Pulse wave assessment device, condition assessment device and pulse wave assessment method

Abstract

Pulse wave estimation device (1, 1a), comprising an image acquisition unit (11) for acquiring an image depicting a person, a skin area detection unit (12) for detecting a skin area of ​​the person from the image, a measurement range setting unit (13) for setting a measurement range in an area in the image corresponding to the skin area for extracting a pulse wave origin signal showing a luminance change, and a pulse wave origin signal extraction unit (14) for extracting a pulse wave origin signal based on the luminance change in the measurement range of the image, characterized by a simulation signal acquisition unit (15) for acquiring a simulation signal simulating the luminance change of the measurement range and estimating as the noise component of the luminance change in the measurement range, and a coefficient calculation unit (161).to calculate a coefficient to adjust the simulation signal such that, in a noise-suppressed signal, after suppression of the simulation signal in the pulse wave source signal, a signal for estimating the person's pulse wave remains; a noise suppression unit (162) to suppress the simulation signal multiplied by the coefficient in the pulse wave source signal; and an estimation unit (163) to estimate the person's pulse wave based on the noise-suppressed signal.

Description

Technical field The present disclosure relates to a pulse wave assessment device, a condition assessment device and a pulse wave assessment method. Background technology A technology is known in which a person's pulse wave is estimated non-contact based on a luminance signal of an area encompassing the person's skin in an image projected by an imaging device (hereinafter referred to as the "skin area"). This estimation is based on subtle luminance changes in the person's skin surface. A problem arises in that the precision of the pulse wave estimation decreases if the luminance signal of the skin area contains a signal that would otherwise result in noise. A technology is known that, conventionally, when a person's pulse wave is the object of pulse wave estimation (hereinafter referred to as the "test subject"), suppresses any signal from the luminance signal of the skin area that would otherwise become noise.For example, JP 2018 - 118 989 A discloses a pulse detection device by which specific frequency components obtained by a frequency analysis of position information of a face area in an imaging area are suppressed as noise in image signals from the face area. LIU, Xuenan, et al. in “Detecting pulse rates from facial videos recorded in unstable lighting conditions: An adaptive spatiotemporal homomorphic filtering algorithm” (IEEE Transactions on Instrumentation and Measurement, 2020, Vol. 70, pp. 1–15) describe a video-based method for determining pulse rates from facial images and focuses in particular on suppressing lighting disturbances. For this purpose, adaptive spatiotemporal homomorphic filtering is used, which separates temporal and spatial changes in illumination from pulse-induced skin color variations through logarithmic transformation and subsequent frequency-space filtering. A pulse wave analysis device using a moving image is also known from US 2018 / 256046 A1. JOHANSSON, Anders, et al. in “Pulse wave transit time for monitoring respiration rate” (Medical and Biological Engineering and Computing, 2006, Vol. 44, No. 6, p.471-478 ) deal with a fluctuation of heart rate in relation to respiration. Overview of the invention Problem to be solved by the invention However, in the prior art, for which the pulse detection device disclosed in JP 2018 - 118 989 A is representative, the problem is that, because a pulse wave signal included in the luminance signal of the skin area of ​​the test subject is also considered and suppressed as a noise component during noise suppression, the luminance signal of the skin area of ​​the test subject, which is to be used for the assessment of the pulse wave of the test subject, may not be extracted. The present disclosure serves to solve this problem and has the purpose of providing a pulse wave assessment device which prevents a situation in which, because a pulse wave signal included in the luminance signal of the skin area of ​​the test subject is also regarded as noise and suppressed during noise suppression, the luminance signal of the skin area of ​​the test subject, which is to be used for the assessment of the pulse wave of the test subject, cannot be extracted. Means of solving the task The object of the invention is achieved according to the invention by the subject matter of the independent claims. The dependent claims relate to further embodiments, and this description explains how the invention can be carried out. The pulse wave assessment device according to the present disclosure comprises an image acquisition unit that acquires an image depicting a person, a skin area detection unit that detects a skin area of ​​the person based on the image, a measurement area setting unit that sets a measurement area for extracting a pulse wave signal showing a luminance change in a region corresponding to the skin area in the image, a pulse wave origin signal extraction unit that extracts a pulse wave origin signal based on a luminance change in the measurement area of ​​the image, and a simulation signal acquisition unit.which acquires a simulation signal simulating the luminance change of the measurement range, which is estimated as the noise component of the luminance change in the measurement range; a coefficient calculation unit that calculates a coefficient to adjust the simulation signal such that, in a noise-suppressed signal, after suppressing the simulation signal in the pulse wave source signal, a signal remains for estimating the person's pulse wave; a noise suppression unit that suppresses the simulation signal multiplied by the coefficient in the pulse wave source signal; and an estimation unit that estimates the person's pulse wave based on the noise-suppressed signal. Effects of the invention According to the present disclosure, a situation can be prevented in which, by also considering and suppressing a pulse wave signal included in the luminance signal of the skin area of ​​the test subject as a noise component during noise suppression, the luminance signal of the skin area of ​​the test subject, which is to be used for the assessment of the pulse wave of the test subject, cannot be extracted. Brief explanation of the drawings [Fig. 1] Fig. 1 is a view showing a structural example of a state assessment device comprising a pulse wave assessment device according to a first embodiment. [Fig. 2] Fig. 2 is a view showing a structural example of the pulse wave assessment device according to the first embodiment. [Fig. 3] Fig. 3 is a view showing a detailed structural example of the pulse wave assessment device according to the first embodiment. [Fig. 4] Figs. 4A, 4B, and 4C are views illustrating examples of a method for setting a measurement range by the measurement range setting unit in the pulse wave assessment device according to the first embodiment. [Fig. 5] Fig. 5 is a flowchart illustrating the operation of the pulse wave assessment device according to the first embodiment. [Fig. 6] Fig. 6 is a flowchart illustrating in detail step ST6 in Fig. 5.[Fig. 7] Fig. 7 is a flowchart illustrating the operation of the state assessment device according to the first embodiment. [Fig. 8] Figs. 8A and 8B are views showing examples of the hardware setup of the pulse wave assessment device of the first embodiment. [Fig. 9] Fig. 9 is a view showing a structural example of a state assessment device comprising a pulse wave assessment device according to a second embodiment. [Fig. 10] Fig. 10 is a view showing a structural example of the pulse wave assessment device according to the second embodiment. [Fig. 11] Fig. 11 is a view showing an example of the distribution of ambient light, expressed by an ambient light model, in a single image for the second embodiment when the two-dimensional Gaussian distribution is used in the ambient light model. [Fig. 12] Fig.Figure 12 is a flowchart illustrating the operation of the pulse wave assessment device according to the second embodiment. [Figure 13] Figure 13 is a view illustrating the influence of ambient light on a signal used for pulse wave assessment of a test subject based on an image when the ambient light is unevenly distributed. Figure 13A is a view showing an example of an image mapped in a scene with uniform ambient light distribution, and Figure 13B is a view showing an example of an image mapped in a scene with uneven ambient light distribution. [Figure 14] Figure 14 is a view illustrating an example of a method for generating a simulation signal by a simulation signal generation unit based on a plurality of ambient light models in the second embodiment.[Fig. 15] Fig. 15 is a view showing, in the second embodiment, an example of a boundary rectangle of the measurement range and its central coordinates, and a representation of the distance between the vertex coordinates of a corner of the measurement range and the corresponding central coordinates. [Fig. 16] Fig. 16 is a view showing, in the second embodiment, an example of a first simulation signal and a second simulation signal, where the simulation signal generation unit has multiplied the signal by a normalization coefficient, thereby adjusting the difference to the correct order of magnitude. Forms for carrying out the invention The following section explains in detail the forms for carrying out the present revelation, using the figures as an example. First embodiment Fig. 1 is a view showing a structural example of a state assessment device 2 comprising a pulse wave assessment device 1 according to the first embodiment. The pulse wave assessment device 1 estimates the pulse wave of a person based on an image depicting that person. The person whose pulse wave is being assessed by the pulse wave assessment device 1 is referred to as the "test subject". The pulse wave assessment device 1 acquires an image consisting of a series of frames Im(k), depicting an area in which at least one skin region should be located (hereinafter referred to as the "skin presence area") at a predetermined frame rate Fr. Here, k represents a frame number assigned to the respective frames. For example, the frame assigned at the time following frame Im(k) is frame Im(k + 1). In the first embodiment, the skin area is an area corresponding to the test subject's face. This is merely an example, and the skin area can also be an area other than the test subject's face. For instance, the skin area can also be an area corresponding to a part of the face, such as the eyes, eyebrows, nose, mouth, forehead, cheeks, or chin. Furthermore, the skin area can also be an area corresponding to a body part other than the face, such as the test subject's head, shoulders, hands, neck, or legs. The skin area can also consist of multiple areas. The pulse wave assessment device 1 then estimates the test subject's pulse wave based on a series of frames Im(k - Tp + 1) to Im(k) per a specific frame rate Tp, and outputs a pulse wave assessment result P(t) representing the estimated pulse wave (hereinafter referred to as "pulse wave information"). Specifically, the pulse wave assessment device estimates the test subject's pulse wave by suppressing a signal that would otherwise become noise from a signal based on luminance changes in the test subject's skin area in the series of frames Im(k - Tp + 1) to Im(k). Here, t represents an output number assigned for each specific frame rate Tp. For example, the pulse wave assessment result assigned at the time following the pulse wave assessment result P(t) is the pulse wave assessment result P(5t + 1). The frame number k and the output number t are integers greater than or equal to 1. The frame rate Tp is an integer greater than or equal to 2. A signal used in the assessment of the test subject's pulse wave, representing luminance changes in the test subject's skin area, includes, in addition to a pulse wave-based signal, for example, a signal based on the test subject's movement or a signal based on ambient light illuminating the imaging area. These signals become noise, reducing the accuracy of the assessment of the test subject's pulse wave. The pulse wave assessment device 1 assesses the test subject's pulse wave based on the suppression of these signals, recognizing them as noise.In the first embodiment, a “movement of the test subject” that causes a luminance change in the image, considered noise with respect to the assessment of the test subject’s pulse wave, includes movement resulting from a shift in the test subject’s head position, movement resulting from a change in facial direction, expressive movement (e.g., a smiling face or a mouth moving while speaking), and movement due to a detection deviation of the area for extracting a signal showing a luminance change (measurement area, which is explained in detail below). In the first embodiment, the pulse wave assessment device 1 acquires a signal that becomes noise from devices outside the pulse wave assessment device 1 (omitted from the illustration in Fig. 1), such as various sensors.In the first embodiment, a signal that becomes noise during the assessment of the test subject's pulse wave is referred to as the "simulation signal". The "simulation signal" is a signal simulating a luminance change in the measuring range. The number of test subjects depicted in the illustration can be one person or several. For the sake of simplicity, the following explanation of the first embodiment will assume a single test subject depicted in the illustration. The state assessment device 2 acquires the pulse wave assessment result P(t) from the pulse wave assessment device 1 and assesses the state of the test subject. In the first embodiment, the state of the test subject is assumed to be, for example, either alert or inattentive. Based on the pulse wave assessment result P(t), the state assessment device 2 assesses the level of alertness, which represents the degree of the test subject's vigilance. The state assessment device 2 outputs state information Z(t) regarding the assessed state of the test subject to an output device 3. For example, if the level of alertness of the test subject has decreased, the state assessment device outputs state information Z(t) to the output device 3, expressing that the level of