Respiratory disease evaluation device and respiratory disease evaluation method

Abstract

To assess the degree of exacerbation of the subject's respiratory disease. [Solution] A photoplethysmography signal corresponding to the subject's pulse is acquired in time series by a sensor (S101). Based on the pulse waveform represented by the time-series photoplethysmography signal, feature quantities including at least the interval, amplitude, and baseline of the pulse waveform are extracted for each beat (S104). Based on the pulse waveform, the respiratory period corresponding to each breath of the subject is identified (S107). The respiratory period is a period that includes multiple consecutive beats. From the pulse waveform, the amount of variation in interval, the amount of variation in amplitude, and the amount of variation in baseline are calculated in an evaluation interval set corresponding to one or more consecutive respiratory periods (S108). Based on the amount of variation in interval, the amount of variation in amplitude, and the amount of variation in baseline in the evaluation interval, the degree of exacerbation, which numerically represents the degree of exacerbation of the subject's respiratory disease, is calculated (S109, S110).

Description

Technical Field

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

Background Art

[0002] Conventionally, as disclosed in Patent Document 1 (US 11160459 A), for example, a system for monitoring the health status of a chronic disease patient based on blood oxygen saturation (SpO2), tissue oxygen saturation, cardiac output, vascular resistance, pulse rate, blood pressure, respiratory rate, and motion data is known.

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

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, the conventional respiratory disease evaluation apparatus only performs rough analysis, and thus there is a problem that the degree of exacerbation of the respiratory disease in the subject cannot be accurately evaluated.

[0006] Therefore, the object of this 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 subject's respiratory disease. [Means for solving the problem]

[0007] To solve the above problems, the respiratory disease evaluation device disclosed herein is A respiratory disease assessment device configured to evaluate the degree of exacerbation of a subject's respiratory disease, A sensor unit that acquires a photoplethysmography signal corresponding to the pulse rate of the subject in a time series, A feature extraction unit extracts feature quantities for each beat that include at least the interval, amplitude, and baseline of the pulse wave waveform shown by the above time-series photoplethysmography signal, based on the pulse wave waveform shown above. The system includes a respiratory period identification unit that identifies the respiratory period corresponding to each breath of the subject based on the pulse wave waveform, wherein the respiratory period is a period that includes multiple consecutive beats. A variation calculation unit calculates the variation in the interval, the variation in the amplitude, and the variation in the baseline for evaluation intervals set to correspond to one or more consecutive respiratory periods, based on the pulse wave waveform described above. An exacerbation degree calculation unit calculates an exacerbation degree that numerically represents the degree of exacerbation of the respiratory disease of the subject, based on the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline within the evaluation interval. It is characterized by having the following features.

[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 duration" refers to the period corresponding to one breath of the subject. "Evaluation interval set to correspond to one or more consecutive breath durations" means that the evaluation interval has a length of one or more times the breath duration and is set to have a start and end date that coincides with the start and end dates of the duration.

[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 of this disclosure, the sensor unit acquires a photoplethysmography signal in a time series corresponding to the subject's pulse. The feature extraction unit extracts features for each beat, including at least the interval, amplitude, and baseline of 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 disclosed herein 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 a respiratory disease evaluation device, The system includes an intermediate indicator calculation unit that calculates interval indicators, amplitude indicators, and baseline indicators, which numerically represent the degree of individual deterioration, using predetermined interval reference values, amplitude reference values, and baseline reference values, based on the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline, respectively. The above-mentioned deterioration calculation unit calculates the deterioration degree based on the above-mentioned interval index, above-mentioned amplitude index, and above-mentioned baseline index. It is characterized by the following:

[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 exacerbation degree, which is the final index, 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 a respiratory disease evaluation apparatus according to an embodiment, the interval reference value, the amplitude reference value, and the baseline reference value each include statistical values of clinical data of a plurality of different subjects.

[0017] In this respiratory disease evaluation apparatus according to an embodiment, the interval reference value, the amplitude reference value, and the baseline reference value each include statistical values (for example, median, quartile range, mean value, and standard deviation) of clinical data of a plurality of different subjects. Therefore, the intermediate index calculation unit can calculate the interval index, the amplitude index, and the baseline index for the subject as the intermediate index for the subject, respectively, based on the statistical values of the clinical data of a plurality of different subjects. Thereby, the degree of worsening of the interval, the degree of worsening of the amplitude, and the degree of worsening of the baseline for the subject can be reflected in the degree of worsening as the final index based on the statistical values of objective clinical data. As a result, the degree of worsening of the respiratory disease of the subject can be evaluated more accurately.

