , A9 , and A13 parallel to the X-axis are arranged at the same positions on the X-axis.

[0091] Similarly, four reference sensors B17 to B20 parallel to the X-axis and each of four signal sensors A13 , A9 , A5 , and A1 parallel to the X-axis are arranged at the same position on the X-axis.

[0092] Here, the arrangement (overall arrangement) of the plurality of reference sensors B1 to BM is not particularly limited, and other arrangements may be adopted.

[0093] In addition, the configuration (for example, position, direction) of each reference sensor B1 to BM is not particularly limited, and various methods may be adopted. Figure 1 In the example of FIG. 1 , the directions of the reference sensors B1 to BM are shown in the same manner, but the directions of the reference sensors B1 to BM may be arbitrary.

[0094] In addition, the name "reference sensor" is a name for explanation, and it may be called other names such as noise sensor or (only) sensor.

[0095] 〈Reference Noise〉

[0096] Each of the reference sensors B1 to BM measures (detects) the noise (signal of the noise) superimposed on the target signal. Then, each of the reference sensors B1 to BM obtains its measurement result (noise measurement result).

[0097] In addition, in this embodiment, the case where each reference sensor B1~BM measures noise instead of measuring the component of the target signal is described, but as another example, a structure in which the result obtained by each reference sensor B1~BM measuring noise includes the component of the target signal to the extent that there is no practical obstacle can also be used.

[0098] Here, in the present embodiment, for convenience of description, the noise measured by the reference sensors B1 to BM is also referred to as reference noise, and the signal measured by the reference sensors B1 to BM is also referred to as a reference signal.

[0099] The reference noise may have, for example, a noise component common to the above-mentioned environmental noise, or may have a noise component different from the above-mentioned environmental noise.

[0100] As a specific example, when the target signal is a magnetic signal, the reference noise may also be noise caused by a geomagnetic signal. In addition, in this case, the reference noise may also be noise caused by a magnetic signal caused by a person or other object (e.g., a train, etc.) other than the measurement object.

[0101] Furthermore, as a specific example, when the target signal is an electrical signal, the reference noise may be electrical noise generated from other circuits in the vicinity of the measurement object 31 .

[0102] In addition, electrical signals and magnetic signals may also be collectively referred to as electromagnetic signals (electromagnetic waves) and processed, for example.

[0103] 〈Types of signal sensors and reference sensors〉

[0104] When a plurality of signal sensors A1 to AL are used, for example, all of them may be sensors of the same type (sensors that measure the same physical quantity), or may include sensors of different types (sensors that measure different physical quantities).

[0105] When a plurality of reference sensors B1 to BM are used, for example, all of them may be sensors of the same type (sensors that measure the same physical quantity), or may include sensors of different types (sensors that measure different physical quantities).

[0106] In addition, as each of the reference sensors B1 to BM, for example, a sensor of the same type as any of the signal sensors A1 to AL may be used, or a sensor of a different type from the signal sensors A1 to AL may be used.

[0107] As a specific example, when magnetic sensors are used as the signal sensors A1 to AL, magnetic sensors may be used as the reference sensors B1 to BM, or a combination of magnetic sensors and acceleration sensors may be used as the reference sensors B1 to BM.

[0108] 〈Connection between information processing device and each sensor〉

[0109] exist Figure 1 In the example of FIG. 1 , each of the signal sensors A1 to AL and the information processing device 21 are connected to each other in a wired or wireless manner so as to be communicable. Furthermore, the information processing device 21 can obtain measurement results (detection results) through each of the signal sensors A1 to AL.

[0110] In addition, each of the reference sensors B1 to BM and the information processing device 21 are connected to each other in a wired or wireless manner so as to be communicable. Furthermore, the information processing device 21 can acquire measurement results (detection results) through each of the reference sensors B1 to BM.

[0111] In addition, Figure 1 In the example of FIG. 1 , details of the connection between the information processing device 21 and each sensor (signal sensors A1 to AL and reference sensors B1 to BM) are omitted from the illustration.

[0112] Here, in this embodiment, the information processing device 21 obtains the measurement results of each sensor by communicating with each sensor (signal sensors A1~AL, reference sensors B1~BM), but as another example, the measurement results of each sensor can be temporarily stored in a removable storage medium and then output from the storage medium to the information processing device 21, thereby the information processing device 21 obtains the measurement results.

[0113] 〈Information processing device〉

[0114] Figure 2 It is a diagram showing a schematic configuration of an information processing device 21 according to an embodiment.

[0115] The information processing device 21 includes an input unit 111 , an output unit 112 , a storage unit 113 , and a control unit 114 .

[0116] The input unit 111 includes an acquisition unit 131 .

[0117] The output unit 112 includes a display unit 141 .

[0118] The control unit 114 includes a processing unit 151 and a display control unit 152 .

[0119] The input unit 111 receives input from the outside.

[0120] In this embodiment, the input unit 111 inputs the signal (measurement result signal) output from each sensor (signal sensor A1 to AL reference sensor B1 to BM). As a specific example, the input unit 111 may input the signal by receiving the signal sent from each sensor (signal sensor A1 to AL reference sensor B1 to BM), or may input the signal stored in the removable storage device from the storage device.

[0121] In addition, the input unit 111 may include, for example, an operation unit operated by a user, and may input information corresponding to the content of an operation performed by the user on the operation unit.