alertness of the test subject has decreased. Output device 3 outputs information based on the state information Z(t) output by state assessment device 2. Output device 3 is, for example, an audio output device. If state assessment device 2 outputs, for example, state information Z(t) indicating that the test subject's alertness level has decreased, output device 3 emits a warning tone to alert the test subject to a decrease in their level of attention. In the first embodiment, it is assumed, as an example, that the pulse wave assessment device 1, the condition assessment device 2, and the output device 3 are installed in a vehicle (not shown), and the test subject is the driver of the vehicle. That is, the pulse wave assessment device 1 assesses the pulse wave of the vehicle driver. Furthermore, the condition assessment device 2 assesses the driver's condition. Then, based on the driver's condition as assessed by the condition assessment device 2, the output device 3 emits a warning tone to the driver. Details of a structural example of the state assessment device 2 shown in Fig. 1 are described below, and first a structural example of the pulse wave assessment device 1 is explained in detail. Fig. 2 is a view showing a structural example of the pulse wave assessment device 1 according to the first embodiment. As shown in Fig. 2, the pulse wave assessment device 1 comprises an imaging unit 11, a skin area detection unit 12, a measurement range setting unit 13, a pulse wave origin signal extraction unit 14, a simulation signal acquisition unit 15, a pulse wave assessment unit 16 and an output unit 17. The pulse wave estimation unit 16 comprises, as shown in Fig. 3, a coefficient calculation unit 161, a noise suppression unit 162 and an estimation unit 163. Image Acquisition Unit 11 acquires an image depicting the test subject. More precisely, Image Acquisition Unit 11 acquires an image depicting the driver of the vehicle, captured by an imaging device (not shown) installed in the vehicle. The imaging device is mounted in such a way that it can image a skin area of ​​the driver. Image Acquisition Unit 11 outputs the acquired image to Skin Area Detection Unit 12. The imaging device of the first embodiment will now be explained. The imaging device comprises an imaging unit (not shown) and an illumination unit (not shown). The illumination unit comprises, for example, an LED (Light Emitting Diode). The illumination unit emits light into an imaging area of ​​the imaging unit. The imaging unit images the imaging area into which light was emitted by the illumination unit. The imaging unit can comprise one illumination unit or a plurality of illumination units. The skin area detection unit 12 detects a skin area of ​​the test subject based on the frame Im(k) included in the image acquired by the image acquisition unit 11. The skin area detection unit 12 can detect the skin area using a known method. For example, the skin area detection unit 12 can detect a skin area using a cascade-type facial sensor that uses hair-like feature sizes. The skin area detection unit 12 generates skin area information S(k) that represents the detected skin area. The skin area information S(k) can include information indicating the presence or absence of a skin area and information representing the position and size of a detected skin area in the image. In the first embodiment, a skin area is represented by a rectangular area in the image, and the skin area information S(k) includes information representing the position and size of the rectangular area in the image. Specifically, the skin area information S(k) represents, for example, the presence / absence of evidence of the test subject's face, the central coordinates Fc (Fcx, Fcy) of a rectangle enclosing the test subject's face in the image, and the width Fcw and height Fch of the rectangle, if the skin area corresponds to the test subject's face. The presence / absence of evidence of the test subject's face is expressed, for example, by "1" if evidence was possible and by "0" if it was not. Furthermore, the central coordinates of the rectangle surrounding the face are represented by the coordinate system of frame Im(k). In frame Im(k), the origin is in the upper left, the direction to the right in frame Im(k) is the positive direction of the x-axis, and the direction downwards in frame Im(k) is the positive direction of the y-axis. The skin area detection unit 12 outputs the generated skin area information S(k) to the measuring range setting unit 13. Based on the frame Im(k) of the image acquired by the image acquisition unit 11 and the skin area information S(k) output by the skin area detection unit 12, the measurement range setting unit 13 sets a plurality of measurement ranges within the image area of ​​frame Im(k) corresponding to the skin area represented by the skin area information S(k). This allows the unit to extract a pulse wave origin signal indicating luminance changes. The measurement range setting unit 13 can acquire the image acquired by the image acquisition unit 11 via the skin area detection unit 12. Once the plurality of measurement ranges has been set, the measurement range setting unit 13 generates measurement range information R(k), which represents the plurality of set measurement ranges.The measurement range information R(k) comprises information representing the position and size of Rn-piece (positive integer) measurement ranges in the diagram. The respective measurement ranges are defined as measurement ranges ri(k) (i = 1, 2, ..., Rn). In the first embodiment, the measurement range ri(k) is a quadrilateral, and the position and size of the measurement range ri(k) are represented in the diagram by the coordinate values ​​of the four vertices of the quadrilateral. Figures 4A, 4B, and 4C are views illustrating an example of a method for setting a measuring range using the measuring range setting unit 13 in the pulse wave assessment device 1 according to the first embodiment. Figure 4 illustrates an example of the method for setting a plurality of measuring ranges using the measuring range setting unit 13. First, as shown in Figs. 4A and 4B, the measuring range setting unit 13 detects orientation points of facial organs such as the outer corner of the eye, the inner corner of the eye, the nose, and the mouth within a skin area sr, which is represented by the skin area information S(k). These orientation points are represented by circles in Figs. 4A and 4B. A vector in which the measuring range setting unit 13 has stored the coordinate values ​​of the detected orientation points is specified as L(k). The measuring range setting unit 13 can detect the facial organs using a known method such as a model called a Constrained Local Model (CLM). Next, the measuring range setting unit 13 sets the vertex coordinates of the quadrilaterals of the measuring ranges ri(k) based on the proven orientation points. For example, the measuring range setting unit 13 sets the vertex coordinates of quadrilaterals as shown in Fig. 4C, setting the Rn-piece measuring ranges ri(k). To illustrate the setting of the measurement ranges ri(k) by the measurement range setting unit 13 in a section of the skin area sr corresponding to a cheek, the measurement range setting unit 13 selects an orientation point LA1 of the facial contour and an orientation point LA2 of the nose. The measurement range setting unit 13 can first select the orientation point LA2 of the nose, and then select the orientation point LA1 of the facial contour that is closest to the orientation point LA2 of the nose. The measuring range setting unit then sets 13 auxiliary orientation points a1, a2 and a3, so that a line segment between orientation point LA1 and orientation point LA2 is divided into four parts. Similarly, the measuring range setting unit 13 selects an orientation point LB1 of the facial contour and an orientation point LB2 of the nose. Furthermore, the measuring range setting unit 13 sets auxiliary orientation points b1, b2, and b3, so that a line segment between orientation point LB1 and orientation point LB2 is divided into four parts. Orientation points LB1 and LB2 can, for example, be selected as orientation points of the facial contour and the nose, respectively, that are adjacent to orientation points LA1 and LA2. The measuring range setting unit 13 sets a quadrilateral area encompassing the auxiliary orientation points a1, b1, b2, and a2 as measuring range R1. The auxiliary orientation points a1, b1, b2, and a2 each become the corner point coordinates corresponding to measuring range R1. Likewise, the measuring range setting unit 13 sets a measuring range R2 encompassing the auxiliary orientation points a2, b2, b3 and a3, and the corner point coordinates of the measuring range R2. An example of setting the measuring range ri(k) in the section corresponding to the cheek has been explained here, whereby the measuring range setting unit 13 also sets a measuring range ri(k) and corner point coordinates of the measuring range ri(k) with respect to a skin area sr of another section of the cheek and a section corresponding to the chin. Although this is not shown in Fig. 4C, the measuring range setting unit 13 can also set the measuring range ri(k) in a section corresponding to the forehead of the skin area sr of the test subject or in a section corresponding to the tip of the nose. The measuring range setting unit 13 outputs the generated measuring range information R(k) to the pulse wave origin signal extraction unit 14. The pulse wave origin signal extraction unit 14 extracts a pulse wave origin signal, based on frame Im(k) of the image acquired by the image acquisition unit 11 and the measurement range information R(k) output by the measurement range setting unit 13. This pulse wave origin signal shows luminance changes within a specified period, in other words, within a period corresponding to the frame rate Tp, from the individual or multiple measurement ranges ri(k) in frame Im(k), which are represented by the measurement range information R(k). The pulse wave origin signal is the source signal of a pulse wave. The pulse wave estimation device 1 uses the pulse wave origin signal to estimate the pulse wave of the test subject. The pulse wave estimation unit 16 performs this estimation. Details of the pulse wave estimation unit 16 are described below. The pulse wave origin signal extraction unit 14 can acquire the image acquired by the image acquisition unit 11 via the skin area detection unit 12 and the measurement range setting unit 13. Once the pulse wave origin signal has been extracted, the pulse wave origin signal extraction unit 14 generates pulse wave origin signal information W(t), which represents the extracted origin signal. The pulse wave origin signal information W(t) comprises information representing a pulse wave origin signal wi(t) extracted from the measurement range ri(k). The pulse wave origin signal wi(t), which consists of time series data for the Tp component, is extracted, for example, based on frames Im(k - Tp + 1), Im(k - Tp + 2), ..., Im(k) of a past Tp component and measurement range information R(k - Tp + 1), R(k - Tp + 2), ..., R(k). When extracting the pulse wave origin signal wi(t), the pulse wave origin signal extraction unit 14 calculates a luminance feature Gi(j) (j = k - Tp + 1, k - Tp + 2, ..., k) of the respective measurement range ri(k) for the respective frame Im(k) of the image. The luminance feature Gi(j) is a value calculated based on the luminance value in a frame Im(j) of the image for the respective measurement range ri(j). The luminance feature Gi(j) is an average or a standard deviation of the luminance value of the image elements included in the measurement range ri(j). In the first embodiment, the luminance feature Gi(j) is, by way of example, an average of the luminance value of the image elements included in the measurement range ri(j).The pulse wave origin signal extraction unit 14 sequences the luminance characteristic Gi(j) calculated for the respective frame Im(k) of the image into time series and determines this as the pulse wave origin signal wi(t). That is, the pulse wave origin signal extraction unit 14 determines the pulse wave origin signal wi(t) = [Gi(k - Tp + 1), Gi(k - Tp + 2), ..., Gi(k)]. The pulse wave origin signal extraction unit 14 generates the aggregated pulse wave origin signals wi(t) in the respective measurement range ri(k) as pulse wave origin signal information W(t). The pulse wave origin signal extraction unit 14 outputs the generated pulse wave origin signal information W(t) to the pulse wave assessment unit 16. The pulse wave origin signal wi(t) includes, in addition to the pulse wave and facial movement components described above, various noise components. For example, there are noise components due to a component defect in the imaging device. To suppress these noise components, filter processing as a pretreatment for the pulse wave origin signal wi(t) is desirable. For example, the pulse wave origin signal extraction unit 14 performs this filter processing. In filter processing, the pulse wave origin signal wi(t) is processed, for example, using a low-pass filter, high-pass filter, or band-pass filter. The following explanation describes the application of a band-pass filter. A Butterworth filter, for example, can be used as a band-pass filter. Desirable cutoff frequencies for the band-pass filter include, for example, a low cutoff frequency of 0.5 Hz and a high cutoff frequency of 5.0 Hz. The simulation signal acquisition unit 15 acquires from a device not shown outside the pulse wave estimation device 1 a simulation signal which simulates luminance changes of the measurement range in a specified period, in other words, in a period which corresponds to the frame rate Tp. The device outside the pulse wave assessment device 1, which serves as the acquisition source for the simulation signal, is hereinafter referred to as the "simulation signal acquisition source device." The simulation signal acquisition source device is, for example, a gyroscope that detects the movement of a vehicle or the movement of the test subject's face, or an illuminance sensor that detects the illuminance of the ambient light in the imaging area. The gyroscope and the illuminance sensor are installed in the vehicle. If, for example, the simulation signal acquisition device is a gyroscope, the simulation signal acquisition unit 15 acquires as a simulation signal a signal detected by the gyroscope representing the movement of the vehicle, or a signal