Respiratory disease assessment device and respiratory disease assessment method

Abstract

In the present invention, a photoplethysmography signal corresponding to the pulse of a subject is acquired in time series by a sensor (S101). On the basis of a pulse waveform represented by the time-series photoplethysmography signal, a feature amount including at least the interval, amplitude, and baseline of the pulse waveform is extracted for each beat (S104). On the basis of the pulse waveform, a respiratory period corresponding to each respiration of the subject is identified (S107). The respiratory period is a period including a plurality of consecutive beats. From the pulse waveform, a variation amount of the interval, a variation amount of the amplitude, and a variation amount of the baseline in an assessment segment that has been set corresponding to one or more of consecutive respiratory periods are calculated (S108). On the basis of the variation amount of the interval, the variation amount of the amplitude, and the variation amount of the baseline in the assessment segment, an exacerbation severity, which numerically represents the degree of exacerbation of a respiratory disease of the subject, is calculated (S109, S110). Thus, the degree of exacerbation of the respiratory disease of the subject is assessed.

Description

Respiratory disease evaluation device and respiratory disease evaluation method

[0001] The present invention relates to a respiratory disease evaluation device and a respiratory disease evaluation method, and more particularly to a respiratory disease evaluation device and a respiratory disease evaluation method for evaluating the degree of exacerbation of a respiratory disease in a subject.

[0002] Conventionally, as a respiratory disease evaluation device of this type, for example, as disclosed in Patent Document 1 (US 11160459 A), monitoring the health status of a chronic disease patient is based on blood oxygen saturation (SpO ２ ), tissue oxygen saturation, cardiac output, vascular resistance, pulse rate, blood pressure, respiratory rate, and motion data.

[0003] Also, as disclosed in Patent Document 2 (Japanese Patent Application Laid-Open No. 2004-121668), there is also known a device for determining respiratory abnormalities in a subject based on the amplitude, interval, and baseline of a photoelectric plethysmogram (PPG) signal.

[0004] US 11160459 A Japanese Patent Application Laid-Open No. 2004-121668

[0005] However, the conventional respiratory disease evaluation device has a problem that it can only perform rough analysis and thus cannot accurately evaluate the degree of exacerbation of a respiratory disease in a subject.

[0006] Therefore, an object of the present invention is to provide a respiratory disease evaluation device and a respiratory disease evaluation method that can accurately evaluate the degree of exacerbation of a respiratory disease in a subject.

[0007] To solve the above problems, the respiratory disease evaluation device of this disclosure is a respiratory disease evaluation device configured to evaluate the degree of exacerbation of a subject's respiratory disease, comprising: a sensor unit that acquires a photoplethysmography signal corresponding to the subject's pulse in a time series; a feature extraction unit that extracts feature quantities including at least interval, amplitude, and baseline of the pulse waveform for each beat based on the pulse waveform shown by the time series photoplethysmography signal; a respiratory period identification unit that identifies a respiratory period corresponding to each respiration of the subject based on the pulse waveform, wherein the respiratory period is a period including multiple consecutive beats; a variation amount calculation unit that calculates the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline in an evaluation interval set corresponding to one or more consecutive respiratory periods from the pulse waveform; and an exacerbation degree calculation unit that calculates an exacerbation degree that numerically represents the degree of exacerbation of the subject's respiratory disease based on the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline in the evaluation interval.

[0008] In this specification, a photoplethysmography (PPG) signal means "a signal that represents information about a pulse wave, obtained by measuring changes in blood volume in arteries, veins, and capillaries corresponding to a heartbeat."

[0009] "One breath period" means the period corresponding to one breath of the subject. "An evaluation interval set to correspond to one or more consecutive breath periods" means that the evaluation interval has a length of one or more times the breath period and is set to have a start and end date that coincides with the start and end dates of the period of that length.

[0010] The "interval" in a pulse wave waveform refers to the time interval between adjacent peak points or between adjacent rising point initiations. The "amplitude" in a pulse wave waveform refers to the difference in signal intensity between the rising point initiation and the peak point of a given pulse wave. The "baseline" in a pulse wave waveform refers to the signal intensity at the rising point initiation.

[0011] In the respiratory disease evaluation device disclosed herein, the sensor unit acquires a photoplethysmography signal in time series corresponding to the subject's pulse. The feature extraction unit extracts feature quantities, including at least the interval, amplitude, and baseline of the pulse waveform, for each beat based on the pulse waveform shown by the time-series photoplethysmography signal. The respiratory period identification unit identifies the respiratory period corresponding to each breath of the subject based on the pulse waveform. The respiratory period is a period that includes multiple consecutive beats. The variation calculation unit calculates the variation in the interval, the variation in the amplitude, and the variation in the baseline from the pulse waveform in an evaluation interval set corresponding to one or more consecutive respiratory periods. The exacerbation degree calculation unit calculates the exacerbation degree, which numerically represents the degree of exacerbation of the respiratory disease in the subject, based on the variation in the interval, the variation in the amplitude, and the variation in the baseline in the evaluation interval. Here, the evaluation interval is set corresponding to one or more consecutive respiratory periods. As a result, the respiratory disease evaluation device of this disclosure can accurately assess the degree of exacerbation of the respiratory disease in the subject (verification data will be described in the Embodiments section).

[0012] In one embodiment of the respiratory disease evaluation device, an intermediate index calculation unit is provided that calculates interval index, amplitude index, and baseline index as intermediate indices, which numerically represent the degree of individual exacerbation, using predetermined interval reference value, amplitude reference value, and baseline reference value from the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline, respectively. The exacerbation degree calculation unit is characterized in that it calculates the degree of exacerbation based on the interval index, the amplitude index, and the baseline index.

[0013] In this embodiment of the respiratory disease evaluation device, the intermediate index calculation unit calculates interval indexes, amplitude indexes, and baseline indexes as intermediate indices, which numerically represent the degree of individual exacerbation, using predetermined interval reference values, amplitude reference values, and baseline reference values, based on the interval fluctuation amount, amplitude fluctuation amount, and baseline fluctuation amount calculated by the fluctuation amount calculation unit. In this way, the respiratory disease evaluation device in this embodiment first calculates interval indexes, amplitude indexes, and baseline indexes that numerically represent the degree of individual exacerbation as intermediate indices, and then calculates the degree of exacerbation as the final index based on these. Therefore, the degree of exacerbation as the final index can appropriately reflect the individual degrees of exacerbation of the interval fluctuation amount, amplitude fluctuation amount, and baseline fluctuation amount. As a result, the degree of exacerbation of the respiratory disease of the subject can be evaluated with even greater accuracy.

[0014] In one embodiment of the respiratory disease evaluation device, the interval reference value, amplitude reference value, and baseline reference value are characterized in that they include data from the subject's own respiratory disease during a stable period.

[0015] In this embodiment of the respiratory disease evaluation device, the interval reference value, amplitude reference value, and baseline reference value include data from the subject's own respiratory disease during a stable period (for example, the minimum values ​​of the interval fluctuation, amplitude fluctuation, and baseline fluctuation). In this case, the intermediate index calculation unit can calculate the interval index, amplitude index, and baseline index, respectively, as intermediate indices for the subject, based on the subject's own data from a stable period. As a result, the final index of exacerbation can reflect the individual exacerbation levels of the interval fluctuation, amplitude fluctuation, and baseline fluctuation, based on the subject's stable period. This allows for a more accurate evaluation of the degree of exacerbation of the subject's respiratory disease.