[0122] The acquisition unit 131 acquires a signal input from the input unit 111 .

[0123] The acquisition unit 131 may store the acquired signal in the storage unit 113 .

[0124] Here, when the signal input by the input unit 111 is an analog signal, for example, the acquisition unit 131 may include an A / D (Analog to Digital) conversion function to convert the signal from an analog signal to a digital signal.

[0125] In addition, when the information processing device 21 is used for real-time processing, the acquisition unit 131 acquires the signal in real time. In addition, even when the information processing device 21 is not used for real-time processing, the acquisition unit 131 can acquire the signal in real time.

[0126] Here, in this embodiment, the acquisition unit 131 has the function of acquiring signals measured by the signal sensors A1 to AL and the function of acquiring signals measured by the reference sensors B1 to BM, but as another example, these functions may be separately provided.

[0127] The output unit 112 performs output to the outside.

[0128] The display unit 141 displays and outputs information related to the signal processing result.

[0129] The display unit 141 has a screen such as a liquid crystal display (LCD) and displays and outputs information related to the signal processing result on the screen. As another configuration example, the display unit 141 may print and output information related to the signal processing result on paper.

[0130] Furthermore, the output unit 112 may have a function of outputting in other forms such as audio output.

[0131] The storage unit 113 includes a storage device such as a memory, and stores information.

[0132] The storage unit 113 stores information such as input signals and processing results of the signals.

[0133] In addition, the storage unit 113 stores information such as a control program, for example.

[0134] The control unit 114 performs various processes and various controls.

[0135] In the present embodiment, the control unit 114 includes a processor such as a CPU (Central Processing Unit), and the processor executes a control program stored in the storage unit 113 to perform various processes and various controls.

[0136] Furthermore, the processor includes a computing device for performing various calculations.

[0137] The processing unit 151 performs a predetermined process based on the signals of the measurement results of the signal sensors A1 to AL. In the present embodiment, the predetermined process is a process of reducing the component of the environmental noise contained in the mixed signal (measurement signal) of the target signal and the environmental noise.

[0138] Furthermore, the processing unit 151 may perform predetermined processing based on the signals of the measurement results of the signal sensors A1 to AL and the signals of the measurement results of the reference sensors B1 to BM.

[0139] In addition, in the present embodiment, the reduction of the specified object component may also be referred to as removal. In this case, as the degree of reduction (removal), for example, a method of completely eliminating the object component may be adopted, or a method of making the object component incomplete but effective in practicality may be adopted.

[0140] For example, as the degree of reducing the environmental noise component from the mixed presence signal (measurement signal), any degree that is practically effective can be used, that is, a method can be adopted to completely eliminate the environmental noise component from the mixed presence signal, or a method can be adopted to eliminate the environmental noise component from the mixed presence signal to a necessary extent.

[0141] The display control unit 152 displays and outputs various information on the screen of the display unit 141 .

[0142] In the present embodiment, the processing unit 151 performs processing using the PFA algorithm to remove the component of the environmental noise from a mixed signal (measurement signal) of the target signal and the environmental noise.

[0143] In this embodiment, for convenience of explanation, data including the environmental noise component may be referred to as control data.

[0144] 〈Timing and duration of control data〉

[0145] In the present embodiment, other timings (different timings) are used as the timing for measuring the measurement signal and the timing for measuring the environmental noise (control data).

[0146] In the present embodiment, this other timing refers to measuring the environmental noise (control data) during the period when the measurement signal is not measured. More specifically, the environmental noise (control data) can be measured during the period when the target signal is not measured (or, the level of the target signal is lower than a specified value). The specified value can also be set to a practically suitable value.

[0147] Furthermore, in this other timing method, the effect of reducing the environmental noise component can be improved by measuring the environmental noise that is the same as (or close to) the environmental noise contained in the measurement signal as control data. Therefore, for example, the timing of measuring the environmental noise (control data) can also be before or after the timing of measuring the measurement signal.

[0148] As a specific example, when measuring a magnetic signal caused by the heart of a person (the person being measured), the environmental noise (control data) can also be measured at a timing when the heart of the person is more than a predetermined distance away from the measurement position (a non-measurement state). At this timing, there is no target signal (in this example, the magnetic signal caused by the heart), or the level of the target signal is lower than a predetermined value, for example, the target signal is smaller than the environmental noise.

[0149] In the present embodiment, the “person to be measured” refers to a person (human) who is the object of measurement, and may also be referred to as a person to be measured, a subject, or the like.

[0150] The length of the period for measuring the environmental noise (control data) is not particularly limited, and may be, for example, the same length as that of the period for measuring the measurement signal, or may be a different length.

[0151] 〈Pre-treatment〉

[0152] The processing unit 151 may have a function of performing predetermined pre-processing on the control data.

[0153] As the pre-processing, for example, a process of emphasizing the component (the component of the environmental noise) to be removed from the measurement signal (measurement data) by PFA may be used. As a specific example, as the pre-processing, a filtering process of using a band pass filter (Band Pass Filter) having a frequency band that allows the component to pass may be used, that is, a filtering process of extracting the component may be used.

[0154] 〈Noise Removal Processing〉

[0155] The processing unit 151 may have a function of performing a predetermined noise removal process on the measurement signal (measurement data) using the measurement results of the reference sensors B1 to BM.

[0156] Furthermore, the processing unit 151 may have a function of performing a predetermined noise removal process on the control data using the measurement results of the reference sensors B1 to BM.