representing the movement of the test subject's face. Since the location and detection range of the gyroscope and the location and imaging range of the imaging device are known in advance, it is possible to determine which measurement range on the image corresponds to the point where the gyroscope detected movement of the vehicle or the test subject's face. Furthermore, if the simulation signal acquisition device is, for example, an illuminance sensor that detects the brightness in the passenger compartment, the simulation signal acquisition unit 15 acquires as a simulation signal a signal detected by the illuminance sensor that represents the intensity of the ambient light. This assumes ambient light illuminating the imaging area uniformly. The simulation signal acquisition unit 15 acquires the measurement range information R(k) from the measurement range setting unit 13 and relates the signal acquired from the simulation signal acquisition source device to the plurality of measurement ranges ri(k). When the simulation signal acquisition unit 15 acquires a simulation signal from the simulation signal acquisition source device, it generates simulation signal information M(t) representing the acquired simulation signal. The simulation signal information M(t) comprises information representing a simulation signal mi(t) corresponding to the measurement range ri(k). The simulation signal mi(t) consists of time series data of the Tp component. For example, the simulation signal acquisition unit 15 acquires a simulation signal mi(t) corresponding to the time at which the frames Im(k - Tp + 1), Im(k - Tp + 2), ..., Im(k) of the previous Tp component are acquired. The simulation signal acquisition unit 15 can acquire the image acquired by the image acquisition unit 11 via the skin area detection unit 12 and the measurement range setting unit 13. The simulation signal acquisition unit 15 outputs simulation signal information M(t) to the pulse wave assessment unit 16. Based on the pulse wave origin signal information W(t) output by the pulse wave origin signal extraction unit 14 and the simulation signal information M(t) output by the simulation signal acquisition unit 15, the pulse wave assessment unit 16 estimates the test subject's pulse wave. That is, the pulse wave assessment unit 16 estimates the test subject's pulse wave based on the pulse wave origin signal wi(t) extracted by the pulse wave origin signal extraction unit 14 and the simulation signal mi(t) acquired by the simulation signal acquisition unit 15. Specifically, the pulse wave estimation unit 16 calculates a coefficient ci(t) based on the pulse wave origin signal information W(t) and the simulation signal information M(t) for multiplication with the simulation signal information M(t) (hereinafter referred to as the "suppression coefficient"), and estimates the pulse wave of the test subject based on a signal (hereinafter referred to as the "noise suppression signal") after suppressing the simulation signal mi(t), which has been multiplied by the suppression coefficient ci(t), as noise in the pulse wave origin signal wi(t). The pulse wave assessment unit 16 outputs a pulse wave assessment result P(t), as pulse wave information representing the assessed pulse wave, to the output unit 17. The pulse wave information could, for example, also consist of time-series data of the test subject's pulse wave, as assessed by pulse wave assessment unit 16, or of the test subject's pulse rate. For the sake of simplicity, it is assumed here that the pulse wave information refers to the test subject's pulse rate (number of beats per minute). Details of the procedure for assessing the pulse wave of the test subject by the pulse wave assessment unit 16 are explained. As described above, the pulse wave estimation unit 16 comprises the coefficient calculation unit 161, the noise reduction unit 162 and the estimation unit 163. The coefficient calculation unit 161 calculates coefficient information C(t) for the simulation signal information M(t) based on the pulse wave origin signal information W(t) and the simulation signal information M(t). The coefficient information C(t) is information regarding the suppression coefficient ci(t), which is used to adjust the magnitude of the simulation signal information M(t) that is suppressed as noise based on the pulse wave origin signal information W(t). Specifically, it is a signal used to adjust the simulation signal such that a noise suppression signal ei(t) remains in the pulse wave origin signal wi(t) after the simulation signal mi(t) has been suppressed, serving as a signal for assessing the test subject's pulse wave. In essence, the coefficient information C(t) is a signal that reduces the simulation signal. If the value of the coefficient information C(t) is large, the amount of simulation signal information M(t) that is suppressed as noise based on the pulse wave origin signal information W(t) becomes larger, and if the value of the coefficient information C(t) is small, the amount of simulation signal information M(t) that is suppressed as noise based on the pulse wave origin signal information W(t) becomes smaller. The coefficient calculation unit 161 calculates the coefficient information C(t) e.g. using the following formula (1): The coefficient calculation unit 161 calculates the coefficient information C(t) such that the difference between the pulse wave origin signal information W(t) and the result of the simulation signal information M(t) multiplied by the coefficient information C(t) is reduced. This allows the pulse wave estimation unit 16 to adjust the amount of simulation signal information M(t) contained in the pulse wave origin signal information W(t) by means of the coefficient information C(t). The adjustment of the amount of simulation signal information M(t) using the coefficient information C(t) is performed by the noise reduction unit 162. The coefficient calculation unit 161 outputs the calculated coefficient information C(t) to the noise suppression unit 162. The noise reduction unit 162 performs noise reduction based on the pulse wave origin signal information W(t), the simulation signal information M(t), and the coefficient information C(t). The noise reduction unit 162 then calculates noise reduction signal information E(t) as signal information after noise reduction. The noise reduction unit 162 calculates the noise reduction signal information E(t) using the following formula (2): Specifically, the noise reduction unit 162 first multiplies the simulation signal mi(t) by the suppression coefficient ci(t). Then, the noise reduction unit 162 calculates the noise reduction signal ei(t) by subtracting a signal resulting from the multiplication of the simulation signal mi(t) by the suppression coefficient ci(t) from the pulse wave origin signal wi(t). The noise reduction signal ei(t) is a signal that results from suppressing noise based on the luminance change in the measurement range ri(k). That is, the noise reduction unit 162 calculates the noise reduction signal ei(t) for the respective measurement range ri(k). Next, the noise reduction unit calculates 162 noise reduction signal information E(t) as the sum of the noise reduction signals ei(t) corresponding to the respective measurement ranges ri(k). The noise reduction unit 162 outputs the calculated noise reduction signal information E(t) to the assessment unit 163. The assessment device 163 estimates the test subject's pulse wave based on the noise reduction signal information E(t). Specifically, the assessment unit 163 performs a Fourier transform on the noise reduction signal information E(t) and calculates the peak frequencies in the frequency-power spectrum as the pulse rate. The assessment unit 163 determines information regarding the calculated pulse rate as the pulse wave assessment result P(t) in the form of pulse wave information, which represents the assessed pulse wave. The assessment unit 163 can also determine the noise suppression signal information E(t) as the pulse wave assessment result P(t). The pulse wave assessment unit 163 outputs the pulse wave assessment result P(t) to the output unit 17. The output unit 17 outputs the pulse wave assessment result P(t) output by the pulse wave assessment unit 16 to a pulse wave information acquisition unit 21 of the state assessment device 2. The functions of the output unit 17 can also be included by the pulse wave assessment unit 16. Next, a structural example of the condition assessment device 2 according to the first embodiment will be explained. As shown in Fig. 1, the state assessment device 2 comprises the pulse wave assessment device 1, the pulse wave information acquisition unit 21, a state assessment unit 22 and an output unit 23. The pulse wave information acquisition unit 21 acquires the pulse wave assessment result P(t) output by the pulse wave assessment device 1. The pulse wave information acquisition unit 21 outputs the acquired pulse wave assessment result P(t) to the state assessment unit 22. The state assessment unit 22 assesses the test subject's state based on the pulse wave assessment result P(t) output by the pulse wave information acquisition unit 21, in other words, the test subject's pulse wave assessed by the pulse wave assessment device 1. In the first embodiment, the state assessment unit 22 assesses the test subject's state based on the test subject's pulse rate assessed by the pulse wave assessment device 1. Specifically, the state assessment unit 22 assesses the driver's alertness level as the driver's state based on the test subject's pulse rate, in other words, the driver's state. For example, the alertness level is expressed by alertness levels of two stages (1: tired, 2: awake). For example, if the pulse wave information acquisition unit 21 outputs the pulse wave assessment result P(t), this is stored by the state assessment unit 22, which calculates a pulse rate of the test subject for 10 minutes after the start of driving as a reference pulse rate for that test subject based on the stored pulse wave assessment result P(t). The state assessment unit 22 can detect the start of driving, for example, by switching on the vehicle's power supply. Furthermore, the state assessment unit 22 can also detect the start of driving based on a signal from various sensors installed in the vehicle, such as a shift position sensor, etc. Generally, it is assumed that a person is in a waking state immediately after starting to drive. Therefore, the state assessment unit 22 calculates the test subject's pulse rate for 10 minutes after starting to drive as a reference pulse rate, which serves as the criterion for determining whether the person is awake. If the test subject's pulse rate has fallen below the reference pulse rate, it can be assessed that the test subject's level of alertness has decreased. The state assessment unit 22 assesses the test subject's level of alertness by comparing the pulse wave assessment result P(t) output by the pulse wave information acquisition unit 21—in other words, the test subject's pulse rate assessed by the pulse wave assessment device 1—with the reference pulse rate. If the test subject's pulse rate has decreased from the reference pulse rate by at least one predefined threshold (hereinafter referred to as the "decrease detection threshold"), the state assessment unit 22 detects a decrease in the alertness level, i.e., alertness level "1". In the first embodiment, the state assessment unit 22 calculated the reference pulse rate based on the pulse wave assessment result P(t) output by the pulse wave information acquisition unit 21; in other words, the pulse wave of the test subject assessed by the pulse wave assessment device 1. This is merely an example. For instance, a general pulse rate for a person's waking state can also be preset as the reference pulse rate and stored in the state assessment unit 22. The state assessment unit 22 then assesses the test subject's alertness based on the stored reference pulse rate.However, because the state assessment unit 22, as explained above, calculates the reference pulse rate of the test subject based on the pulse wave assessment result P(t) output by the pulse wave assessment device 1, an assessment of the test subject's level of alertness can be made taking into account individual differences. The state assessment unit 22 can also assess the test subject's state of alertness by combining a method for assessing the test subject's level of alertness based on the pulse wave assessment result P(t) with a known alertness assessment tool. A conceivable known alertness assessment tool is a method in which the level of alertness is assessed by detecting an increasing eye-closed time fraction. The state assessment unit 22 outputs state information Z(t) regarding the assessed state of the test subject to the output unit 23. The output unit 23 outputs the state information Z(t) issued by the state assessment unit 22 to the output device 3. The functions of the output unit 23 can also be encompassed by the state assessment unit 22. As described above, in the first embodiment, the state information Z(t) regarding the state of the test subject, as assessed by the state assessment unit 22, is output to the output device 3; this is merely an example. The state assessment unit 22 can, for example, also store the state information Z(t). In this case, it is not absolutely necessary for the state assessment device 2 to be connected to the output device 3. Furthermore, a setup is also possible in which the state assessment device 2 does not include the output unit 23. The operation of the pulse wave assessment device 1 according to the first embodiment is explained. Fig. 5 is a flowchart to explain the operation of the pulse wave assessment device 1 according to the first embodiment. The image acquisition unit 11 acquires an image on which the test subject is depicted (step ST1). The image acquisition unit 11 outputs the acquired image to the skin area detection unit 12. The skin area detection unit 12 detects a skin area of ​​the test subject (step ST2) based on the frame Im(k) included in the image acquired in step ST1 by the image acquisition unit 11. The skin area detection unit 12 generates skin area information S(k) that represents the detected skin area. The skin area detection unit 12 outputs the generated skin area information S(k) to the measuring range setting unit 13. Based on the frame Im(k) of the image acquired in step ST1 by the image acquisition unit 11 and the skin area information S(k) output in step