[0016] In one embodiment of the respiratory disease evaluation device, the interval reference value, amplitude reference value, and baseline reference value are each characterized by including statistical values ​​of clinical data from multiple different subjects.

[0017] In this embodiment of the respiratory disease evaluation device, the interval reference value, amplitude reference value, and baseline reference value each include statistical values ​​(e.g., median, interquartile range, mean, and standard deviation) of clinical data from multiple different subjects. Therefore, the intermediate index calculation unit can calculate the interval index, amplitude index, and baseline index, respectively, as intermediate indices for the subject, based on the statistical values ​​of clinical data from multiple different subjects. As a result, the exacerbation degree, as the final index, can reflect the individual exacerbation levels of the interval fluctuation, amplitude fluctuation, and baseline fluctuation for the subject, based on the statistical values ​​of objective clinical data. This allows for a more accurate evaluation of the degree of respiratory disease exacerbation in the subject.

[0018] In one embodiment of the respiratory disease evaluation device, the respiratory disease is characterized by being bronchial asthma or chronic obstructive pulmonary disease (COPD).

[0019] This respiratory disease evaluation device according to one embodiment can accurately evaluate the degree of exacerbation of bronchial asthma or chronic obstructive pulmonary disease, which are respiratory diseases, in the subject.

[0020] In one embodiment of the respiratory disease evaluation device, an output unit further comprises an output unit that outputs the degree of exacerbation as an image, wherein the image includes, as a line graph, the degree of exacerbation acquired multiple times over a certain period for a given subject on a plane including a first axis representing the elapsed time and a second axis representing the degree of exacerbation.

[0021] In this embodiment of the respiratory disease evaluation device, the output unit outputs an image that includes a line graph of the degree of exacerbation acquired multiple times over a certain period for a given subject on a plane including a first axis representing the elapsed time and a second axis representing the degree of exacerbation. Therefore, a user (for example, a subject such as a patient, or a medical professional such as a doctor or nurse) can intuitively grasp the trend of remission or worsening of the respiratory disease symptoms for the subject by looking at the image. For example, if the subject is an asthma patient receiving home care, by looking at this image, if it can be seen that the subject's respiratory disease symptoms, including asthma, are on a worsening trend, they can take measures such as inhaling medication, taking oral medication, or seeking medical attention.

[0022] In one embodiment of the respiratory disease evaluation device, an output unit further comprises an output unit that outputs the degree of exacerbation as an image, wherein the image is a plane including a third axis representing the degree of exacerbation, and the distribution of the degree of exacerbation obtained for multiple different subjects along the third axis is included as a graph.

[0023] In this embodiment of the respiratory disease evaluation device, the output unit outputs an image that includes a graph of the distribution of exacerbation levels acquired for multiple different subjects along a third axis representing the degree of exacerbation on a plane that includes the third axis. Therefore, a user (typically a physician) can intuitively grasp the distribution of the degree of respiratory disease exacerbation for multiple different subjects by looking at the image. Furthermore, the physician, as the user, can intuitively grasp where the patient they are currently examining is located within the distribution of exacerbation levels among the multiple different subjects. Therefore, the physician is able to more easily and effectively decide on a prescription for that patient.

[0024] One embodiment of the respiratory disease evaluation device is characterized by comprising a housing that integrally houses the sensor unit, the feature extraction unit, the respiratory period identification unit, the variation amount calculation unit, and the exacerbation degree calculation unit.

[0025] In this embodiment of the respiratory disease evaluation device, the sensor unit, the feature extraction unit, the respiratory period identification unit, the variation calculation unit, and the exacerbation degree calculation unit are all housed together in a single housing. Therefore, the device can be configured compactly. In that case, the device becomes more convenient for the user to handle.

[0026] In one embodiment of a respiratory disease evaluation device, the device comprises a first housing that integrally houses the sensor unit and a transmitting unit that transmits the output of the sensor unit, and a second housing that integrally houses a receiving unit that receives the output of the sensor unit from the transmitting unit wirelessly or via wire, the feature extraction unit, the respiratory period identification unit, the variation amount calculation unit, and the exacerbation degree calculation unit.

[0027] In this embodiment of the respiratory disease evaluation device, the sensor unit and the transmission unit that transmits the output of the sensor unit are integrally housed in a first housing. The receiving unit that receives the output of the sensor unit from the transmission unit wirelessly or via wired connection, the feature extraction unit, the respiratory period identification unit, the variation calculation unit, and the exacerbation degree calculation unit are integrally housed in a second housing. In this case, by installing application software (computer program) on an existing computer device such as a smartphone, personal computer, or PDA (Personal Digital Assistant), it becomes possible to have the second housing and the components housed within the second housing perform their functions. This makes it possible to configure the device while minimizing the additional cost burden on the user.

[0028] In another aspect, the respiratory disease evaluation method of this disclosure is a respiratory disease evaluation method configured to evaluate the degree of exacerbation of a subject's respiratory disease, characterized in that it includes: acquiring a photoplethysmography signal corresponding to the subject's pulse in a time series using a sensor; extracting feature quantities including at least interval, amplitude, and baseline of the pulse waveform for each beat based on the pulse waveform represented by the time series photoplethysmography signal; identifying a respiratory period corresponding to each respiration of the subject based on the pulse waveform, wherein the respiratory period is a period including multiple consecutive beats; calculating the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline in an evaluation interval set corresponding to one or more consecutive respiratory periods from the pulse waveform; and calculating an exacerbation degree that numerically represents the degree of exacerbation of the subject's respiratory disease based on the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline in the evaluation interval.

[0029] According to the respiratory disease assessment method disclosed herein, the degree of exacerbation of the respiratory disease in the subject can be accurately assessed.

[0030] As is clear from the above, the respiratory disease evaluation device and respiratory disease evaluation method disclosed herein can accurately evaluate the degree of exacerbation of a subject's respiratory disease.