[0157] Here, as the noise removal process, for example, a process such as adaptive noise cancellation (ANC: Adaptive Noise Canceling) may be used (for example, refer to Non-Patent Document 3).

[0158] [Specific example of environmental noise removal processing]

[0159] Reference Figure 3 to Figure 6 A specific example of the environmental noise removal process performed by the information processing device 21 is shown.

[0160] In this embodiment, for the sake of convenience, the part that aggregates L signal sensors A1 to AL is referred to as the signal sensor part 331, the part that aggregates M reference sensors B1 to BM is referred to as the reference sensor part 332, and the part that aggregates the signal sensor part 331 and the reference sensor part 332 is referred to as the sensor part 311.

[0161] In addition, in a configuration example in which the reference sensors B1 to BM are not used, the reference sensor unit 332 (reference sensors B1 to BM) may not be provided.

[0162] Here, in this example, the signal sensor unit 331 (signal sensors A1 to AL) shares the measurement signal and the environmental noise signal. However, as another example, the measurement signal and the environmental noise signal may be partially or entirely different.

[0163] In this example, the reference sensor unit 332 (reference sensors B1 to BM) is common to the measurement signal and the environmental noise signal, but as another example, a part or all of the reference sensors may be different between the measurement signal and the environmental noise signal.

[0164] In addition, in this example, the signal sensor unit 331 and the reference sensor unit 332 are provided separately.

[0165] <Specific Example of Processing in First Configuration Example>

[0166] Figure 3 It is a diagram schematically showing the process flow of the first structural example of the embodiment.

[0167] exist Figure 3 , a sensor unit 311 including a signal sensor unit 331 and a processing unit 151 a including a signal processing unit 411 are shown.

[0168] In this example, the sensor unit 311 may not include the reference sensor unit 332 (reference sensors B1 to BM).

[0169] Here, the processing unit 151a is Figure 2 An example of the processing unit 151 is shown.

[0170] A specific example of the processing in this example will be described.

[0171] By measuring the measurement signal a1 by the signal sensor unit 331 , measurement data a11 which is data of the measurement signal a1 is obtained.

[0172] Furthermore, by measuring the environmental noise signal a2 by the signal sensor unit 331 at a timing different from the measurement of the measurement signal a1, the control data a12 which is the data of the environmental noise signal a2 is obtained.

[0173] Here, in this example, when the measurement signal a1 is measured by the signal sensor unit 331 , the state in which the measurement object 31 exists at a predetermined measurement position is maintained.

[0174] On the other hand, in this example, when the environmental noise signal a2 is measured by the signal sensor unit 331 , the state in which the measurement object 31 is not present at the predetermined measurement position is maintained.

[0175] In addition, as a state in which the measuring object 31 does not exist at the specified measurement position, for example, a state in which a signal component (component of the target signal) caused by the measuring object 31 is not included in the ambient noise signal a2 (control data a12), or a state in which even if the signal component is included in the ambient noise signal a2 (control data a12), the level of the signal component is lower than a specified value can be used.

[0176] The signal processing unit 411 performs PFA processing using the measurement data a11 and the control data a12 to reduce the environmental noise component included in the measurement data a11. Thus, a measurement signal (measurement data) with the environmental noise component reduced is obtained as a processed signal.

[0177] <Specific Example of Processing in Second Configuration Example>

[0178] Figure 4 It is a diagram schematically showing the process flow of the second structural example of the embodiment.

[0179] exist Figure 4 , a sensor unit 311 including a signal sensor unit 331 and a processing unit 151 b including a signal pre-processing unit 431 and a signal processing unit 432 are shown.

[0180] In this example, the sensor unit 311 may not include the reference sensor unit 332 (reference sensors B1 to BM).

[0181] Here, the processing unit 151b is Figure 2 An example of the processing unit 151 shown in FIG.

[0182] A specific example of the processing in this example will be described.

[0183] In this example, except that the structure of the processing unit 151b is different, it is the same as the first structural example, and the same reference numerals are attached to the same parts as the first structural example.

[0184] In this example, measurement data a11 and control data a12 are obtained in the same manner as in the first configuration example.

[0185] The signal pre-processing unit 431 performs predetermined pre-processing on the control data a12.

[0186] The signal processing unit 432 performs PFA processing using the measurement data a11 and the pre-processed control data a12 to reduce the environmental noise component included in the measurement data a11. Thus, a measurement signal (measurement data) with reduced environmental noise component is obtained as a processed signal.

[0187] exist Figure 4 In the second configuration example shown in FIG. 1 , the signal preprocessing unit 431 performs a predetermined preprocessing on the control data a12, thereby emphasizing the component of the environmental noise included in the control data a12. Therefore, for example, Figure 3 Compared with the first configuration example shown, the accuracy of reducing the environmental noise component by PFA can be improved.

[0188] <Specific example of processing of the third configuration example>

[0189] Figure 5 It is a diagram schematically showing the process flow of the third structural example of the implementation method.

[0190] exist Figure 5 , a sensor unit 311 including a signal sensor unit 331 and a reference sensor unit 332 , and a processing unit 151 c including a signal pre-processing unit 431 , a noise removal unit 451 , and a signal processing unit 452 are shown.

[0191] Here, the processing unit 151c is Figure 2 An example of the processing unit 151 is shown.