ST2 by the skin area detection unit 12, the measurement range setting unit 13 sets a plurality of measurement ranges for extracting a pulse wave origin signal indicating luminance changes in the image area of ​​frame Im(k) corresponding to the skin area represented by the skin area information S(k) (step ST3). If the majority of measuring ranges have been set, the measuring range setting unit generates 13 measuring range information R(k), which represents the majority of set measuring ranges. The measuring range setting unit 13 outputs the generated measuring range information R(k) to the pulse wave origin signal extraction unit 14 and the simulation signal acquisition unit 15. The pulse wave origin signal extraction unit 14 extracts, based on the frame Im(k) of the image acquired in step ST1 by the image acquisition unit 11 and the measurement range information R(k) output in step ST3 by the measurement range setting unit 13, a pulse wave origin signal (step ST4) that shows luminance changes in a specified period, in other words, in a period corresponding to the frame rate Tp, of the individual or the plurality of measurement ranges ri(k) in the frame Im(k) represented by the measurement range information R(k). Once the pulse wave origin signal has been extracted, the pulse wave origin signal extraction unit generates 14 pulse wave origin signal information W(t), which represents the extracted origin signal. The pulse wave origin signal extraction unit 14 outputs the generated pulse wave origin signal information W(t) to the pulse wave assessment unit 16. The simulation signal acquisition unit 15 acquires a simulation signal (step ST5) from the simulation signal acquisition source device, which simulates luminance changes of the measurement range in a specified period, in other words, in a period which corresponds to the frame rate Tp. The simulation signal acquisition unit 15 determines a signal from the simulation signal acquisition source device that corresponds to the respective plurality of measurement ranges ri(k) represented by the measurement range information R(k), as a simulation signal, and summarizes the simulation signals in question as simulation signal information M(t). The simulation signal acquisition unit 15 outputs the simulation signal information M(t) to the pulse wave assessment unit 16. Based on the pulse wave origin signal information W(t) output by the pulse wave origin signal extraction unit 14 in step ST4 and the simulation signal information M(t) output by the simulation signal acquisition unit 15 in step ST5, the pulse wave estimation unit 16 estimates the pulse wave of the test subject (step ST6). The pulse wave assessment unit 16 outputs the pulse wave assessment result P(t), as pulse wave information representing the assessed pulse wave, to the output unit 17. The output unit 17 outputs the pulse wave assessment result P(t) issued by the pulse wave assessment unit 16 to the pulse wave information acquisition unit 21 of the state assessment device 2. The flowchart in Fig. 5 illustrates the processing sequence of step ST4, step ST5, but this is merely an example. The processing sequence of step ST4 and step ST5 can also be reversed, and the processing of step ST4 and step ST5 can also be carried out in parallel. Fig. 6 is a flowchart to explain in detail step ST6 in Fig. 5. The coefficient calculation unit 161 calculates coefficient information C(t) for the simulation signal information M(t) (step ST61) based on the pulse wave origin signal information W(t) output in step ST4 in Fig. 5 by the pulse wave origin signal extraction unit 14 and the simulation signal information M(t) output in step ST5 in Fig. 5 by the simulation signal acquisition unit 15. The coefficient calculation unit 161 outputs the calculated coefficient information C(t) to the noise suppression unit 162. Based on the pulse wave origin signal information W(t) output by the pulse wave origin signal extraction unit 14 in step ST4 in Fig. 5, the simulation signal information M(t) output by the simulation signal acquisition unit 15 in step ST5 in Fig. 5, and the coefficient information C(t) output by the coefficient calculation unit 161 in step ST61, the noise reduction unit 162 performs noise reduction (step ST62). Specifically, the noise reduction unit 162 calculates noise reduction signal information E(t) as signal information after noise reduction by subtracting a signal resulting from the multiplication of the simulation signal mi(t) by the suppression coefficient ci(t) from the pulse wave origin signal wi(t) (step ST62).The noise reduction unit 162 outputs the calculated noise reduction signal information E(t) to the assessment unit 163. In step ST62, the assessment device 163 estimates the test subject's pulse wave based on the noise reduction signal information E(t) (step ST63). Specifically, the assessment unit 163 performs a Fourier transform on the noise reduction signal information E(t) and calculates the peak frequencies in the frequency-power spectrum as the pulse rate. The pulse wave assessment unit 163 outputs the pulse wave assessment result P(t) to the output unit 17. The operation of the condition assessment device 2 according to the first embodiment is explained. Fig. 7 is a flowchart to explain the operation of the condition assessment device 2 according to the first embodiment. The pulse wave information acquisition unit 21 acquires the pulse wave assessment result P(t) (step ST11) output by the pulse wave assessment device 1. The pulse wave information acquisition unit 21 outputs the acquired pulse wave assessment result P(t) to the state assessment unit 22. The condition assessment unit 22 assesses the condition of the test subject based on the pulse wave assessment result P(t) output by the pulse wave information acquisition unit 21 in step ST11 (step ST12). The state assessment unit 22 outputs state information Z(t) regarding the assessed state of the test subject to the output unit 23. The output unit 23 outputs the state information Z(t) issued by the state assessment unit 22 to the output device 3. The luminance signal used to assess the test subject's pulse wave, based on luminance changes in the subject's skin area, comprises a luminance signal based on the subject's actual pulse wave and a signal that degenerates into noise. Therefore, assessing the test subject's pulse wave requires extracting a luminance signal based on the subject's actual pulse wave, rather than the signal that degenerates into noise, by suppressing the noise signal from the luminance signal based on skin area luminance changes.However, if the pulse wave signal included in the luminance signal of the test subject's skin areas is also considered noise during noise suppression and is suppressed, this leads to the suppression of the luminance signal based on the test subject's actual pulse wave, which is included in the luminance signal based on the skin area luminance changes, along with the signal that becomes noise. This creates a situation in which no sufficient luminance signal based on the test subject's actual pulse wave remains, nor is it possible to determine the magnitude of the luminance signal, thus preventing the test subject's pulse wave from being assessed. In contrast, in the pulse wave assessment device 1 according to the first embodiment, a pulse wave origin signal wi(t) is extracted, which is based on luminance changes in a measurement range ri(t) that has been set in a range corresponding to a skin area of ​​the test subject in the image, and a simulation signal mi(t) is acquired, which is assessed as the noise component of the luminance changes in the measurement range ri(t).Then, in the pulse wave assessment device 1, a suppression coefficient ci(t) is calculated, by which the simulation signal mi(t) is adjusted such that in the noise suppression signal ei(t) after the suppression of the simulation signal mi(t) in the pulse wave origin signal wi(t) a signal for the assessment of the test subject's pulse wave remains, and after the simulation signal mi(t) multiplied by the suppression coefficient ci(t) has been suppressed in the pulse wave origin signal wi(t), the pulse wave of the test subject is assessed based on the noise suppression signal ei(t). This prevents a situation in pulse wave assessment device 1 where, due to noise suppression, a pulse wave signal included in the luminance signal of the test subject's skin area is also considered noise and suppressed, thus preventing the extraction of the luminance signal of the test subject's skin area, which is intended for assessing the test subject's pulse wave. Therefore, pulse wave assessment device 1 allows the test subject's pulse wave to be assessed with high precision. In the foregoing first embodiment, the coefficient information C(t) was calculated by the coefficient calculation unit 161 in the pulse wave assessment device 1 using the formula (1) above. However, when the coefficient information C(t) is calculated by the coefficient calculation unit 161 using the formula (1) above, it is possible that the noise suppression signal information E(t) calculated by the noise suppression unit 162 using the formula (2) above may subsequently assume a value close to “0”. In the above first embodiment, the coefficient calculation unit 161 can therefore also calculate the coefficient information C(t) using the following formula (3). In formula (3), formula (1) was supplemented by the term λ || C(t) ||2, which reduces the degree of approximation of || C(t) M(t) - W(t) ||2an “0”. Because the coefficient calculation unit 161 calculates the coefficient information C(t) using formula (3), a situation in which a signal component required for assessing the pulse wave information is not retained in the noise reduction signal information E(t) subsequently calculated by the noise reduction unit 162 can be further reduced. The pulse wave assessment device 1 better prevents a situation in which, because a pulse wave signal included in the luminance signal of the test subject's skin area is also considered and suppressed as noise during noise reduction, the luminance signal of the test subject's skin area, which is to be used for assessing the test subject's pulse wave, cannot be extracted. Therefore, the pulse wave assessment device 1 allows the test subject's pulse wave to be assessed with high precision. Furthermore, in the aforementioned first embodiment of the pulse wave assessment device 1, a plurality of measurement ranges were set by the measurement range setting unit 13 in the image area of ​​frame Im(k), which corresponds to the skin area represented by the skin area information S(k), although this is merely an example. The measurement range setting unit 13 can also, for example, set only one measurement range. If only one measuring range is set using the measuring range setting unit 13, the preferred setting for this single measuring range is a skin area with minimal movement, such as mouth movement due to speaking or movement due to changes in expression. "Movements of a skin area" here refers not to movements resulting from a change in the head's position itself, but rather to "movements of a skin area" caused by factors other than a change in the head's position. If only one measuring range is set by the measuring range setting unit 13, it is, for example, preferred if this set measuring range is a skin area corresponding to a cheek or the forehead. However, if the skin area corresponding to the forehead is covered by forehead hair, etc., a skin area corresponding to the cheek is preferred instead. In the foregoing first embodiment, the pulse wave assessment device 1 is encompassed by the state assessment device 2, this being merely an example. The pulse wave assessment device 1 can also be provided outside the state assessment device 2 and connected to the state assessment device 2 outside the state assessment device 2. In the first embodiment described above, the illumination unit is encompassed by the imaging device; this is merely an example. For instance, the illumination unit can also be located outside the imaging device and emit light into the imaging area from outside the imaging device. Furthermore, in the aforementioned first embodiment, the test subject is the driver of a vehicle, although this is merely an example. The test subject could also be a passenger other than the driver of a vehicle. In the foregoing first embodiment, the pulse wave assessment device 1 and the condition assessment device 2 are onboard devices, and the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, the output unit 17, the pulse wave information acquisition unit 21, the condition assessment unit 22 and the output unit 23 are included by the onboard devices. Without limitation hereto, a system can also be formed by an onboard device and a server, in which the onboard device of the vehicle is equipped with part of the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, the output unit 17, the pulse wave information acquisition unit 21, the condition assessment unit 22 and the output unit 23, and the remainder are comprised of the server, which is connected to the onboard device in question via a network. Furthermore, the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, the output unit 17, the pulse wave information acquisition unit 21, the state assessment unit 22 and the output unit 23 can all be included by one server. The pulse wave assessment device 1 and the condition assessment device 2 according to the preceding first embodiment are not limited to onboard devices with which a vehicle is equipped, but can also be applied, for example, to electrical household appliances. Furthermore, the test subject is not limited to a single occupant of a vehicle, but can be several different people. As a concrete example, a television set up in the living room of an apartment could be equipped with pulse wave assessment device 1 and state assessment device 2. In this case, the test subject is a user, such as the resident of the apartment. Pulse wave assessment device 1 estimates the user's pulse wave based on an image projected by an imaging device built into the television. The imaging device should be able to image at least a portion of the test subject's skin presence. State assessment device 2, based on a pulse wave assessment result P(t) derived from the user's pulse wave as assessed by pulse wave assessment device 1, uses a rise or fall in the pulse rate to assess and record the user's physical condition. Figures 8A and 8B are views illustrating