[0031] Figure 1(A) is a perspective view showing the external appearance of a respiratory disease evaluation device according to one embodiment of this disclosure. Figure 1(B) is a diagram showing the respiratory disease evaluation device attached to the fingertip of a subject. Figure 3(A) is a diagram showing the functional block configuration of the respiratory disease evaluation device. Figure 3(A) is a diagram showing the sensor unit included in the respiratory disease evaluation device, which consists of a transmissive photoplethysmography sensor, and detects a photoplethysmography signal from the subject's finger. Figure 3(B) is a diagram showing the sensor unit included in the respiratory disease evaluation device, which consists of a reflective photoplethysmography sensor, and detects a photoplethysmography signal from the subject's finger. Figure 5(A) and Figure 5(B) are diagrams schematically illustrating the waveform of the photoplethysmography signal and the feature quantities, including at least interval, amplitude, and baseline, that should be extracted from the photoplethysmography signal. Figures 6(A), 6(B), 6(C), and 6(D) illustrate the temporal changes in photoplethysmography signals, intervals, amplitudes, and baselines acquired over multiple consecutive respiratory periods, respectively. These figures show the data flow from the photoplethysmography signal to the calculation of the exacerbation degree. Figures 8(A-1), 8(B-1), 8(C-1), and 8(D-1) illustrate the above-mentioned photoplethysmography signal, the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline acquired during a stable period of asthma in a particular subject, respectively. Figures 8(A-2), 8(B-2), 8(C-2), and 8(D-2) illustrate the above-mentioned photoplethysmography signal, the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline acquired during an exacerbation of asthma in the same subject, respectively. Figure 9(B) shows the interval index, amplitude index, and baseline index, which are intermediate indices obtained by the flow in Figure 4, compared between the stable and exacerbated states of the subject. Figure 9(C) shows the SpO2 obtained according to Patent Document 1 (US 11160459 A), with the evaluation interval not corresponding to the respiratory period. ２The first figure shows pulse rate and respiratory rate compared between the stable and exacerbated states of the subject, respectively. The second figure shows interval index, amplitude index, and baseline index, which were obtained simulated according to Patent Document 2 (Japanese Patent Publication No. 2004-121668), with the evaluation interval not corresponding to the respiratory period, compared between the stable and exacerbated states of the subject, respectively. The leftmost figure, 9(A), shows the severity judged by a physician, compared between the stable and exacerbated states of the subject, respectively. The third figure shows an image containing a line graph of the degree of exacerbation obtained multiple times over a certain period for a certain asthma patient, following the flow chart in Figure 4. The fourth figure shows an image containing a line graph of the degree of exacerbation obtained multiple times over a certain period for a certain COPD patient, similarly. Figure 10(C) is a diagram showing an image containing a line graph of the degree of exacerbation obtained multiple times over a certain period for a healthy person. The diagram shows an image containing a graph of the distribution of another degree of exacerbation obtained for multiple different subjects using the flow chart in Figure 4. Figure 12(A) is a perspective view showing the appearance of a respiratory disease evaluation device of another embodiment of the present invention. Figure 12(B) shows the respiratory disease evaluation device attached to the wrist of a subject. Figure 13(A) is a perspective view showing the appearance of a respiratory disease evaluation device of yet another embodiment of the present invention. Figure 13(B) shows the respiratory disease evaluation device attached to the base of a finger of a subject.

[0032] The embodiments of this invention will now be described in detail with reference to the drawings.

[0033] (Outline Configuration of the Device) Figure 1(A) shows an oblique view of the external appearance of a respiratory disease evaluation device 1 according to one embodiment of this disclosure. In the following description, terms such as "top," "bottom," "upper surface," "lower surface," "front side," and "back side" are merely convenient designations for describing the external appearance of the respiratory disease evaluation device 1. This respiratory disease evaluation device 1 can be worn regardless of the orientation of the fingertips of the person being measured.

[0034] The respiratory disease evaluation device 1 comprises a main body 1M that forms a fingertip clip-type housing. The main body 1M has an upper body 1A and a lower body 1B arranged vertically. At the front end 1e of the main body 1M, a finger insertion hole 3 is formed, spanning between the upper body 1A and the lower body 1B, into which the subject's fingertip (the area to be measured) is inserted during measurement. In this example, the finger insertion hole 3 has a substantially elliptical cross-section and extends into the interior of the main body 1M, and a sensor unit 2 is provided inside it. On the upper surface of the upper body 1A, there is a display unit 6 for displaying various information and an operating unit 9 for operation by the user (for example, a subject such as a patient, or a medical professional such as a doctor or nurse).

[0035] Near the rear end 1f of the main body 1M, the opposing surfaces of the upper body 1A and the lower body 1B are formed as tapered surfaces 13 and 14 that open toward the rear. A hinge 12 is provided at the point where the tapered surfaces 13 and 14 meet, connecting the upper body 1A and the lower body 1B. The upper body 1A and the lower body 1B are rotatable relative to each other around this hinge 12. Furthermore, the upper body 1A and the lower body 1B are biased around the hinge 12 by a spring (not shown) in a direction that brings them closer together on the end 1e side. When the main body 1M is not subjected to external force, the upper body 1A and the lower body 1B are in contact with each other on the end 1e side.

[0036] When in use, the subject places, for example, the thumb of their right hand on the sheet portion 11 located near the rear end 1f of the upper surface of the upper part 1A of the main body, and the index finger of their right hand on the lower surface of the lower part 1B of the main body, applying force by gripping the upper part 1A and the lower part 1B of the main body from above and below. As a result, the upper part 1A and the lower part 1B of the main body rotate around the hinge 12 so that the tapered surfaces 13 and 14 move closer to each other, while the upper part 1A and the lower part 1B of the main body open apart at the end 1e. This causes the finger insertion hole 3 to open wide, allowing the subject to easily insert the fingertips of their left hand into the finger insertion hole 3. When the subject releases their right hand fingers from the main body 1M with their left hand fingertips in the finger insertion hole 3, as shown in Figure 1(B), the fingertips of the left hand (the fingertips of the index fingers in this example) 90 are inserted into the finger insertion hole 3 and are gripped between the upper part 1A and the lower part 1B of the main body by the restoring force of the spring. In other words, the main unit 1M is attached to the fingertip 90, and the sensor unit 2 is positioned opposite the fingertip 90. Note that the finger to be measured may be any finger other than the index finger, or it may be a finger of the right hand.

[0037] Figure 2 shows the functional block configuration of the respiratory disease evaluation device 1. This respiratory disease evaluation device 1 integrates a sensor unit 2, a control unit 4, a storage unit 5, a display unit 6, an operation unit 9, a communication unit 7, and a power supply unit 8 into a single main body 1M.

[0038] As shown in Figure 3(A), the sensor unit 2 in this example consists of a known transmissive photoplethysmography sensor and detects a photoplethysmography signal PPG from the subject's finger. Specifically, the sensor unit 2 includes a light-emitting diode 21A that generates red light LR and a light-emitting diode 21B that generates infrared light LIR, arranged side by side on the upper side of the fingertip 90, and further includes phototransistors 22A and 22B arranged side by side on the lower side of the fingertip 90 opposite to the light-emitting diodes 21A and 21B. The control unit 4 controls the emission of light from the light-emitting diodes 21A and 21B, and the phototransistors 22A and 22B each generate photocurrents in response to the light LR and LIR transmitted through the artery 91 and vein 92 of the fingertip 90. Based on these photocurrents, a photoplethysmography signal PPG is acquired.

[0039] Incidentally, as shown in FIG. 3(B), the sensor unit 2 may be composed of a known reflective photoplethysmographic sensor. In this example, the reflective photoplethysmographic sensor shown in FIG. 3(B) includes a light-emitting diode 21A that generates red light LR and a light-emitting diode 21B that generates infrared light LIR, which are arranged side by side under the fingertip 90. Further, it includes a phototransistor 22 that is arranged side by side between these light-emitting diodes 21A and 21B. Thereby, a photoplethysmographic signal PPG is detected from the finger of the subject.

[0040] The control unit 4 shown in FIG. 2 includes a CPU (Central Processing Unit) that operates by software (computer program), and controls the operation of the entire respiratory disease evaluation apparatus 1. The operation will be described in detail later.