[0192] A specific example of the processing in this example will be described.

[0193] In this example, except for using a reference sensor unit 332 and a different structure of the processing unit 151c (mainly with respect to the measurement signal a1, having a noise removal unit 451), it is the same as the second structural example, and the same figure marks are given to the same parts as the second structural example.

[0194] In this example, similar to the second configuration example, the control data a12 is pre-processed by the signal pre-processing unit 431 .

[0195] The reference signal a3 correlated with the measurement signal a1 is measured by the reference sensor unit 332 .

[0196] Here, in this example, the reference signal a3 indicates a signal measured by the reference sensor unit 332 when the measurement signal a1 is measured by the signal sensor unit 331 .

[0197] The noise removal unit 451 performs noise removal processing (in the present embodiment, removes the reference noise component) on the measurement data based on the result (measurement data) of measuring the measurement signal a1 obtained by the signal sensor unit 331 and the result (reference data) of measuring the reference signal a3 obtained by the reference sensor unit 332, thereby obtaining the measurement data c11 after noise removal.

[0198] Here, various methods can be used as a method for removing noise, and for example, an ANC method can also be used.

[0199] The signal processing unit 452 performs PFA processing using the noise-removed measurement data c11 and the pre-processed control data a12 to reduce the environmental noise component contained in the measurement data c11. Thus, a measurement signal (measurement data) with reduced environmental noise components is obtained as a processed signal.

[0200] exist Figure 5 In the third configuration example shown, by performing a predetermined pre-processing on the control data a12 using the signal pre-processing unit 431, the environmental noise component included in the control data a12 is close to the environmental noise component included in the volume data c11. Figure 3 Compared with the first configuration example shown, the accuracy of reducing the environmental noise component by PFA can be improved.

[0201] In addition, Figure 5 In the third configuration example shown, the noise removal unit 451 removes noise from the measurement data, for example, Figure 4 Compared with the second configuration example shown in the figure, the accuracy of reducing the environmental noise component by PFA can be improved.

[0202] <Specific example of processing of the fourth configuration example>

[0203] Figure 6 It is a diagram schematically showing the process flow of the fourth structural example of the implementation method.

[0204] exist Figure 6 , a sensor unit 311 including a signal sensor unit 331 and a reference sensor unit 332 , and a processing unit 151 d including a noise removing unit 451 , a noise removing unit 471 , a signal pre-processing unit 472 , and a signal processing unit 473 are shown.

[0205] Here, the processing unit 151d is Figure 2 An example of the processing unit 151 is shown.

[0206] A specific example of the processing in this example will be described.

[0207] In this example, except that the structure of the processing unit 151d is different (mainly, regarding the environmental noise signal a2, it has a noise removal unit 471), it is the same as the third structure example, and the same figure marks are attached to the same parts as the third structure example.

[0208] In this example, the measurement data c11 after noise removal is obtained in the same manner as in the third configuration example.

[0209] The reference sensor unit 332 measures a reference signal a4 correlated with the environmental noise signal a2.

[0210] Here, in this example, the reference signal a4 indicates a signal measured by the reference sensor unit 332 when the environmental noise signal a2 is measured by the signal sensor unit 331 .

[0211] The noise removal unit 471 performs noise removal processing (in the present embodiment, removes the reference noise component) on the control data based on the result (control data) obtained by measuring the ambient noise signal a2 by the signal sensor unit 331 and the result (reference data) obtained by measuring the reference signal a4 by the reference sensor unit 332, thereby obtaining the control data d11 after noise removal.

[0212] Here, various methods can be used as a method for removing noise, and for example, an ANC method can also be used.

[0213] The signal pre-processing unit 472 performs predetermined pre-processing on the control data d11 after noise removal.

[0214] Here, as the pre-processing, for example, the same processing as that in the second structural example (and the third structural example) can be performed, or the same processing as that in the second structural example (and the third structural example) can be performed.

[0215] The signal processing unit 473 performs PFA processing using the noise-removed measurement data c11 and the noise-removed and pre-processed control data d11 to reduce the environmental noise component contained in the measurement data c11. As a result, a measurement signal (measurement data) with reduced environmental noise components is obtained as a processed signal.

[0216] exist Figure 6 In the fourth configuration example shown, the noise removal unit 471 removes noise from the control data, for example, Figure 5 Compared with the third configuration example shown in the figure, the accuracy of reducing the environmental noise component by PFA can be improved.

[0217] [Example of waveform]

[0218] Reference Figure 7 to Figure 14An example of a waveform of a signal processed by the information processing device 21 is shown.

[0219] exist Figure 7 to Figure 14 In the graphs shown respectively in , the horizontal axis represents time and the vertical axis represents level (for example, the unit of magnetic flux density is B [pT]).

[0220] In addition, each graph shown in these figures shows the tendency of each waveform, and is not necessarily strict.

[0221] In this case, it means Figure 6 An example of a waveform in the fourth structural example shown. In addition, Figure 3 to Figure 5 The trends of the waveforms in the first to third configuration examples shown are also the same.

[0222] Figure 7 This is a diagram showing an example of a waveform group 2011 of measurement data before noise removal according to the embodiment.

[0223] Figure 8 1 is a diagram showing an example of a waveform group 2021 of measurement data after noise removal according to the embodiment.

[0224] Fig. 9 This is a diagram showing an example of a waveform group 2111 of control data before noise removal according to the embodiment.