examples of the hardware setup of the pulse wave assessment device 1 of the first embodiment. In the first embodiment, the functions of the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, and the output unit 17 are implemented by a processing circuit 101. That is, the pulse wave assessment device 1 includes the processing circuit 101 to control the assessment of the test subject's pulse wave using an ambient light model. The processing circuit 101 can be special hardware as shown in Fig. 8A, but it can also be a processor 104 as shown in Fig. 8B, which executes programs stored in a memory. If the processing circuit 101 is a special piece of hardware, the processing circuit 101 corresponds, for example, to a simple circuit, a complex circuit, a programmed processor, parallel programmed processors, ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array) or a combination thereof. If the processing circuit is the processor 104, the functions of the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, and the output unit 17 are implemented by software, firmware, or a combination of software and firmware. The software or firmware is described as a program and stored in a memory 105. The processor 104 reads and executes programs stored in memory 105, thereby performing the functions of the imaging unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16 and the output unit 17.That is, when implemented by the processor 104, the pulse wave assessment device 1 includes the memory 105 for storing programs that are ultimately executed in steps ST1 to ST6 described above in Fig. 5. It can further be said that the programs stored in the memory 105 serve to execute the sequence or procedure of the processing operations of the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, and the output unit 17 on a computer. The memory 105 can be a non-volatile or volatile semiconductor memory such as, for example,It could be a RAM, a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable Read Only Memory) or an EEPROM (Electrically Erasable Programmable Read Only Memory), a magnetic disk, a floppy disk, an optical disk, a compact disc, a minidisk or a DVD (Digital Versatile Disc). The functions of the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, and the output unit 17 can also be implemented partly by special hardware and partly by software or firmware. For example, the processing circuit 101, as special hardware, can implement the functions of the image acquisition unit 11 and the output unit 17, and the functions of the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, and the pulse wave assessment unit 16 can be implemented by the processor 104 reading and executing programs stored in memory 105. Furthermore, the pulse wave assessment device 1 comprises an input interface device 102 and an output interface device 103 for performing wired or wireless communication with a device such as an imaging device, etc. The structures shown in Fig. 8A and Fig. 8B are examples of the hardware architecture of the state assessment device 2 according to the first embodiment. In the first embodiment, the functions of the pulse wave information acquisition unit 21, the state assessment unit 22, and the output unit 23 are implemented by means of the processing circuit 101. That is, the state assessment device 2 includes the processing circuit 101 to control the assessment of the test subject's condition based on the pulse wave information regarding the test subject's pulse wave, which was assessed by the pulse wave assessment device 1. If the processing circuit is the processor 104, the functions of the pulse wave information acquisition unit 21, the state assessment unit 22, and the output unit 23 are implemented by software, firmware, or a combination of software and firmware. The software or firmware is described as a program and stored in memory 105. The processor 104 reads and executes programs stored in memory 105, thereby performing the functions of the pulse wave information acquisition unit 21, the state assessment unit 22, and the output unit 23. That is, when executed by the processor 104, the state assessment device 2 includes memory 105 for storing programs that are ultimately executed in steps ST11 to ST12 as described above in Fig. 7.It can also be said that the programs stored in memory 105 are the sequence or a procedure for executing the pulse wave information acquisition unit 21, the state assessment unit 22 and the output unit 23 on a computer. The functions of the pulse wave information acquisition unit 21, the state assessment unit 22, and the output unit 23 can also be implemented partly by special hardware and partly by software or firmware. For example, the processing circuit 101, as special hardware, can implement the functions of the pulse wave acquisition unit 21 and the output unit 23, and the functions of the state assessment unit 22 can be implemented by the processor 104 reading and executing a program stored in memory 105. Furthermore, the condition assessment device 2 comprises the input interface device 102 and the output interface device 103 for carrying out wired or wireless communication with a device such as the pulse wave assessment device 1 or the output device 3. As stated above, the assembly of the pulse wave assessment device 1 according to the first embodiment comprises the image acquisition unit 11, which acquires an image depicting a person (test subject); the skin area detection unit 12, which detects a skin area of ​​the person based on the image; the measurement range setting unit 13, which sets the measurement range ri(k) in an area in the image corresponding to the skin area for extracting the pulse wave origin signal wi(t), which exhibits a luminance change; the pulse wave origin signal extraction unit 14, which extracts the pulse wave origin signal wi(t) based on a luminance change in the measurement range ri(k) of the image; and the simulation signal acquisition unit 15, which acquires a simulation signal mi(t) simulating the luminance change of the measurement range ri(k), which is considered a noise component. the change in luminance in the measurement range ri(k) is estimated,the coefficient calculation unit 161, which calculates a coefficient (suppression coefficient ci(t)) to adjust the simulation signal mi(t) such that in a noise suppression signal ei(t) after suppressing the simulation signal mi(t) in the pulse wave origin signal wi(t) a signal for estimating the person's pulse wave remains; the noise suppression unit 162, which suppresses the simulation signal mi(t) multiplied by the coefficient in the pulse wave origin signal wi(t); and the estimation unit 163, which estimates the person's pulse wave based on the noise suppression signal ei(t). The pulse wave assessment device 1 can therefore prevent a situation in which, due to the noise suppression, a pulse wave signal that is included in the luminance signal of the skin area of ​​the test subject is also considered a noise component and suppressed, thus altering the luminance signal of the skin area of ​​the test subject.The pulse wave used to assess the test subject's pulse wave cannot be extracted, thus preventing its extraction. Therefore, the pulse wave assessment device 1 allows for a high-precision assessment of the test subject's pulse wave. Furthermore, the condition assessment device 2, according to the preceding first embodiment, is designed to assess the condition of the test subject based on the pulse rate of the person (test subject) as assessed by the pulse wave assessment device 1 with the aforementioned design. Therefore, the condition assessment device 2 prevents a situation in which, due to noise suppression, a pulse wave signal included in the luminance signal of the test subject's skin area is also considered noise and suppressed, thus preventing the extraction of the luminance signal of the test subject's skin area, which is intended for assessing the test subject's pulse wave. In such a situation, the condition of the test subject can be assessed based on a pulse wave estimated with high precision. Therefore, the condition assessment device 2 can assess the condition of the test subject with high precision. Second embodiment In the first embodiment, the pulse wave assessment device acquires a simulation signal from the simulation signal acquisition source device. The second embodiment describes an embodiment in which the pulse wave assessment device generates a simulation signal. Fig. 9 is a view showing a structural example of the state assessment device 2, which includes a pulse wave assessment device 1a according to the second embodiment. In Fig. 9, for a structural example that is identical to the structural example of the condition assessment device 2, which was explained with reference to Fig. 1 in the first embodiment, the same reference numerals are provided and a duplicate explanation is omitted. The structural example of the state assessment device 2 shown in Fig. 9 differs from the structural example of the state assessment device 2, which was explained in the first embodiment with reference to Fig. 1, in the structural example of the pulse wave assessment device 1a, which is encompassed by the state assessment device 2. Fig. 10 is a view showing the structural example of the pulse wave assessment device 1a according to the second embodiment. In Fig. 10, for a structural example that is identical to the structural example of the pulse wave assessment device 1, which was explained with reference to Fig. 2 in the first embodiment, the same reference numerals are provided and a duplicate explanation is omitted. The structural example of the pulse wave assessment device 1a shown in Fig. 10 differs from the structural example of the pulse wave assessment device 1, which was explained in the first embodiment with reference to Fig. 2, in that it includes a simulation signal generation unit 18. The simulation signal generation unit 18 generates a simulation signal based on the frame Im(k) of the image acquired by the image acquisition unit 11 and the measurement range information R(k) output by the measurement range setting unit 13. This simulation signal simulates luminance changes of a measurement range within a predetermined period, in other words, within a period corresponding to the frame rate Tp. In the second embodiment, the measurement range setting unit 13 outputs the generated measurement range information R(k) to the pulse wave origin signal extraction unit 14 and the simulation signal generation unit 18. For example, the simulation signal generation unit 18 generates a simulation signal based on the frame Im(k) of the image, the measurement range information R(k) and an ambient light model, which simulates luminance changes of the measurement range that have occurred under the ambient light in a given period of time, in other words, in a period of time corresponding to the frame rate Tp, due to a change in the position of the measurement range. The simulation signal generation unit 18 generates the simulation signal for the respective plurality of measurement ranges ri(k), which are represented by the measurement range information R(k). The simulation signal generation unit 18 can acquire the image acquired by the image acquisition unit 11 via the skin area detection unit 12 and the measurement range setting unit 13. When the simulation signal generation unit 18 generates the simulation signal for the respective measurement ranges ri(k), simulation signal information M(t) adapted to the generated simulation signal is produced. The simulation signal information M(t) comprises information representing the simulation signal mi(t) generated for the measurement range ri(k). The simulation signal mi(t), which consists of time series data for the Tp component, is generated, for example, based on frames Im(k - Tp + 1), Im(k - Tp + 2), ..., Im(k) of a past Tp component, measurement range information R(k - Tp + 1), R(k - Tp + 2), ..., R(k), and the ambient light model. The simulation signal generation unit 18 is pre-equipped with the ambient light model. The ambient light model is a model of the distribution of ambient light that, based on the spatial luminance distribution in an area into which the ambient light is emitted, outputs values ​​that simulate luminance values ​​of coordinates in the image. For example, when the image is projected, the ambient light serves as illumination for the imaging unit of the imaging device. In this case, the illumination is emitted most intensely by the lighting unit near the center of the imaging area. In the image projected by the imaging unit, the luminance is strongest at the center and decreases from the center towards the outer edge of the image. In the second embodiment, the "center" is not strictly limited to the "center" but also essentially encompasses the center. For example, in the case of ambient light being emitted into an imaging area in order to create an image such that the center of the image is bright and the surroundings are dark, the ambient light model is the two-dimensional Gaussian distribution expressed in the following formula (4). q_(x, y) is a value simulating the luminance value at coordinates (x, y) in the image, where (x_c, y_c) are the central coordinates of the two-dimensional Gaussian distribution. a is a parameter that defines the height of the two-dimensional Gaussian distribution. σ is a parameter that defines the spread of the two-dimensional Gaussian distribution. The central coordinates of the two-dimensional Gaussian distribution are determined based on the spatial luminance distribution as the light emitted by the lighting unit is acquired by the acquiring unit. Fig. 11 is a view which, in the second embodiment, shows an example of the distribution of ambient light expressed by an ambient light model in an illustration image when the two-dimensional Gaussian distribution is used in the ambient light model. The ambient light model shown in Fig. 11 is an ambient light model for the case where the ambient light is illumination light from the illumination unit of the imaging device. The simulation signal generation unit 18 converts the coordinate values ​​(x, y) in the image, which includes the measurement ranges ri(k), into the simulation signal mi(t) using the ambient light model. When generating the simulation signal mi(t), the simulation signal generation unit 18 calculates the luminance value at the coordinates in the respective measurement ranges ri(k) for the respective frame Im(k) of the image using