[0041] The storage unit 5 includes a RAM (Random Access Memory) used as a work area necessary for the control unit 4 to execute a program, and a ROM (Read Only Memory) for storing a program to be executed by the control unit 4. Further, the storage unit 5 stores the signal output by the sensor unit 2 and the information obtained by processing the signal in time series over a certain period.

[0042] In this example, the display 6 is composed of an LCD (Liquid Crystal Display) or an EL (Electroluminescence) display. This display 6 displays the deterioration degree of the respiratory disease of the subject obtained as a calculation result and other information.

[0043] In this example, the operation unit 9 is composed of a push-button switch (power ON button). That is, when the subject presses the push-button switch 9, the power of the respiratory disease evaluation apparatus 1 is turned on (ON) or off (OFF).

[0044] The communication unit 7 includes an input / output interface and can transmit information from the control unit 4 to other devices (for example, substantial computer devices such as the smartphone 30 and the personal computer 40) via the network 70. Further, the communication unit 7 can receive information from other devices via the network 70 and deliver it to the control unit 4. Note that the network 70 may be a wireless network as shown in the figure, or may be a wired network via, for example, a LAN (Local Area Network) cable.

[0045] The power supply unit 8 consists of dry batteries (in this example, two AA batteries) not shown in the figure. When the push button switch 9 is turned on, power is supplied from these dry batteries to each part of the respiratory disease evaluation device 1. Note that the power supply unit 8 may have a power-off function that automatically stops power supply when pulsations are not detected for a certain period of time.

[0046] In this example, since the sensor unit 2, the control unit 4, the storage unit 5, the display 6, the operation unit 9, the communication unit 7, and the power supply unit 8 are accommodated in the main body 1M integrally, the respiratory disease evaluation device 1 can be configured compactly. Therefore, it becomes convenient for the user (including subjects such as patients, medical staff such as doctors or nurses, etc.) of this respiratory disease evaluation device 1 to handle.

[0047] (Operation of the device) FIG. 4 shows the flow of the respiratory disease evaluation method from obtaining the photoplethysmogram signal to outputting the exacerbation degree by the respiratory disease evaluation device 1.

[0048] With the main unit 1M (or its sensor unit 2) attached to the fingertip 90, when the subject instructs to start measurement using the push-button switch on the operation unit 9 provided on the main unit 1M, the control unit 4 starts acquiring a photoplethysmography signal PPG corresponding to the subject's pulse rate using the sensor unit 2, as shown in step S101 of Figure 4. Next, as shown in step S102, the control unit 4 applies a known smoothing process to the acquired photoplethysmography signal PPG to remove noise. Figure 5(A) illustrates the waveform (smoothed waveform) of the photoplethysmography signal PPG acquired in time series over a period including multiple consecutive beats (approximately 6 beats in this example). The photoplethysmography signal PPG shows a pulse wave waveform that alternates between peaks and troughs according to the subject's beat.

[0049] Next, as shown in step S103 of Figure 4, the control unit 4 detects the peak points pp, pp, ... of the photoplethysmography signal PPG. As a result, as shown in step S104, the control unit 4 acts as a feature extraction unit and extracts features for each beat that include at least the interval Tc, amplitude Am, and baseline Ba of the pulse wave waveform. Subsequently, as shown in step S105, the control unit 4 applies a known smoothing process to the acquired signals representing the interval Tc, amplitude Am, and baseline Ba to remove noise.

[0050] Here, as shown in Figure 5(A), the "interval" Tc of the pulse wave waveform means the time interval between adjacent peak points pp, pp. Alternatively, the "interval" of the pulse wave waveform may be defined as the time interval between adjacent rising edge start points sp, sp. However, since the signal intensity of the peak point pp is larger than the signal intensity of the rising edge start point sp, defining the "interval" Tc as the time interval between adjacent peak points pp, pp is more advantageous from the viewpoint of the signal-to-noise ratio (SNR). The "amplitude" Am of the pulse wave waveform means the difference in signal intensity between the rising edge start point sp and the peak point pp of a certain pulse wave (peak). The "baseline" Ba of the pulse wave waveform means the signal intensity of the rising edge start point sp.

[0051] In this embodiment, three feature quantities are extracted from the pulse wave waveform shown by the photoelectric pulse wave signal PPG: interval Tc, amplitude Am, and baseline Ba. However, in addition to interval Tc, amplitude Am, and baseline Ba, the gradient Gl of the pulse wave waveform and a notch Nc as shown in Figure 5(B) may also be extracted as feature quantities of the pulse wave waveform. The "gradient" Gl of the pulse wave waveform refers to the slope created by the rising start point sp and the peak point pp of a certain pulse wave (peak). The "notch" Nc refers to a dip that occurs during the falling of a certain pulse wave (peak).

[0052] Figures 6(A), 6(B), 6(C), and 6(D) illustrate the temporal changes in the photoplethysmography signal PPG, interval Tc, amplitude Am, and baseline Ba, acquired in a time series over multiple consecutive respiratory periods (approximately seven respiratory periods in this example). For reference, Figure 6(A) also shows the movement of the subject's thoracic cage during each breath as the waveform of the thoracic signal Ch.

[0053] Next, as shown in step S106 of Figure 4, the control unit 4 acts as a respiratory period identification unit, and in this example, detects sinusoidal changes in the peak point of the photoplethysmography signal PPG over multiple respiratory periods (changes synchronized with the thoracic signal Ch in Figure 6(A)) to identify the respiratory period corresponding to each breath of the subject. In Figure 6(A), three consecutive respiratory periods Tb0, Tb1, and Tb2 are illustrated. In this example, each respiratory period Tb0, Tb1, and Tb2 has substantially the same duration and each contains multiple consecutive beats (approximately 10 beats in this example).

[0054] Next, as shown in step S107 of Figure 4, the control unit 4 acts as a fluctuation amount calculation unit and, in this example, sets the one-breath period Tb1 shown in Figure 6(A) as the evaluation interval, and further calculates the interval fluctuation amount TcD1, the amplitude fluctuation amount AmD1, and the baseline fluctuation amount BaD1 during this one-breath period Tb1, as shown in step S108.

[0055] Here, as shown in Figure 6(B), the interval variation TcD1 is defined as the difference between the maximum value TcMax and the minimum value TcMin of the interval in the evaluation interval (one respiratory period) Tb1. That is, TcD1 = TcMax - TcMin.

[0056] As shown in Figure 6(C), the amplitude variation AmD1 is defined as the difference between the maximum amplitude AmMax and the minimum amplitude AmMin in the evaluation interval (one breath period) Tb1. That is, AmD1 = AmMax - AmMin.

[0057] As shown in Figure 6(D), the baseline fluctuation BaD1 is defined as the difference between the maximum value BaMax and the minimum value BaMin of the baseline in the evaluation interval (one respiratory period) Tb1. That is, BaD1 = BaMax - BaMin.

[0058] In addition, Figures 6(B), 6(C), and 6(D) also show the interval variation TcD, amplitude variation AmD, and baseline variation BaD obtained during the end of each respiratory period Tb0, Tb1, and Tb2.