[0225] Fig.10 This is a diagram showing an example of a waveform group 2121 of control data after noise removal according to the embodiment.

[0226] Fig.11 This is a diagram showing an example of a waveform group 2131 of control data after preprocessing according to the embodiment.

[0227] Fig.12 This is a diagram showing an example of a waveform group 2211 of a PFA processing result according to the embodiment.

[0228] exist Figure 7 2 shows a waveform group 2011 of the result (measurement data) obtained by measuring the measurement signal a1 by the signal sensor unit 331. The waveform group 2011 is a waveform group before the noise removal unit 451 removes the noise.

[0229] The waveform group 2011 includes a plurality of (multiple channels) waveforms measured by a plurality of signal sensors A1 to AL and an average result of these plurality of waveforms.

[0230] exist Figure 8 2 shows a waveform group 2021 which is a result of noise removal by the noise removing unit 451 (measurement data c11 ).

[0231] Here, in this example, the waveform of the measurement data before noise removal contains large noise (for example, noise generated by the influence of geomagnetism, etc.), but the noise removal reduces the component of this noise.

[0232] exist Fig. 9 2 shows a waveform group 2111 of the result (control data) obtained by measuring the environmental noise signal a2 by the signal sensor unit 331. The waveform group 2111 is a waveform group before the noise removal unit 471 removes the noise.

[0233] The waveform group 2111 includes a plurality of (multiple channels) waveforms measured by a plurality of signal sensors A1 to AL and an average result of these plurality of waveforms.

[0234] exist Fig.10 2 shows a waveform group 2121 which is a result (control data d11) of noise removal by the noise removal unit 471. The waveform group 2121 is a waveform group before pre-processing by the signal pre-processing unit 472.

[0235] Here, in this example, the waveform of the control data before noise removal includes large noise caused by the influence of geomagnetism, etc., but the noise removal reduces the component of this noise.

[0236] exist Fig.11 2 shows a waveform group 2131 which is a result (control data) obtained by pre-processing by the signal pre-processing unit 472 .

[0237] Here, in this example, the waveform of the control data before preprocessing also includes, for example, noise components that are not reduced by PFA, and such noise components are reduced by preprocessing, that is, the noise components (ambient noise components) that are reduced by PFA are emphasized.

[0238] exist Fig.12 2 shows a waveform group 2211 of the result (processing completion signal) obtained by the signal processing unit 473 performing PFA.

[0239] Here, in Fig.13 and Fig.14 An example of a waveform of one channel is shown in FIG.

[0240] Fig.13 30 is a diagram showing an example of a waveform 3011 of one channel before PFA processing according to the embodiment.

[0241] Fig.14 FIG. 3 is a diagram showing an example of a waveform 3021 of one channel as a result of the PFA processing according to the embodiment.

[0242] exist Fig.14The waveform 3021 of the PFA processing result is shown. Fig.13 Compared with the waveform 3011 before PFA processing, the ambient noise component is reduced.

[0243] like Fig.13 and Fig.14 As shown in the example of FIG. 3 , the waveform 3011 before the PFA process includes fluctuation components, but the fluctuation components are reduced in the waveform 3021 after the PFA process.

[0244] <Control range of background technology>

[0245] In addition, in this embodiment, the control interval and the measurement interval are set to intervals of different timings. As a comparative example, in the background art, Fig.12 PFA is performed by setting control intervals on the left and right sides of the waveform of the measurement signal (here, the waveform of the measurement signal before PFA) as shown, that is, using data of a signal in a part of the measurement interval (ideally, an interval other than the target signal) as control data. However, in this background technology, the measurement data may be included in the control data, and sometimes the accuracy of PFA cannot be fully obtained.

[0246] On the other hand, in the present embodiment, the accuracy of the PFA process can be improved.

[0247] [Overview of PFA]

[0248] Here, refer to Figure 15-16 The outline of the data partitioning factor analysis (PFA) is described. The details of PFA are described in, for example, Non-Patent Document 1 and Non-Patent Document 2, especially p. 96-97.

[0249] PFA is an algorithm for removing interference signal components (in this embodiment, environmental noise components) from object signals (in this embodiment, measurement signals) by using a Bayesian factor analysis (BFA) algorithm twice, and estimating measurement object signals (in this embodiment, target signals). Details of Bayesian factor analysis are described in, for example, non-patent document 2, especially p.75-82, and non-patent document 4, especially p.65-72.

[0250] Fig.15 It is a diagram showing an example of a control period and a measurement period in PFA.

[0251] exist Fig.15 In the graph shown, the horizontal axis represents time, and the vertical axis represents level (for example, the unit of magnetic flux density, ie, B [pT]).

[0252] exist Fig.154 shows a waveform group 4011 of signals (target signals) that are the targets of PFA processing.

[0253] Waveform group 4011 includes waveforms of multiple channels.

[0254] exist Fig.15 An example of a control interval and an example of a measurement interval used in the PFA process are shown in FIG. The control interval, for example, refers to a data interval that contains only an interference signal (environmental noise) but does not contain a measurement object signal (target signal), but as another example, it may also contain a measurement object signal (target signal) at a level greater than 0 and lower than a specified value.

[0255] An example of a mathematical expression representing the PFA data model is shown.