the ambient light model as a simulated value Vi(j) (j = k - Tp + 1, k - Tp + 2, ..., k). The simulation signal generation unit 18 arranges the Vi(j) calculated for the respective frame Im(k) of the image into time series and determines them as the simulation signal mi(t). That is, the simulation signal generation unit 18 determines the simulation signal mi(t) = [Vi(k - Tp + 1), Vi(k - Tp + 2), ..., Vi(k)]. The simulation signal generation unit 18 generates the combined simulation signals mi(t) in the respective measurement range ri(k) as simulation signal information M(t). In the preceding explanation, the ambient light model is the two-dimensional Gaussian distribution, but this is merely an example. Any model other than the two-dimensional Gaussian distribution can be used as the ambient light model. For example, the actually measured distribution of the illumination light can also be used as the ambient light model if the ambient light is the illumination light from the illumination unit of the imaging device. That is, there is no restriction to a model based on a formula; the ambient light model can also be generated based on values ​​obtained by actually measuring the brightness at each position in the image. Furthermore, the simulation signal generation unit 18 can calculate a simulation signal mi(t) for the measuring ranges ri(k), or for each of the coordinate points that possess the respective measuring ranges ri(k). In the second embodiment, it is specified that the simulation signal generation unit 18 calculates, as an example, a simulation signal mi(t) for the measuring ranges ri(k). The simulation signal generation unit 18 calculates, for example, a simulation signal mi(t) for the measuring range ri(k) using the centroid coordinate of a quadrilateral of the measuring range ri(k). The simulation signal generation unit 18 outputs the generated simulation signal information M(t) to the simulation signal acquisition unit 15. In the second embodiment, the simulation signal acquisition unit 15 acquires simulation signal information M(t) output by the simulation signal generation unit 18 and outputs the relevant simulation signal information M(t) to the pulse wave assessment unit 16. If the simulation signal generation unit 18 calculates simulation signals mi(t) for each of the coordinate points in the respective measurement ranges ri(k), the noise reduction unit 162 multiplies a coefficient corresponding to the number of simulation signals mi(t) calculated for a measurement range ri(k) (hereinafter referred to as the "simulation signal coefficient") by the respective simulation signals mi(t). The noise reduction unit 162 then subtracts from the pulse wave origin signal wi(t) a signal resulting from the multiplication of the simulation signal mi(t) by the suppression coefficient ci(t) after multiplication by the simulation signal coefficient. To give a concrete example, the simulation signal generation unit 18 sets, for example, the maximum value of the amplitude of the simulation signal mi(t) for each of the coordinate points in the respective measurement ranges ri(k) to mi_amp(t), and the maximum value of the amplitude of the pulse wave origin signal wi(t) to wi_amp(t). Here, the noise reduction unit 162 multiplies the simulation signal coefficient “wi_amp / mi_amp” by the respective simulation signals mi(t). Then, the noise reduction unit 162 subtracts the respective simulation signals mi(t) from the pulse wave origin signal wi(t) after multiplication by “wi_amp / mi_amp”. The operation of the pulse wave assessment device 1a according to the second embodiment is explained. Fig. 12 is a flowchart to explain the operation of the pulse wave assessment device 1a according to the second embodiment. The specific operation of steps ST21 to ST24 and step ST27 in Fig. 12 is identical to the specific operation of steps ST1 to ST4 and step ST6 in Fig. 5, which were explained in the first embodiment, so that a duplicate explanation is omitted. The simulation signal generation unit 18 generates a simulation signal based on the frame Im(k) of the image acquired in step ST21 by the image acquisition unit 11 and the measurement range information R(k) output in step ST23 by the measurement range setting unit 13, which simulates luminance changes of a measurement range in a specified period, in other words, in a period which corresponds to the frame rate Tp (step ST25). For example, based on the frame Im(k) of the image acquired in step ST21 by the image acquisition unit 11, the measurement range information R(k) output in step ST23 by the measurement range setting unit 13 and an ambient light model, the simulation signal generates a simulation signal that simulates luminance changes of the measurement range that have occurred under the ambient light in a specified period of time, in other words, in a period corresponding to the frame rate Tp, due to a change in the position of the measurement range. In step ST23, the measuring range setting unit 13 outputs the generated measuring range information R(k) to the pulse wave origin signal extraction unit 14 and the simulation signal generation unit 18. The simulation signal generation unit then generates 18 simulation signal information M(t) that is adapted to the simulation signal ri(k) generated for the respective measurement ranges. The simulation signal generation unit 18 outputs the generated simulation signal information M(t) to the simulation signal acquisition unit 15. The simulation signal generation unit 15 acquires the simulation signal information M(t) (step ST26) output by the simulation signal generation unit 18 in step ST25. The simulation signal acquisition unit 15 outputs the acquired simulation signal information M(t) to the pulse wave assessment unit 16. The flowchart in Fig. 12 shows the processing sequence of steps ST24 and ST25, but this is merely an example. The processing sequence of steps ST24 and ST25 can also be reversed, and steps ST24 and ST25 can also be processed in parallel. The operation of the condition assessment device 2 according to the second embodiment is the same as the operation explained in the first embodiment by means of the flowchart shown in Fig. 7, so that a duplicate explanation is omitted. In this way, for example, in the pulse wave assessment unit 1a, a simulation signal mi(t) can be generated based on the frame Im(k) of the image, the measurement range information R(k) and an ambient light model, which simulates luminance changes of the measurement range that have occurred under the ambient light in a given period of time, in other words, in a period which corresponds to the frame rate Tp, due to a change in the position of the measurement range.Then, in the pulse wave assessment device 1a, a suppression coefficient ci(t) is calculated, which adjusts the simulation signal mi(t) such that an assessment signal of the test subject's pulse wave remains in the noise-suppressed signal of the simulation signal mi(t) generated from the pulse wave origin signal wi(t), and after the simulation signal mi(t) multiplied by the suppression coefficient ci(t) has been suppressed in the pulse wave origin signal wi(t), the test subject's pulse wave is assessed based on the noise suppression signal ei(t) after the suppression. This prevents a situation in pulse wave assessment device 1a where, due to noise suppression, a pulse wave signal included in the luminance signal of the test subject's skin area is also considered noise and suppressed, thus preventing the extraction of the luminance signal of the test subject's skin area, which is intended for assessing the test subject's pulse wave. Therefore, pulse wave assessment device 1a allows for highly precise assessment of the test subject's pulse wave. Furthermore, in the aforementioned second embodiment, in the pulse wave assessment unit 1a, for example, as described above, a simulation signal mi(t) is generated based on the frame Im(k) of the image, the measurement range information R(k) and an ambient light model, which simulates luminance changes of the measurement range that have arisen under the ambient light in a given period of time, in other words, in a period which corresponds to the frame rate Tp, by a change in the position of the measurement range. Because the pulse assessment device 1a uses an ambient light model when generating the simulation signal, noise caused by the test subject's movement can be suppressed and the test subject's pulse wave can be assessed even in a scene with an uneven ambient light distribution in the image. This is explained in detail below. As described above, a method is known in which the pulse wave of a person is estimated without contact based on subtle luminance changes in a skin area of ​​a person in an image acquired by an imaging device. For example, a method is known in which, as in Reference Document 1 below, a plurality of measurement areas are set in a portrait of a test subject, a frequency-power spectrum of luminance signals acquired in the respective measurement areas is calculated, pulse waves corresponding to the peak frequencies of the frequency-power spectrum are synthesized, and the pulse rate is estimated based on the peak of the frequency-power spectrum of the synthesized pulse waves. [Reference document 1] Mayank Kumar, et al., “Distance PPG: Robust non-contact vital signs monitoring using a camera,” Biomedical optics express, 6 (5), 1565-1588, 2015 However, the method disclosed in Reference Document 1 has the problem that the precision in assessing the pulse waves decreases when the test subject's face moves. This is because, when the test subject's face moves, a component corresponding to the movement appears as a peak in the frequency-power spectrum, so that instead of a frequency component corresponding to the pulse wave, the component corresponding to the movement of the face is falsely detected as a pulse wave. As a measure against this problem, a technology is known, as described above, by which specific frequency components obtained through a frequency analysis of positional information of a face area within an imaging area are suppressed as noise from image signals of the face area. However, there may also be a scene in which the distribution of ambient light within the imaging area is uneven. For example, in an imaging device, the illumination light can be emitted most intensely by a lighting unit near the center of the imaging unit's field of view. As a result, the luminance of the image projected by the imaging unit is strongest in the center and decreases from the center towards the outer edge of the image. This means that the distribution of ambient light in the field of view is uneven. In a scene where the distribution of ambient light in the image area is uneven, the pulse wave, which is estimated based on subtle luminance changes in the skin of a test subject in the image, is influenced not only by changes in the position of the skin but also by ambient light. If this is not taken into account, there is a possibility that insufficient noise reduction will be achieved. Figure 13 is a view illustrating the effects of ambient light on a signal used for pulse wave assessment of a test subject based on an image when the ambient light is unevenly distributed. Figure 13A shows an example of an image displayed in a scene with uniform ambient light distribution. Figure 13B shows an example of an image displayed in a scene with uneven ambient light distribution. In Figures 13A and 13B, the images are labeled ImA and ImB, respectively. The color depth shown in Figures 13A and 13B represents a luminance distribution corresponding to the ambient light. Specifically, the lighter (whiter) the color, the higher the luminance, and the darker (blacker) the color, the lower the luminance. The illustration shows a test subject (SA in Fig. 13A and SB in Fig. 13B). For example, the test subject has moved their face, so that within a multiple frame (the frame of the test subject portion), the test subject's face moves sequentially from the top left to the right in Fig. 13. For simplicity, only one frame is shown in Fig. 13, and the movement of the test subject's face within this multiple frame is indicated by an arrow. As shown in Fig. 13A, in a scene with uniform ambient light, both a signal representing the position of the face and a signal representing the luminance of the face's surface are unaffected by the ambient light, even if the test subject moves their face; in other words, regardless of the test subject's face position in a multiple of frames of the images in temporal sequence. On the other hand, as shown in Fig.Figure 13B shows that, in a scene with uneven ambient light, a signal representing the position of the face is not affected by the ambient light, even when the test subject moves their face. However, a signal representing the luminance of the face's surface is affected by the ambient light as the test subject moves their face—in other words, as the position of the test subject's face changes in multiple frames of the image over time. The effect on the luminance of the test subject's face becomes stronger the closer the test subject's face is to the center of the image. In the pulse wave assessment unit 1a, a simulation signal mi(t) is generated based on the frame Im(k) of the image, the measurement range information R(k), and the ambient light model. This simulation signal mi(t) simulates luminance changes of the measurement range that occur under ambient light within a predefined period—in other words, within a period corresponding to the frame rate Tp—due to a change in the measurement range's position. The pulse wave assessment unit 1a then uses this generated simulation signal mi(t) for noise suppression. This allows the pulse assessment device 1a to suppress noise caused by a change in the position of the test subject's skin area, even in scenes with uneven ambient light distribution in the image, and thus accurately assess the test subject's pulse.Then the condition of the test subject can be assessed by the condition assessment device 2, even if it is a scene with an uneven distribution of ambient light in the imaging area. The preceding explanation assumed a single ambient light model, but multiple ambient light models are also possible. The simulation signal generation unit 18 can generate a simulation signal mi(t) and simulation signal information M(t) adapted to the respective simulation signal mi(t) using a plurality of ambient light models. In this case, the pulse wave estimation unit 16 calculates