[0059] Next, in this example, as shown in step S109 of Figure 4, the control unit 4 acts as an intermediate index calculation unit and calculates intermediate indices, an interval index Pc1, an amplitude index Pa1, and a baseline index Pb1, which numerically represent the degree of individual deterioration, from the amplitude fluctuation amount TcD1, the amplitude fluctuation amount AmD1, and the baseline fluctuation amount BaD1, using predetermined interval reference value TcRef1, amplitude reference value AmRef1, and baseline reference value BaRef1.

[0060] In this example, for the interval variation TcD1, amplitude variation AmD1, and baseline variation BaD1 in the evaluation interval (one respiratory period) Tb1 shown in Figure 7(B), interval reference value TcRef1, amplitude reference value AmRef1, and baseline reference value BaRef1 are pre-defined, as shown in Figure 7(C). Figures 7(A) to 7(D) show the data flow from acquiring the photoplethysmography signal to outputting the exacerbation degree.

[0061] In this example, the control unit 4 uses the following data for the interval reference value TcRef1, amplitude reference value AmRef1, and baseline reference value BaRef1: data from the stable period of the subject's own respiratory disease (asthma in this example), specifically the best values. In this case, as shown in Figure 7(D), the control unit 4 divides the interval variation TcD1, amplitude variation AmD1, and baseline variation BaD1 by the interval reference value TcRef1, amplitude reference value AmRef1, and baseline reference value BaRef1, respectively, to calculate the interval index Pc1, amplitude index Pa1, and baseline index Pb1 as intermediate indices. That is, TcD1 / TcRef1 = Pc1 AmD1 / AmRef1 = Pa1 BaD1 / BaRef1 = Pb1 … (Eq. 1)

[0062] For example, as shown in Table 1 below, the interval reference value TcRef1 = 5.0 (bpm), the amplitude reference value AmRef1 = 0.030 (dimensionless), and the baseline reference value BaRef1 = 0.016 (dimensionless) are set to be equal to the best values ​​(interval variation, amplitude variation, and baseline variation) during a certain subject's stable period. Furthermore, the variation amounts obtained by measurement are assumed to be interval variation TcD1 = 20.4 (bpm), amplitude variation AmD1 = 0.075 (dimensionless), and baseline variation BaD1 = 0.056 (dimensionless). In this case, the intermediate indices are calculated as follows: interval index Pc1 = 4.1 (dimensionless), amplitude index Pa1 = 2.5 (dimensionless), and baseline index Pb1 = 3.5 (dimensionless). (Table 1)

[0063] Next, in this example, as shown in step S110 of Figure 4, the control unit 4 acts as a severity calculation unit and calculates the severity I1 based on the interval index Pc1, the amplitude index Pa1, and the baseline index Pb1. In this example, the average value of the interval index Pc1, the amplitude index Pa1, and the baseline index Pb1 is calculated as the severity I1. That is, (Pc1 + Pa1 + Pb1) / 3 = I1 … (Eq. 2).

[0064] For example, as shown in the example in Table 1 above, if the interval index Pc1 = 4.1, the amplitude index Pa1 = 2.5, and the baseline index Pb1 = 3.5, the exacerbation degree I1 is calculated as 3.4 (dimensionless).

[0065] Finally, in this example, the control unit 4 shown in Figure 2 acts as an output unit and digitally displays the calculated severity I1 as a numerical value (3.4 in the example above) on the display unit 6.

[0066] Thus, in this embodiment, as intermediate indices, interval indices Pc1, amplitude indices Pa1, and baseline indices Pb1 are calculated, each representing the degree of individual exacerbation numerically based on the subject's stable period. Based on these, the exacerbation degree I1 is calculated as the final indices. Therefore, the exacerbation degree I1, as the final indices, can appropriately reflect the individual degrees of exacerbation of the amplitude fluctuation TcD1, amplitude fluctuation AmD1, and baseline fluctuation BaD1.

[0067] (Verification of the effects of the invention) In order to verify the effects of the invention, the inventors used the respiratory disease evaluation device 1 of this embodiment to acquire photoplethysmography signals PPG_St and PPG_Ex from a certain subject during stable (represented by the symbol St) and exacerbated (represented by the symbol Ex) periods of asthma, as shown in Figures 8(A-1) and 8(A-2), respectively. Figures 8(B-1), 8(C-1), and 8(D-1) show the interval variation TcD_St, amplitude variation AmD_St, and baseline variation BaD_St, respectively, calculated from the photoplethysmography signal PPG_St in Figure 8(A-1). Furthermore, Figures 8(B-2), 8(C-2), and 8(D-2) show the interval variation TcD_Ex, amplitude variation AmD_Ex, and baseline variation BaD_Ex, respectively, calculated from the photoplethysmography signal PPG_Ex in Figure 8(A-2). For statistical purposes, the sample size N=10 was used.

[0068] Column 9(B) shows box plots comparing the interval index Pc1, amplitude index Pa1, and baseline index Pb1, calculated as intermediate indices using the flow chart in Figure 4, for stable St and exacerbating Ex, for this sample group. In the figure, × marks indicate the mean and - marks indicate the median. At a glance, it is clear that there are differences in the interval index Pc1, amplitude index Pa1, and baseline index Pb1 between stable St and exacerbating Ex. A Wilcoxon signed-rank test was performed with a sample size N=10 and a significance level of 0.05. The t-values ​​were t=8 for the interval index Pc1, t=2 for the amplitude index Pa1, and t=6 for the baseline index Pb1 (the p-values ​​were p=0.047 for the interval index Pc1, p=0.009 for the amplitude index Pa1, and p=0.028 for the baseline index Pb1). Under these conditions, a statistically significant difference exists if t < 10 (conversely, a statistically significant difference cannot be said if t ≥ 10). Therefore, it can be said that the interval index Pc1, amplitude index Pa1, and baseline index Pb1, calculated as intermediate indices, reflect the degree of exacerbation of the subject's asthma.

[0069] Column 9(A) shows the severity of the sample group as determined by the physician, comparing stable St and exacerbation Ex, similar to Column 9(B), as a box plot. In the figure, the severity is expressed numerically, with "no seizures" being 0, "minor seizures" being 1, "moderate seizures" being 2, and "major seizures" being 3. A Wilcoxon signed-rank test was performed on these results, similar to Column 9(B), and the t-value was t=0 (the p-value was p=0.005). Column 9(A) confirms that the sample group indeed represents stable St and exacerbation Ex data.

[0070] Column 9(C) shows the above sample group, with the evaluation interval not corresponding to the respiratory period, as described in Patent Document 1 (US 11160459 A) for SpO2. ２When the percentage (%), pulse rate (bpm), and respiratory rate (bpm) were measured, these data were compared between stable St and exacerbation Ex and shown as box plots. A Wilcoxon signed-rank test was performed on these results, similar to that in column 9(B), and the t-value was SpO2. ２ For the following, t=18; for pulse rate, t=23; and for respiratory rate, t=18 (p-value is SpO2). ２ The p values ​​were p = 0.333 for t, p = 0.646 for pulse rate, and p = 0.333 for respiratory rate. As previously mentioned, under these conditions, there is a statistically significant difference if t < 10 (conversely, there is no statistically significant difference if t ≥ 10). Therefore, the SpO2 measured as described in Patent Document 1 ２ The percentage (%), pulse rate (bpm), and respiratory rate (bpm) do not necessarily reflect the degree of exacerbation of the subject's asthma.