[0256] [Number 1]

[0257] y k =Au k +Bv k +ε: measurement data

[0258] y k =Bv k +ε: Control data

[0259] Here,

[0260] Au k :Modeling of the measurement target signal (vector)

[0261] Bv k :Modeling of interference signals (vector)

[0262] ε: sensor noise (vector)

[0263] y k : Multi-channel sensor data (vector)

[0264] k: sensor channel number (=1, 2, ...)

[0265] A: Mixed ranks

[0266] B: Mixed rows and columns

[0267] Fig.16 It is a diagram schematically showing the algorithm of PFA.

[0268] In PFA, the processes of (step S1) to (step S3) are roughly performed in sequence.

[0269] In (step S1), the BFA algorithm is applied to the data of the control section to obtain a mixed matrix B with respect to the interference signal (in this embodiment, the environmental noise).

[0270] In (step S2), the BFA algorithm is applied to the data of the measurement interval to obtain the mixed array A and factor activity u k (Here, the u k It is a reference numeral with a horizontal bar on the upper side. ).

[0271] In (step S3), Au k (Here, the u k ) is obtained as a result of signal estimation.

[0272] In addition, PFA and SSP are compared. The details of SSP are described in Non-Patent Document 3, for example.

[0273] In SSP, noise and signal are separated using only spatial information. In addition, in SSP, each component (noise, signal) is separated as an orthogonal component (orthogonal complementary space).

[0274] On the other hand, in PFA, noise and signal are separated using both temporal and spatial information.

[0275] Therefore, PFA is effective also for signals whose noise source and signal source are close to each other (signals in the same spatial region), such as noise generated by vibration of a jig.

[0276] In addition, in PFA, noise and signal can be separated on an oblique basis. Therefore, in PFA, each component (noise, signal) can be separated more fully.

[0277] [About the above implementation methods]

[0278] As described above, the measuring device 1 of this embodiment includes a signal sensor unit 331 and a processing unit (in Figure 2 In the example, processing unit 151).

[0279] The signal sensor unit 331 includes one or more signal sensors (in the present embodiment, signal sensors A1 to AL) for acquiring signals, and measures a signal (measurement signal) in a state where a target signal and environmental noise exist in a mixed state.

[0280] The processing unit uses the measurement signal acquired by the signal sensor unit 331 as measurement data and the environmental noise signal acquired by the other signal sensor units 331 as control data to perform a process of removing the environmental noise component by PFA.

[0281] As a structural example, in the measurement device 1 of this embodiment, the signal sensor unit 331 includes one or more signal sensors (in this embodiment, signal sensors A1 to AL). The signal sensor unit 331 has a function of measuring a measurement signal in which a target signal and a first noise (in this embodiment, environmental noise) are mixed, and a function of detecting a first noise signal whose level of a component of the target signal is lower than a specified value and contains the first noise.

[0282] In addition, in the measuring device 1 of the present embodiment, the processing unit performs processing to reduce the first noise component contained in the measurement data through data partitioning factor analysis (PFA) based on the data of the measurement signal measured by the signal sensor unit 331, i.e., the measurement data, and the data of the first noise signal measured by the signal sensor unit 331, i.e., the control data.

[0283] Therefore, in the measurement device 1 of the present embodiment, it is possible to improve the accuracy of reducing the environmental noise component (here, the first noise component) in PFA.

[0284] In the measurement device 1 of the present embodiment, the processing unit performs preprocessing for emphasizing the environmental noise component to be removed on the acquired control data.

[0285] As one configuration example, in the measurement device 1 of the present embodiment, the processing unit performs pre-processing of emphasizing a component to be reduced on the control data before the data partitioning factor analysis (PFA).

[0286] Therefore, in the measurement device 1 of the present embodiment, it is possible to further improve the accuracy of reducing the environmental noise component in PFA.

[0287] In the measuring device 1 of the present embodiment, in addition to a signal sensor unit 331 having one or more signal sensors (in the present embodiment, signal sensors A1 to AL) for acquiring signals, it also has a reference sensor unit 332 having one or more reference sensors (in the present embodiment, reference sensors B1 to BM) for acquiring reference noise (prescribed noise).

[0288] The processing unit performs the previous stage of noise removal processing (noise removal processing) on ​​the measurement signal (measurement data) acquired by the signal sensor unit 331 based on the data acquired by the reference sensor unit 332 .

[0289] As a structural example, in the measurement device 1 of this embodiment, the reference sensor unit 332 includes one or more reference sensors (in this embodiment, reference sensors B1 to BM). The reference sensor unit 332 has a function of measuring a second noise signal (in this embodiment, a reference signal when measuring a measurement signal) containing a second noise.

[0290] Furthermore, in the measurement device 1 of the present embodiment, the processing unit performs processing to reduce the second noise component included in the measurement data based on the second noise signal measured by the reference sensor unit 332 before the data partitioning factor analysis (PFA).

[0291] Therefore, in the measurement device 1 of the present embodiment, it is possible to further improve the accuracy of reducing the environmental noise component in PFA.

[0292] In the measurement device 1 of the present embodiment, the processing unit performs the previous stage noise removal processing (noise removal processing) on ​​the control data acquired by the signal sensor unit 331 based on the data acquired by the reference sensor unit 332 .

[0293] As a configuration example, in the measurement device 1 of the present embodiment, the reference sensor unit 332 has a function of measuring a third noise signal including third noise (in the present embodiment, a reference signal when measuring an environmental noise signal).