coefficient information C(t) for the plurality of ambient light models using formula (1), based on the pulse wave origin signal information W(t) and a plurality of simulation signal information M(t) generated by the simulation signal generation unit 18 using the plurality of ambient light models. The noise reduction unit 162 calculates the noise reduction signal information E(t) using the above formula by subtracting the plurality of simulation signal information M(t), multiplied by the coefficient information C(t), from the pulse wave origin signal information W(t). Fig. 14 is a view to illustrate an example of a method for generating a simulation signal mi(t) by the simulation signal generation unit 18 based on a plurality of ambient light models in the second embodiment. In Fig. 14, ImC represents an image produced by an imaging device in a vehicle during a nighttime journey; ImD represents an image produced by the imaging device in the vehicle during a daytime journey in an environment where light enters the imaging area in such a way that the luminance on the left side of the image is stronger; and ImE represents an image produced by the imaging device in the vehicle during a daytime journey in an environment where light enters the imaging area in such a way that the luminance on the right side of the image is stronger. Furthermore, Fig.Figure 81a is a figure representing the intensity distribution of light, expressed by the ambient light model, based on the ambient light in the state depicted by the image shown in ImC; Figure 81b is a figure representing the intensity distribution of light, expressed by the ambient light model, based on the state depicted by the image shown in ImD; and Figure 81c is a figure representing the intensity distribution of light, expressed by the ambient light model, based on the state depicted by the image shown in ImE. In Figures 81a, 81b, and 81c, the intensity of the ambient light is represented by the depth of the color, with a greater intensity being expressed as the lighter the color. For ease of understanding, Figure 14 illustrates the imaging unit (401 in Figure 14) and the illumination units (402 in Figure 14) encompassed by the imaging device. Furthermore, Figure 14 shows14 Dr. shows the face of the test subject, here the driver. For example, in the driving scene at night, the ambient light is exclusively illumination light emitted by the lighting units that comprise the imaging device. For example, in the daytime driving scene where light from outside the vehicle enters in such a way that the luminance on the left side of the image becomes stronger, the ambient light is light entering from outside the vehicle. Furthermore, in the daytime driving scene where light from outside the vehicle enters in such a way that the luminance on the right side of the image becomes stronger, the ambient light is light entering from outside the vehicle.For example, by means of a setup in which the simulation signal generation unit 18 is pre-equipped with a plurality of ambient light models corresponding to driving scenes at night and driving scenes during the day, and by means of the plurality of ambient light models a simulation signal mi(t) and simulation signal information M(t) are generated, the pulse wave estimation device 1a can suppress noise due to movement of the skin area of ​​the test subject and estimate the pulse wave of the test subject according to different scenes in which the distribution of the ambient light in the image is uneven. In the foregoing second embodiment, the simulation signal mi(t) was generated in the pulse wave assessment device 1a by the simulation signal generation unit 18 based on frames Im(k) in the image, measurement range information R(k) and ambient light models, this being only an example. The simulation signal generation unit 18 can, for example, also generate a signal that simulates luminance changes of the measurement range caused by position changes of the measurement range as a simulation signal mi(t) without using an ambient light model based on frames Im(k) in the image and measurement range information R(k). Here too, the pulse wave assessment device 1a prevents a situation in which, due to noise suppression, a pulse wave signal included in the luminance signal of the test subject's skin is also considered noise and suppressed, thus preventing the extraction of the luminance signal of the test subject's skin, which is intended for assessing the test subject's pulse wave. Therefore, the pulse wave assessment device 1a allows for highly precise assessment of the test subject's pulse wave. The movements of the test subject are not limited to left or right movements, but can also be forward or backward movements. In the second embodiment, the simulation signal generation unit 18 can therefore also generate the simulation signal mi(t) and simulation signal information M(t) adapted to the respective simulation signal mi(t), taking this into account. More precisely, the simulation signal generation unit 18 can also generate the simulation signal mi(t) based on a signal in which, for example, the magnitude of luminance changes in the measuring range ri(k) that occurred due to a left or right movement of the test subject and the magnitude of luminance changes in the measuring range ri(k) that occurred due to a forward or backward movement of the test subject have been normalized. The simulation signal generation unit 18 determines the simulation signal mi(t), which was generated by means of the method described in the preceding second embodiment, as the simulation signal mi(t) that simulates luminance changes of the measuring range ri(k) that have occurred due to a movement of the test subject to the left or right (hereinafter referred to as the “first simulation signal mi1(t)”). Apart from the first simulation signal mi1(t), the simulation signal generation unit 18 generates a simulation signal mi(t) that simulates luminance changes of the measuring range ri(k) that have occurred due to a movement of the test subject forwards or backwards (hereinafter referred to as the "second simulation signal mi2(t)"). The specific procedure by which the simulation signal generation unit 18 generates the second simulation signal mi2(t) is explained. The simulation signal generation unit 18 first calculates a boundary rectangle Rec(k) for all measurement ranges ri(k) and determines their central coordinate O(k) (x, y) = (xc, yc). The view on the upper side in Fig. 15 is an example showing the boundary rectangle Rec(k) of the measurement ranges ri(k) and their central coordinate O(k). The simulation signal generation unit 18 then calculates a distance Dis(k) between the respective corner coordinates of the respective measurement ranges ri(k) and the central coordinate O(k). For example, if the corner coordinates of a corner of a measurement range ri(k) are given as (x, y) = (xi_rb, yi_rb) and the corresponding distance between these and the central coordinate O(k) as Dis_i_rb, the simulation signal generation unit 18 calculates Dis_i_rb using the following formula (5). The view on the lower side of Fig. 15 is a graphical representation of the distance between the corner coordinates of a corner of a measurement range ri(k) and the corresponding central coordinate O(k). Then the simulation signal generation unit 18 determines the distance Dis(k) determined above between the corner coordinates of the respective measuring areas ri(k) and the central coordinate O(k) of the bounding rectangle Rec(k) as the second simulation signal mi2(t). In the example described above, the simulation signal generation unit 18 calculated the distance between the corner coordinates of the respective measurement ranges ri(k) and the central coordinate O(k) of the bounding rectangle Rec(k), and there is no limitation to this. For example, the simulation signal generation unit 18 can also calculate the distance between the centroid coordinates of the respective measurement ranges ri(k) and the central coordinate O(k) of the bounding rectangle Rec(k). Furthermore, in the example described above, the simulation signal generation unit 18 can also use an average value of the corner coordinates of the respective measurement ranges ri(k), or in other words, a centroid, instead of the central coordinate O(k) of the bounding rectangle Rec(k), and calculate a distance Dis(k) between this centroid and the corner coordinates of the respective measurement ranges ri(k). It is sufficient if the simulation signal generation unit 18 defines reference coordinates for the respective measurement ranges ri(k). Next, in the simulation signal generation unit 18, the first simulation signal mi1(t) and the second simulation signal mi2(t) are normalized by multiplying them by a coefficient (hereinafter referred to as the "normalization coefficient"). In other words, in the simulation signal generation unit 18, the difference in magnitude between the first simulation signal mi1(t) and the second simulation signal mi2(t) is adjusted by multiplying them by the normalization coefficient. For example, in the simulation signal generation unit 18, either the first simulation signal mi1(t) or the second simulation signal mi2(t) is multiplied by the normalization coefficient. Alternatively, in the simulation signal generation unit 18, both the first simulation signal mi1(t) and the second simulation signal mi2(t) can be multiplied by the normalization coefficient. The normalization coefficient can be a preset value, or the simulation signal generation unit 18 can calculate a normalization coefficient that adjusts to an average value of the order of magnitude of the first simulation signal mi1(t) and the second simulation signal mi2(t). Fig. 16 shows a view of the second embodiment, illustrating an example of the first simulation signal mi1(t) and the second simulation signal mi2(t), where the simulation signal generation unit 18 multiplies the signal by the normalization coefficient, thereby adjusting the difference to the correct order of magnitude. The simulation signal generation unit 18 then combines the first simulation signal mi1(t) and the second simulation signal mi2(t) after multiplication by the normalization coefficient to form the simulation signal mi(t). In this way, because the simulation signal generation unit 18 generates the simulation signal mi(t) based on a signal in which the magnitude of a signal, the luminance changes of the measuring range ri(k) that occurred due to a movement of the test subject to the left or right (first simulation signal mi1(t)), and the magnitude of a signal, the luminance changes of the measuring range ri(k) that occurred due to a movement of the test subject forward or backward (second simulation signal mi2(t)), have been normalized, noise due to position changes of the skin area of ​​the test subject can be suppressed and the pulse wave of the test subject can be assessed by the pulse wave assessment device 1a, even taking into account a movement of the test subject forward and backward. In the aforementioned second embodiment, the measuring range setting unit 13 can also be used to set only one measuring range. Furthermore, when generating a simulation signal from a plurality of measurement ranges set by the measurement range setting unit 13 in the pulse wave estimation device 1a, the simulation signal generation unit 18 can select a measurement range and generate a simulation signal only for the selected measurement range. In the aforementioned second embodiment, the pulse wave assessment device 1a comprises the state assessment device 2, although this is merely an example. The pulse wave assessment device 1a can also be provided outside of the state assessment device 2 and connected to the state assessment device 2 outside of the state assessment device 2. In the second embodiment described above, the illumination unit is encompassed by the imaging device; this is merely an example. For instance, the illumination unit can also be located outside the imaging device and emit light into the imaging area from outside the imaging device. Furthermore, in the second embodiment, the test subject can also be a different occupant than the driver of a vehicle. Furthermore, in the aforementioned second embodiment, the pulse wave assessment device 1a and the condition assessment device 2 are onboard devices, and the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, the output unit 17, the simulation signal generation unit 18, the pulse wave information acquisition unit 21, the condition assessment unit 22 and the output unit 23 are included by the onboard devices. Without limitation hereto, a system can also be formed by an onboard device and a server in which the onboard device of the vehicle is equipped with part of the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, the output unit 17, the simulation signal generation unit 18, the pulse wave information acquisition unit 21, the condition assessment unit 22 and the output unit 23, and the remainder are comprised of the server, which is connected to the onboard device in question via a network. Furthermore, the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, the output unit 17, the simulation signal generation unit 18, the pulse wave information acquisition unit 21, the state assessment unit 22 and the output unit 23 can all be included by one server. The pulse wave assessment device 1a and the condition assessment device 2 according to the second embodiment described above, like the pulse wave assessment device 1 and the condition assessment device 2 according to the first embodiment, are not limited to onboard devices with which a vehicle is equipped, but can also be applied, for example, to electrical household appliances. Furthermore, the test subject is not limited to a single occupant of a vehicle, but can be several different people. The hardware design of the pulse wave assessment device 1a according to the second embodiment is the same as the hardware design of the pulse wave assessment device 1 of the first embodiment explained by means of Fig. 8A and Fig. 8B. In the second embodiment, the functions of the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, the output unit 17, and the simulation signal generation unit 18 are implemented by the processing circuit 101. That is, the pulse wave assessment device 1a includes the processing circuit 101 to control the assessment of the test subject's pulse wave. The processing circuit 101 can be special hardware as shown in Fig. 8A, but it can also be the