[0071] Column 9(D) shows a box plot comparing stable St and exacerbation Ex data when the above sample group is used and the evaluation interval is not corresponding to the respiratory period, and the interval index (represented by the symbol Pc1'), amplitude index (represented by the symbol Pa1'), and baseline index (represented by the symbol Pb1') are calculated as simulated interval index Pc1', amplitude index (represented by the symbol Pa1'), and baseline index (represented by the symbol Pb1') are calculated respectively. The conditions are the same as in this embodiment (shown in Column 9(B)). The inventors believe that these simulated interval index Pc1', simulated amplitude index Pa1', and simulated baseline index Pb1' can be derived from the suggestions in Patent Document 2 (Japanese Patent Application Publication No. 2004-121668). Based on these results, a Wilcoxon signed-rank test was performed in the same manner as in column 9(B). The t-values ​​were t=27 for the simulated interval index Pc1', t=25 for the simulated amplitude index Pa1', and t=25 for the simulated baseline index Pb1' (the p-values ​​were p=0.959 for the simulated interval index Pc1', p=0.799 for the simulated amplitude index Pa1', and p=0.799 for the simulated baseline index Pb1'). As previously stated, under these conditions, a statistically significant difference exists if t < 10 (conversely, a statistically significant difference cannot be said if t ≥ 10). Therefore, it cannot be said that the simulated interval index Pc1', simulated amplitude index Pa1', and simulated baseline index Pb1' that can be derived from the suggestions in Patent Document 2 reflect the degree of exacerbation of the subjects' asthma.

[0072] Based on the above, it can be said that, according to this embodiment (shown in column 9(B)), the interval index Pc1, amplitude index Pa1, and baseline index Pb1 calculated as intermediate indices accurately reflect the degree of exacerbation of the subject's asthma. Therefore, it can be said that the exacerbation degree I1, calculated as the average value of the interval index Pc1, amplitude index Pa1, and baseline index Pb1, accurately reflects the degree of exacerbation of the subject's asthma. Thus, it has been verified that this respiratory disease evaluation device 1 can accurately evaluate the degree of exacerbation of a subject's asthma.

[0073] (Modification 1) In the above example, the control unit 4 set the respiratory period Tb1 shown in Figure 6(A) as the evaluation interval, but it is not limited to this. Multiple consecutive respiratory periods, for example, three consecutive respiratory periods as shown in Figure 6(A), may be set as the evaluation interval.

[0074] (Modification 2) In the above example, the control unit 4 acts as a severity calculation unit and calculates the average value of the interval index Pc1, amplitude index Pa1, and baseline index Pb1 as the severity I1, but it is not limited to this. For example, the severity I1 may be determined by selecting the index with the largest value among the interval index Pc1, amplitude index Pa1, and baseline index Pb1 included in the intermediate index (maximum value priority method). In the example shown in Table 1, the interval index Pc1 = 4.1, the amplitude index Pa1 = 2.5, and the baseline index Pb1 = 3.5, so the interval index Pc1 with the largest value (= 4.1) is determined as the severity I1. In other words, the severity I1 is determined to be 4.1.

[0075] Alternatively, the control unit 4 may function as an exacerbation degree calculation unit, weighting the interval index Pc1, amplitude index Pa1, and baseline index Pb1 included in the intermediate index, and calculating the average value as the exacerbation degree I1 (weighted average method). In this case, if the weighting coefficients are, for example, α, β, and γ, the exacerbation degree I1 is calculated by (α・Pc1 + β・Pa1 + γ・Pb1) / 3 = I1 … (Eq. 3). The weighting coefficients α, β, and γ can be determined experimentally, for example, so as to increase the correlation between the exacerbation degree I1 calculated by this equation (Eq. 3) and the severity judged by the physician (shown in column 9(A) of Figure 9).

[0076] (Modification 3) In the above example, the control unit 4 acts as an output unit and digitally displays the calculated severity I1 as a numerical value (3.4 in the above example) on the display unit 6, but it is not limited to this. For example, the control unit 4 may act as an output unit and display the calculated severity I1 as an image including a graph on the display unit 6. Alternatively, the control unit 4 may act as an output unit and output the calculated severity I1 as an image via the communication unit 7 and the network 70, and display that image on the display unit 36 ​​of the smartphone 30, the display unit 46 of the personal computer 40, etc. that receive the output.

[0077] Figure 10(A) illustrates an image displayed on the display 36 by the control unit (including CPU) 34 of the smartphone 30 when the subject is an asthma patient. This image includes a line graph I1G on a plane Q1 which includes a horizontal axis H as the first axis representing the elapsed time and a vertical axis V as the second axis representing the exacerbation degree I1 for the subject, obtained multiple times over a certain period (including multiple consecutive days). In this example, plane Q1 is divided into a stable zone G, a caution zone Y, and a warning zone R by dashed lines indicating two thresholds Th11 and Th12 of different magnitudes. In this example, Th11 is set to 2 and Th12 to 4 (however, it is not limited to this). In this example, the background colors of the stable zone G, caution zone Y, and warning zone R are set to yellow-green, yellow, and light red, respectively, to intuitively represent the severity. The line graph I1G is created by connecting the plot points I1d, I1d, ... which represent the exacerbation level I1, with dashed lines in this example. Of the plot points I1d, I1d, ..., those in the stable zone G are colored green, while those in the caution zone Y and warning zone R are colored red.

[0078] In this way, users (referring to subjects such as patients, or healthcare professionals such as doctors or nurses) can intuitively grasp the trend of remission or worsening of the subject's asthma symptoms by viewing the image. For example, if the subject is an asthma patient receiving home care, viewing this image can reveal that their asthma symptoms are worsening, allowing them to take appropriate action such as using an inhaler, taking oral medication, or seeking medical attention.

[0079] Figure 10(B) shows an example where, for a subject who is a COPD patient, the exacerbation level I1 obtained multiple times over a certain period (including multiple consecutive days) is displayed as a line graph I1G', exactly as in Figure 10(A). In this way, by looking at this image, the user can intuitively grasp the trend of remission or worsening of the subject's COPD symptoms.

[0080] Furthermore, Figure 10(C) shows an example in which, when the subject is healthy, the exacerbation level I1 obtained multiple times over a certain period (including multiple consecutive days) is displayed as a line graph I1G'' in exactly the same way as in Figure 10(A). In this case, the user can intuitively understand by looking at this image that there are no signs of respiratory disease development in that subject.

[0081] In the examples of Figures 10(A), 10(B), and 10(C), the horizontal axis H, vertical axis V, and thresholds Th11 and Th12 are displayed, but these elements may be omitted to simplify the image. In other words, the plot points I1d, I1d, ... may simply be superimposed on the stable area G, attention area Y, and warning area R, which are each colored with background colors. Furthermore, the plot points I1d, I1d, ... may be colored with only one color (for example, black).