[0294] Furthermore, in the measurement device 1 of the present embodiment, the processing unit performs processing to reduce the third noise component included in the control data based on the third noise signal measured by the reference sensor unit 332 before the data partitioning factor analysis (PFA).

[0295] Therefore, in the measurement device 1 of the present embodiment, it is possible to further improve the accuracy of reducing the environmental noise component in PFA.

[0296] In the measurement device 1 of the present embodiment, the reference sensor unit 332 includes one or more sensors of the same type as the signal sensor unit 331 or sensors of a different type.

[0297] As a configuration example, in the measurement device 1 of the present embodiment, at least one reference sensor included in the reference sensor unit 332 is a sensor of the same type as at least one signal sensor included in the signal sensor unit 331 .

[0298] Therefore, in the measuring device 1 of the present embodiment, appropriate types of sensors can be used as the signal sensor and the reference sensor.

[0299] As described above, in the measurement device 1 of the present embodiment, various environmental noise components (components of interference signals other than the target signal) can be removed with high accuracy in PFA.

[0300] In the measuring device 1 of the present embodiment, for example, with respect to noise that is difficult to remove in PFA, by using data acquired separately from the measurement signal (for example, data that does not include the target signal, or data that includes the target signal but at a low level, such as empty-room noise data) as control data, it is possible to remove the component of environmental noise from the measurement signal with high accuracy (high-accuracy noise removal).

[0301] Here, in the present embodiment, for example, the measurement data and the control data are separated more clearly than in the related art, and it is considered that the accuracy of removing the environmental noise component in the PFA becomes higher.

[0302] In addition, in the measurement device 1 of the present embodiment, for example, by pre-processing the control data to emphasize the environmental noise component to be removed, it is possible to achieve more accurate removal of the environmental noise component. As a specific example, in the present embodiment, by performing PFA on the result obtained by performing a predetermined pre-processing on the environmental noise signal as control data, the environmental noise component can be removed more effectively, including periodic noise.

[0303] Furthermore, the measurement device 1 of this embodiment includes, for example, a reference sensor for measuring reference noise (predetermined noise), and by combining a noise removal method such as ANC with PFA, environmental noise can be effectively removed, thereby achieving high-precision measurement.

[0304] Here, in this embodiment, for example, a measurement method may be adopted in which the person to be measured is not covered with a magnetic shield, or a measurement method may be adopted in which the person to be measured is covered with a magnetic shield. For example, in an environment where the external magnetic field is large, it is sometimes effective to reduce the external magnetic field using a magnetic shield.

[0305] In the present embodiment, for example, by providing reference sensors B1 to BM and using noise removal such as ANC in combination, PFA can be applied also to magnetic measurement in an external environment of a magnetic shield.

[0306] In addition, in the present embodiment, a case where the object to be measured is a person (a person to be measured) is shown, but as another example, the object to be measured may be an object other than a person.

[0307] In addition, the program for realizing the function of any structural part in any device described above can also be recorded in a computer-readable recording medium, so that the computer system reads and executes the program. In addition, the "computer system" mentioned here includes hardware such as an operating system or peripheral devices. In addition, "computer-readable recording medium" refers to removable media such as floppy disks, optical magnetic disks, ROMs, CD (Compact Disc)-ROM (Read Only Memory), and storage devices such as hard disks built into the computer system. Furthermore, "computer-readable recording medium" includes a medium that keeps the program for a certain period of time, such as a volatile memory inside a server or a computer system that becomes a client when sending a program via a network such as the Internet or a communication line such as a telephone line.

[0308] The volatile memory may be, for example, a RAM (Random Access Memory). The recording medium may be, for example, a non-transitory recording medium.

[0309] In addition, the above-mentioned program can also be transmitted from a computer system storing the program in a storage device, etc. to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the "transmission medium" for transmitting the program refers to a medium having the function of transmitting information, such as a network such as the Internet or a communication line such as a telephone line.

[0310] In addition, the above program may also be a program for realizing a part of the above functions. Furthermore, the above program may also be a so-called differential file that can realize the above functions by combining with a program already recorded in the computer system. The differential file may also be called a differential program.

[0311] In addition, the functions of any structural parts in any device described above can also be implemented by a processor. For example, each process in the embodiment can also be implemented by a processor that acts based on information such as a program, and a computer-readable recording medium that stores information such as a program. Here, the processor can, for example, implement the functions of each part by separate hardware, or it can also implement the functions of each part by integrated hardware. For example, the processor can also include hardware that includes at least one of a circuit for processing digital signals and a circuit for processing analog signals. For example, the processor can also be composed of one or more circuit devices mounted on a circuit substrate, or one or more circuit elements or both. As a circuit device, an IC (Integrated Circuit) or the like can also be used, and as a circuit element, a resistor or a capacitor or the like can also be used.

[0312] Here, the processor may be, for example, a CPU. However, the processor is not limited to the CPU, and various processors such as a GPU (Graphics Processing Unit) or a DSP (Digital Signal Processor) may also be used. In addition, the processor may be, for example, a hardware circuit based on an ASIC (Application Specific Integrated Circuit). In addition, the processor may be, for example, composed of a plurality of CPUs, or may be composed of a hardware circuit based on a plurality of ASICs. In addition, the processor may be, for example, composed of a combination of a plurality of CPUs and a hardware circuit based on a plurality of ASICs. In addition, the processor may also include, for example, one or more of an amplifier circuit or a filter circuit that processes analog signals.