processor 104 as shown in Fig. 8B, which executes programs stored in a memory. The processing circuit 101 reads and executes the programs stored in memory 105, thereby performing the functions of the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, the output unit 17, and the simulation signal generation unit 18. That is to say, when implemented by the processing circuit 101, the pulse wave assessment device 1a includes memory 105 for storing programs that are ultimately executed in steps ST21 to ST27 as described above in Fig. 12.It can further be said that the programs stored in memory 105 serve to execute the sequence or procedure of the processing of the image acquisition unit 11, the skin area detection unit 12, the measurement range setting unit 13, the pulse wave origin signal extraction unit 14, the simulation signal acquisition unit 15, the pulse wave assessment unit 16, the output unit 17 and the simulation signal generation unit 18 on a computer. Furthermore, the pulse wave assessment device 1a includes the input interface device 102 and the output interface device 103 for carrying out wired or wireless communication with a device such as an imaging device, etc. As described above, the pulse wave assessment device 1a according to the second embodiment, in addition to the structure of the pulse wave assessment device 1 according to the first embodiment, includes the simulation signal generation unit 18, which generates the simulation signal mi(t). The pulse wave assessment device 1a therefore prevents a situation in which, because a pulse wave signal included in the luminance signal of the test subject's skin is also considered noise and suppressed during noise reduction, the luminance signal of the test subject's skin, which is to be used for assessing the test subject's pulse wave, cannot be extracted. Therefore, the pulse wave assessment device 1a allows the test subject's pulse wave to be assessed with high precision. In the present disclosure, an unrestricted combination of the respective forms of execution or any modification of a component of the respective forms of execution is possible, or any components of the respective forms of execution can be omitted. The following section summarizes various aspects of the present revelation as additions. (Addendum 1) Pulse wave estimation device comprising an image acquisition unit that acquires an image depicting a person, a skin area detection unit that detects a skin area of ​​the person based on the image, a measurement range setting unit that sets a measurement range in an area in the image corresponding to the skin area for extracting a pulse wave signal showing a luminance change, a pulse wave origin signal extraction unit that extracts a pulse wave origin signal based on a luminance change in the measurement range of the image, a simulation signal acquisition unit that acquires a simulation signal simulating the luminance change of the measurement range, which is estimated to be the noise component of the luminance change in the measurement range, and a coefficient calculation unit that calculates a coefficient to adjust the simulation signal accordingly.that in a noise-suppressed signal, after suppression of the simulation signal in the pulse wave origin signal, a signal for estimating the person's pulse wave remains; a noise suppression unit that suppresses the simulation signal multiplied by the coefficient in the pulse wave origin signal; and an estimation unit that estimates the person's pulse wave based on the noise-suppressed signal. (Addendum 2) Pulse wave assessment device of addition 1, characterized in that a simulation signal generation unit is included, by which the simulation signal is generated, and the simulation signal acquisition unit acquires the simulation signal that was generated by the simulation signal generation unit. (Addendum 3) Pulse wave assessment device of addition 2, characterized in that the simulation signal generation unit generates a signal as a simulation signal based on position changes of the measuring range, which simulates the luminance changes of the measuring range that have resulted from the position changes of the measuring range. [Addendum 4] Pulse wave assessment device of addition 2, characterized in that the simulation signal generation unit generates a signal as a simulation signal based on position changes of the measuring range and a model of the distribution of ambient light, which simulates the luminance changes of the measuring range caused by the position changes of the measuring range under the ambient light. [Addendum 5] Pulse wave assessment device of addition 4, characterized in that the ambient light is an irradiation light emitted by a lighting unit encompassed by the imaging device through which the image was created. [Addendum 6] Pulse wave estimation device of addition 4 or addition 5, characterized in that the simulation signal generation unit generates the simulation signal based on a plurality of different models of the distribution of ambient light, corresponding to situations in which the ambient light is emitted and changes in the position of the measuring range. [Addendum 7] Pulse wave estimation device of addition 2, characterized in that the simulation signal generation unit generates the simulation signal based on a signal in which the magnitude of a signal representing luminance changes of the measuring range that have occurred due to a movement of the person to the left or right, and the magnitude of a signal representing luminance changes of the measuring range that have occurred due to a movement of the person forward or backward, have been normalized. [Addendum 8] Condition assessment device, comprising a condition assessment unit that assesses the condition of the person based on the pulse wave of a person assessed by a pulse wave assessment device of one of the additions 1 to 7. [Addendum 9] Condition assessment device according to supplement 8, characterized in that the condition assessment unit assesses the alertness of the person as the condition of the person. [Addendum 10] State assessment device according to addition 9, characterized in that the state assessment unit calculates a reference pulse rate based on the pulse wave of the person assessed by the pulse wave assessment device in a state in which the person is presumed to be alert, and assesses the level of alertness of the person by comparing the pulse wave assessed by the pulse wave assessment device with the reference pulse rate. [Addendum 11] Pulse wave estimation procedure, comprising a step in which an image acquisition unit acquires an image depicting a person, a step in which a skin area detection unit detects a skin area of ​​the person based on the image, a step in which a measurement range setting unit, in an area in the image corresponding to the skin area, sets a measurement range for extracting a pulse wave signal showing a luminance change, a step in which a pulse wave origin signal extraction unit extracts a pulse wave origin signal based on a luminance change in the measurement range of the image, a step in which a simulation signal acquisition unit acquires a simulation signal simulating the luminance change of the measurement range, which is estimated to be the noise component of the luminance change in the measurement range, a stepin which a coefficient calculation unit calculates a coefficient to adjust the simulation signal such that, in a noise-suppressed signal after suppression of the simulation signal in the pulse wave source signal, a signal remains for estimating the person's pulse wave; a step in which a noise suppression unit in the pulse wave source signal suppresses the simulation signal multiplied by the coefficient; and a step in which an estimation unit estimates the person's pulse wave based on the noise-suppressed signal. Industrial application area The pulse wave assessment device according to the present disclosure can prevent a situation in which, because a pulse wave signal included in the luminance signal of the skin area of ​​the test subject is also considered as noise and suppressed during noise suppression, the luminance signal of the skin area of ​​the test subject, which is to be used for assessing the pulse wave of the test subject, cannot be extracted. Explanation of reference symbols 1, 1a Pulse wave estimation device 11 Image acquisition unit 12 Skin area detection unit 13 Measurement range setting unit 14 Pulse wave origin signal extraction unit 15 Simulation signal acquisition unit 16 Pulse wave estimation unit 161 Coefficient calculation unit 162 Noise reduction unit 163 Estimation unit 17 Output unit 18 Simulation signal generation unit 2 State estimation device 21 Pulse wave information acquisition unit 22 State estimation unit 23 Output unit 3 Output device 401 Imaging unit 402 Illumination unit 101 Processing circuit 102 Input interface device 103 Output interface device 104 Processor 105 Memory

Claims

Pulse wave estimation device (1, 1a), comprising an image acquisition unit (11) for acquiring an image depicting a person, a skin area detection unit (12) for detecting a skin area of ​​the person from the image, a measurement range setting unit (13) for setting a measurement range in an area in the image corresponding to the skin area for extracting a pulse wave origin signal showing a luminance change, and a pulse wave origin signal extraction unit (14) for extracting a pulse wave origin signal based on the luminance change in the measurement range of the image, characterized by a simulation signal acquisition unit (15) for acquiring a simulation signal simulating the luminance change of the measurement range and estimating as the noise component of the luminance change in the measurement range, and a coefficient calculation unit (161).to calculate a coefficient to adjust the simulation signal such that, in a noise-suppressed signal, after suppression of the simulation signal in the pulse wave source signal, a signal for estimating the person's pulse wave remains; a noise suppression unit (162) to suppress the simulation signal multiplied by the coefficient in the pulse wave source signal; and an estimation unit (163) to estimate the person's pulse wave based on the noise-suppressed signal. Pulse wave assessment device (1, 1a) according to claim 1, further comprising a simulation signal generation unit (18) to generate the simulation signal, wherein the simulation signal acquisition unit (15) acquires the simulation signal generated by the simulation signal generation unit (18). Pulse wave assessment device (1, 1a) according to claim 2, wherein the simulation signal generation unit (18) generates a signal as a simulation signal based on position changes of the measuring range, which simulates the luminance changes of the measuring range caused by the position changes of the measuring range. Pulse wave assessment device (1, 1a) according to claim 2, wherein the simulation signal generation unit (18) generates a signal, based on the position changes of the measuring area and a distribution model of ambient light in an imaging area, which simulates the luminance changes of the measuring area under the ambient light caused by the position changes of the measuring area, as the simulation signal. Pulse wave assessment device (1, 1a) according to claim 4, wherein the ambient light is an irradiation light emitted by an illumination unit included in the imaging device by which the image was created. Pulse wave assessment device (1, 1a) according to claim 4, wherein the simulation signal generation unit (18) generates the simulation signal based on a plurality of different distribution models of ambient light, corresponding to situations in which the ambient light is emitted and the position changes of the measuring range. Pulse wave assessment device (1, 1a) according to claim 2, wherein the simulation signal generation unit (18) generates the simulation signal based on a signal in which the magnitude of a signal representing the luminance changes of the measurement range caused by a left or right movement of the person and the magnitude of a signal representing the luminance changes of the measurement range caused by a forward and backward movement of the person have been normalized. Condition assessment device (2) comprising a condition assessment unit (22) for assessing the condition of the person based on the pulse wave of a person assessed by a pulse wave assessment device (1, 1a) according to any one of claims 1 to 7. State assessment device (2) according to claim 8, wherein the state assessment unit (22) assesses the state of the person as a level of alertness of the person. State assessment device (2) according to claim 9, wherein the state assessment unit (22) calculates a reference pulse rate based on the pulse wave of the person assessed by the pulse wave assessment device in a state in which the person is presumed to be alert, and assesses the level of alertness of the person by comparing the pulse wave assessed by the pulse wave assessment device with the reference pulse rate. Pulse wave estimation procedure comprising a step of acquisition, by an image acquisition unit (11), of an image depicting a person; a step of detection, by a skin area detection unit (12), of a skin area of ​​the person based on the image; a step of setting, by a measurement range setting unit (13), of a measurement range for extracting a pulse wave origin signal exhibiting a luminance change in an area corresponding to the skin area in the image; and a step of extraction, by a pulse wave origin signal extraction unit (14), of the pulse wave origin signal based on the luminance change in the measurement range of the image, characterized by a step of acquisition, by a simulation signal acquisition unit (15), of a simulation signal simulating the luminance change of the measurement range.and that is estimated as a noise component of the luminance change in the measurement range, a step of calculating, by a coefficient calculation unit (161), a coefficient to adjust the simulation signal such that in a noise-suppressed signal, after suppression of the simulation signal in the pulse wave origin signal, a signal for estimating the person's pulse wave remains, a step of suppressing, by a noise suppression unit (162), the simulation signal multiplied by the coefficient in the pulse wave origin signal, and a step of estimating, by an estimation unit (163), the person's pulse wave based on the noise-suppressed signal.

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