[0082] (Modification 4) In the above example, the interval reference value TcRef1, amplitude reference value AmRef1, and baseline reference value BaRef1 were data from the subject's own respiratory disease (asthma in this example) during a stable period, but are not limited to this. The interval reference value TcRef1, amplitude reference value AmRef1, and baseline reference value BaRef1 may each be statistical values ​​(e.g., median, interquartile range, mean, and standard deviation) of clinical data from multiple different subjects.

[0083] For example, as shown in Table 2 below, for the interval variation TcD1, instead of the previously described interval reference value TcRef1, the mean value of clinical data from multiple different subjects is set in advance as the interval reference value TcRef2 = 13.9, and its standard deviation is set as the interval reference value TcRef3 = 15.1. For the amplitude variation AmD1, instead of the previously described amplitude reference value AmRef1, the mean value of clinical data from the above multiple different subjects is set in advance as the amplitude reference value AmRef2 = 0.0451, and its standard deviation is set as the amplitude reference value AmRef3 = 0.0273. For the baseline fluctuation BaD1, instead of the previously described baseline reference value BaRef1, the mean value of the clinical data from the above-mentioned multiple different subjects is pre-set as the baseline reference value BaRef2 = 0.0346, and its standard deviation is set as the baseline reference value BaRef3 = 0.0220. Furthermore, the fluctuations obtained by measurement are assumed to be: interval fluctuation TcD1 = 20.4 (bpm), amplitude fluctuation AmD1 = 0.075 (dimensionless), and baseline fluctuation BaD1 = 0.056 (dimensionless). (Table 2)

[0084] In this case, the intermediate indices, namely the interval index Pc2, the amplitude index Pa2, and the baseline index Pb2, are calculated using the following equation (Eq. 4): (TcD1 - TcRef2) / TcRef3 = Pc2 (AmD1 - AmRef2) / AmRef3 = Pa2 (BaD1 - BaRef2) / BaRef3 = Pb2 ... (Eq. 4)

[0085] According to the numerical example above, specifically, the intermediate indices are calculated as follows: interval index Pc2 = 2.55 (dimensionless), amplitude index Pa2 = 2.07 (dimensionless), and baseline index Pb2 = 2.12 (dimensionless).

[0086] Finally, in this example, as shown in step S110 of Figure 4, the control unit 4 acts as a severity calculation unit and calculates the severity I2 based on the interval index Pc2, the amplitude index Pa2, and the baseline index Pb2. In this example, the average value of the interval index Pc2, the amplitude index Pa2, and the baseline index Pb2 is calculated as the severity I2. That is, (Pc2 + Pa2 + Pb2) / 3 = I2 … (Eq. 5). Specifically, according to the numerical example above, the severity I2 is calculated to be 2.25 (dimensionless).

[0087] In this way, the final exacerbation grade I2 can reflect the individual exacerbation levels of the subject, based on the statistical values ​​of objective clinical data, specifically the amplitude fluctuation TcD1, the amplitude fluctuation AmD1, and the baseline fluctuation BaD1. As a result, the degree of asthma exacerbation in the subject can be evaluated with greater accuracy.

[0088] (Modification 5) As described in Modification 4 above, the clinical data of multiple different subjects (asthma patients), including interval index Pc2, amplitude index Pa2, baseline index Pb2, and exacerbation degree I2, is stored in the memory unit 45 of a personal computer 40 installed in the hospital via the network 70 shown in Figure 2, as shown in Table 3. Here, the far right column of Table 3 shows the severity of the attack as judged by the physician when examining each case. (Table 3)

[0089] Figure 11 illustrates an image displayed on the display unit 46 by the control unit (including the CPU) 44 of the personal computer 40 in this case. This image includes a one-dimensional scatter plot graph I2G on a plane Q2 that includes a left vertical axis V1 as a third axis representing the exacerbation degree I2 and a right vertical axis V2 representing the attack intensity, along vertical axes V1 and V2, representing the distribution of exacerbation degree I2 obtained for multiple different subjects (asthma patients). In this example, plane Q2 is divided into an attack-free region G, a minor attack region Y, a moderate attack region PR, and a severe attack region R by dashed lines indicating three thresholds of different magnitudes Th21, Th22, and Th23. In this example, Th21 is set to -0.50, Th22 to 0.50, and Th23 to 2.00 (however, it is not limited to these values). In this example, the background colors of the seizure-free region G, the minor seizure region Y, the moderate seizure region PR, and the major seizure region R are set to green, yellow, light red, and red, respectively, to intuitively represent the severity. The plot points I2d, I2d, ... that make up the scatter plot graph I2G are colored blue.

[0090] In this way, the user (typically a physician) can intuitively grasp the distribution of asthma severity (and exacerbation) for multiple different subjects by viewing the image. Furthermore, the physician, as a user, can intuitively understand where their own patient falls within that distribution of severity (and exacerbation) among multiple different subjects. Therefore, the physician is better able to make decisions regarding prescriptions for that patient.

[0091] Furthermore, the threshold values ​​Th21, Th22, and Th23 are not limited to Th21 = -0.50, Th22 = 0.50, and Th23 = 2.00. The threshold values ​​Th21, Th22, and Th23 can be determined experimentally to maximize the correlation between the calculated exacerbation level I2 and the seizure intensity (on a four-point scale) as assessed by a physician.

[0092] In addition, in the example in Figure 11, a horizontal axis representing the number (frequency) of plotted points I2d, I2d, ... may be set, and the distribution of the exacerbation degree I2 may be displayed as a histogram.

[0093] (Modification 6) In the above example, the device is equipped with a main body 1M (see Figure 1(A)) that forms a fingertip clip-type housing, but it is not limited to this. For example, the respiratory disease evaluation device 101 shown in Figure 12(A) is equipped with a main body 101M having a short cylindrical outer shape that forms a wristwatch-type housing, and belts 103, 103 that extend from the main body 101M to the rear and front sides in Figure 12(A). A display 106 for displaying various information is provided on the top surface of the main body 101M (the surface furthest from the wrist when worn). In this example, a sensor unit 102 consisting of a reflective photoplethysmography sensor is provided on the bottom surface of the main body 101M (the surface opposite to the top surface). An operating unit 109 for user operation is provided on the outer circumferential surface of the main body 101M. Inside the main body 101M, in addition to the control unit 104, a storage unit (not shown), a communication unit, and a power supply unit are housed and mounted.

[0094] As illustrated in Figure 12(A), the respiratory disease evaluation device 101 is attached to the subject's wrist 190. In this attached state, the sensor unit 102 detects the photoplethysmography signal PPG from the subject's wrist 190. Thereafter, it operates in the same manner as the previous example (respiratory disease evaluation device 1).

[0095] This allows the respiratory disease evaluation device 101 to accurately assess the degree of exacerbation of the subject's asthma.