[0313] As mentioned above, although the embodiment of this disclosure is described in detail with reference to drawings, the specific structure is not limited to this embodiment, and also includes the design etc. which do not deviate from the scope of the meaning of this disclosure.

[0314] [Notes]

[0315] (Configuration Example 1) to (Configuration Example 5) are shown.

[0316] (Structural Example 1)

[0317] A measuring device comprising:

[0318] a signal sensor unit including one or more signal sensors having a function of measuring a measurement signal in which a target signal and a first noise are mixed, and a function of detecting a first noise signal in which a level of a component of the target signal is lower than a predetermined value and includes the first noise; and

[0319] A processing unit, which performs processing to reduce the component of the above-mentioned first noise contained in the above-mentioned measurement data through data segmentation factor analysis based on the measurement data and the control data, the above-mentioned measurement data is the data of the above-mentioned measurement signal measured by the above-mentioned signal sensor unit, and the above-mentioned control data is the data of the above-mentioned first noise signal measured by the above-mentioned signal sensor unit.

[0320] (Structural Example 2)

[0321] According to the measuring device described in (Structural Example 1), wherein

[0322] The processing unit performs pre-processing on the control data to emphasize a component to be reduced from the measurement signal before the data splitting factor analysis.

[0323] (Structural Example 3)

[0324] The measuring device according to (Structural Example 1) or (Structural Example 2), wherein:

[0325] The device comprises: a reference sensor unit including one or more reference sensors and having a function of measuring a second noise signal including a second noise;

[0326] The processing unit performs a process of reducing a component of the second noise included in the measurement data based on the second noise signal measured by the reference sensor unit before the data splitting factor analysis.

[0327] (Structural Example 4)

[0328] According to the measuring device described in (Structural Example 3), wherein

[0329] The reference sensor unit has a function of measuring a third noise signal including a third noise.

[0330] The processing unit performs a process of reducing a component of the third noise included in the control data based on the third noise signal measured by the reference sensor unit before the data splitting factor analysis.

[0331] Here, the following structure may also be used.

[0332] (Structural Example 4A)

[0333] The measuring device according to (Structural Example 1) or (Structural Example 2), wherein:

[0334] The device comprises: a reference sensor unit including one or more reference sensors and having a function of measuring a third noise signal including a third noise;

[0335] The processing unit performs a process of reducing a component of the third noise included in the control data based on the third noise signal measured by the reference sensor unit before the data splitting factor analysis.

[0336] (Structural Example 5)

[0337] A measuring device according to (Structural Example 3) or (Structural Example 4), wherein:

[0338] At least one of the reference sensors included in the reference sensor unit is a sensor of the same type as at least one of the signal sensors included in the signal sensor unit.

[0339] Here, the following structure may also be used.

[0340] (Structural Example 5A)

[0341] A measuring device according to (Structural Example 3) or (Structural Example 4), wherein:

[0342] At least one of the reference sensors included in the reference sensor unit is a sensor of a different type from at least one of the signal sensors included in the signal sensor unit.

[0343] Description of Reference Numerals

[0344] 1 ... measuring device, 11 ... signal sensor configuration unit, 21 ... information processing device, 31 ... measurement object, 111 ... input unit, 112 ... output unit, 113 ... storage unit, 114 ... control unit, 131 ... acquisition unit, 141 ... display unit, 151, 151a to 151d ... processing unit, 152 ... display control unit, 311 ... sensor unit, 331 ... signal sensor unit, 332 ... reference sensor unit, 411, 432, 452, 473 ... signal processing unit Processing unit, 431, 472…signal pre-processing unit, 451, 471…noise removal unit, 2011, 2021, 2111, 2121, 2131, 2211, 4011…waveform group, 3011, 3021…waveform, A1~AL…signal sensor, B1~BM…reference sensor, a1…measurement signal, a2…environmental noise signal, a3, a4…reference signal, a11, c11…measurement data, a12, d11…control data

Claims

1. A measuring device, wherein: have: a signal sensor unit including one or more signal sensors having a function of measuring a measurement signal in which a target signal and a first noise are mixed, and a function of detecting a first noise signal in which a level of a component of the target signal is lower than a predetermined value and includes the first noise; as well as A processing unit, which performs processing to reduce the first noise component contained in the measurement data through data segmentation factor analysis based on measurement data and control data, wherein the measurement data is data of the measurement signal measured by the signal sensor unit, and the control data is data of the first noise signal measured by the signal sensor unit.

2. The measuring device according to claim 1, wherein: The processing unit performs pre-processing on the control data to emphasize a component to be reduced from the measurement signal before the data splitting factor analysis.

3. The measuring device according to claim 1 or 2, wherein: The device comprises: a reference sensor unit including one or more reference sensors and having a function of measuring a second noise signal including a second noise; The processing unit performs processing for reducing the second noise component included in the measurement data based on the second noise signal measured by the reference sensor unit before the data splitting factor analysis.

4. The measuring device according to claim 3, wherein: The reference sensor unit has a function of measuring a third noise signal including a third noise. The processing unit performs processing for reducing a third noise component included in the control data based on the third noise signal measured by the reference sensor unit before the data splitting factor analysis.

5. The measuring device according to claim 3, wherein: At least one of the reference sensors included in the reference sensor section is a sensor of the same type as at least one of the signal sensors included in the signal sensor section.

Images