[0096] (Modification 7) In the above example, the control unit 4 mounted on the main body 1M of the respiratory disease evaluation device 1 (or the control unit 104 mounted on the main body 101M of the respiratory disease evaluation device 101) performed calculation processing (flow in Figure 4) to determine the exacerbation degree I1 or I2 from the photoplethysmography signal PPG, but it is not limited to this. For example, the control unit 4 mounted on the main body 1M (first housing) of the respiratory disease evaluation device 1 may transmit the photoplethysmography signal PPG acquired by the sensor unit 2 to the smartphone 30 or personal computer 40 which constitutes the second housing via the communication unit 7 which acts as a transmitting unit. The smartphone 30 and personal computer 40 are each equipped with input / output interfaces 37 and 47 which act as receiving units and are capable of receiving the photoplethysmography signal PPG. The control unit 34 of the smartphone 30 and the control unit 44 of the personal computer 40 may receive the photoplethysmography signal PPG from the main unit 1M via the network 70 and input / output interfaces 37 and 47, and perform processing to determine the exacerbation degree I1 (or I2) from the photoplethysmography signal PPG. In this case as well, the degree of exacerbation of the subject's asthma can be evaluated with good accuracy, similar to the example above.

[0097] In this case, by installing application software for executing the respiratory disease evaluation method (Figure 4) flow on an existing computer device such as a smartphone 30 or a personal computer 40, it becomes possible to have the second housing and the components housed within the second housing perform their functions. This makes it possible to configure the respiratory disease evaluation device of the present invention while minimizing the additional cost burden on the user.

[0098] Furthermore, when the respiratory disease evaluation device of the present invention takes the form of including a first housing and a second housing as described above, it may be configured as the respiratory disease evaluation device 201 shown in Figure 13(A). This respiratory disease evaluation device 201 comprises a short cylindrical ring member 211 forming the first housing and a smartphone 230 forming the second housing. In this example, the ring member 211 is equipped with a sensor unit 202 consisting of a transmissive photoplethysmography sensor and an input / output interface 207 that acts as a transmitter capable of transmitting a photoplethysmography signal PPG. The smartphone 230 has a display unit 236 and houses and is equipped with an input / output interface 237 that acts as a receiver capable of receiving a photoplethysmography signal PPG and a control unit 234 including a CPU.

[0099] When using this respiratory disease evaluation device 201, as shown in Figure 13(B), the ring member 211 is attached to the base 290 of the subject's finger. In this attached state, the sensor unit 202 detects the photoplethysmography signal PPG from the base 290 of the subject's finger. After that, it operates in the same manner as in the previous example (respiratory disease evaluation devices 1 and 101). As a result, this respiratory disease evaluation device 201 can also accurately evaluate the degree of exacerbation of the subject's asthma.

[0100] The respiratory disease evaluation method described above may be recorded as software (computer program) on a non-transitory data storage medium such as a CD (compact disc), DVD (digital universal disc), or flash memory. By installing the software recorded on such a medium onto a computer device such as a smartphone, personal computer, or PDA (personal digital assistant), the respiratory disease evaluation method described above can be executed on that computer device.

[0101] The embodiments described above are illustrative, and various modifications are possible without departing from the scope of this invention. Each of the embodiments described above can stand on its own, but they can also be combined. Furthermore, various features within different embodiments can stand on their own, but they can also be combined.

[0102] 1, 101, 201 Respiratory disease evaluation device 1M, 101M Main unit 2, 102, 202 Sensor unit 4, 34, 44, 104, 234 Control unit 6, 36, 46, 106, 236 Display unit 9, 109 Operation unit 211 Ring member

Claims

1. A respiratory disease evaluation device configured to evaluate the degree of exacerbation of a subject's respiratory disease, comprising: a sensor unit that acquires a photoplethysmography signal corresponding to the subject's pulse in a time series; a feature extraction unit that extracts feature quantities including at least interval, amplitude, and baseline of the pulse waveform for each beat based on the pulse waveform shown by the time-series photoplethysmography signal; a respiratory period identification unit that identifies a respiratory period corresponding to each respiration of the subject based on the pulse waveform, wherein the respiratory period is a period including multiple consecutive beats; a variation amount calculation unit that calculates the variation amount of the interval, the variation amount of the amplitude, and the variation amount of the baseline in an evaluation interval set corresponding to one or more consecutive respiratory periods from the pulse waveform; and an exacerbation degree calculation unit that calculates an exacerbation degree that numerically represents the degree of exacerbation of the subject's respiratory disease based on the variation amount of the interval, the variation amount of the amplitude, and the variation amount of the baseline in the evaluation interval.

2. A respiratory disease evaluation device according to claim 1, comprising an intermediate index calculation unit that calculates interval index, amplitude index, and baseline index as intermediate indices, which numerically represent the degree of individual exacerbation, using predetermined interval reference value, amplitude reference value, and baseline reference value from the amount of variation in interval, the amount of variation in amplitude, and the amount of variation in baseline, and the exacerbation degree calculation unit calculates the degree of exacerbation based on the interval index, the amplitude index, and the baseline index.

3. A respiratory disease evaluation device according to claim 2, characterized in that the interval reference value, amplitude reference value, and baseline reference value include data from the subject's own respiratory disease during a stable period.

4. A respiratory disease evaluation device according to claim 2, characterized in that the interval reference value, amplitude reference value, and baseline reference value each include statistical values ​​of clinical data from multiple different subjects.

5. A respiratory disease evaluation device according to any one of claims 1 to 4, characterized in that the respiratory disease is bronchial asthma or chronic obstructive pulmonary disease.

6. A respiratory disease evaluation device according to any one of claims 1 to 4, further comprising an output unit that outputs the degree of exacerbation as an image, wherein the image includes, as a line graph, the degree of exacerbation acquired multiple times over a certain period for a certain subject on a plane including a first axis representing the elapsed time and a second axis representing the degree of exacerbation.

7. A respiratory disease evaluation device according to any one of claims 1 to 4, further comprising an output unit that outputs the degree of exacerbation as an image, wherein the image includes, as a graph, the distribution of the degree of exacerbation obtained for a plurality of different subjects along the third axis on a plane including a third axis representing the degree of exacerbation.

8. A respiratory disease evaluation device according to claim 1, characterized in that it comprises a housing that integrally houses the sensor unit, the feature extraction unit, the respiratory period identification unit, the variation amount calculation unit, and the exacerbation degree calculation unit.

9. A respiratory disease evaluation device according to claim 1, comprising: a first housing integrally housing the sensor unit and a transmitting unit for transmitting the output of the sensor unit; a second housing integrally housing a receiving unit for receiving the output of the sensor unit from the transmitting unit wirelessly or via wire; the feature extraction unit; the respiratory period identification unit; the variation amount calculation unit; and the exacerbation degree calculation unit.

10. A respiratory disease evaluation method configured to evaluate the degree of exacerbation of a subject's respiratory disease, comprising: acquiring a photoplethysmography signal corresponding to the subject's pulse in a time series using a sensor; extracting feature quantities including at least interval, amplitude, and baseline of the pulse waveform for each beat based on the pulse waveform represented by the time series photoplethysmography signal; identifying a respiratory period corresponding to each respiration of the subject based on the pulse waveform, wherein the respiratory period is a period including multiple consecutive beats; calculating the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline in an evaluation interval set corresponding to one or more consecutive respiratory periods from the pulse waveform; and calculating an exacerbation degree that numerically represents the degree of exacerbation of the subject's respiratory disease based on the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline in the evaluation interval.

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