[0018] In a respiratory disease evaluation apparatus according to an embodiment, the respiratory disease is bronchial asthma or chronic obstructive pulmonary disease (COPD).

[0019] In this respiratory disease evaluation apparatus according to an embodiment, the degree of worsening of bronchial asthma or chronic obstructive pulmonary disease as the respiratory disease of the subject can be evaluated accurately.

[0020] In a respiratory disease evaluation apparatus according to an embodiment, it further includes an output unit that outputs the degree of worsening as an image, the image includes, for a certain subject over a certain period, the degrees of worsening acquired a plurality of times on a plane including a first axis representing the elapsed time and a second axis representing the degree of worsening, as a line graph and is characterized by this.

[0021] In the respiratory disease evaluation apparatus of this embodiment, the output unit outputs an image including, as a line graph, the exacerbation degrees obtained for a certain subject over a certain period on a plane including a first axis representing the elapsed period and a second axis representing the exacerbation degree. Therefore, a user (referring to, for example, a subject such as a patient, or a medical worker such as a doctor or a nurse) can intuitively grasp the remission or exacerbation trend of the symptoms of the respiratory disease for the subject by looking at the image. For example, when the subject is an asthma patient undergoing home treatment, if it is found by looking at this image that the symptoms of the respiratory disease including the subject's own asthma tend to worsen, the subject can take measures such as inhaling a medicine solution, taking medicine, or visiting a doctor.

[0022] In a respiratory disease evaluation apparatus of an embodiment, it further includes an output unit that outputs the exacerbation degree as an image, where the image includes, as a graph, the distribution of the exacerbation degrees obtained for a plurality of different subjects along a third axis on a plane including the third axis representing the exacerbation degree. It is characterized by this.

[0023] In the respiratory disease evaluation apparatus of this embodiment, the output unit outputs an image including, as a graph, the distribution of the exacerbation degrees obtained for a plurality of different subjects along a third axis on a plane including the third axis representing the exacerbation degree. Therefore, a user (typically a doctor) can intuitively grasp the distribution of the exacerbation degrees of the respiratory disease for the plurality of different subjects by looking at the image. Further, the doctor as a user can intuitively grasp where the patient being examined by the doctor himself / herself is located within the distribution of the exacerbation degrees among the plurality of different subjects. Therefore, it becomes easier for the doctor to determine a prescription for the patient and the doctor is assisted.

[0024] In a respiratory disease evaluation apparatus of an embodiment, it includes a housing that integrally houses the sensor unit, the feature amount extraction unit, the breathing period specifying unit, the variation amount calculation unit, and the exacerbation degree calculation unit. It is characterized by the following:

[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, A first housing integrally houses the sensor unit and a transmission unit that transmits the output of the sensor unit, A second housing integrally houses a receiving unit that receives the output of the above-mentioned sensor unit wirelessly or via wire from the above-mentioned transmitting unit, the above-mentioned feature extraction unit, the above-mentioned respiratory period identification unit, the above-mentioned variation amount calculation unit, and the above-mentioned exacerbation degree calculation unit. It is characterized by having the following features.

[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 context, the respiratory disease assessment method of this disclosure is A respiratory disease assessment method configured to evaluate the degree of exacerbation of a subject's respiratory disease, The photoplethysmography signal corresponding to the pulse rate of the subject described above is acquired in time series by a sensor. Based on the pulse waveform represented by the above time-series photoplethysmography signal, feature quantities including at least the interval, amplitude, and baseline of the pulse waveform are extracted for each beat. Based on the pulse wave waveform described above, the respiratory period corresponding to each breath of the subject is identified, and this respiratory period is a period containing multiple consecutive beats. From the pulse wave waveform described above, the variation in the interval, the variation in the amplitude, and the variation in the baseline are calculated for each evaluation interval set to correspond to one or more consecutive respiratory periods. Based on the variation in the interval, the variation in the amplitude, and the variation in the baseline within the evaluation interval, the degree of exacerbation, which numerically represents the degree of exacerbation of the respiratory disease in the subject, is calculated. It is characterized by including the following.

[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. [Effects of the Invention]

[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. [Brief explanation of the drawing]

[0031] [Figure 1] 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 2] This figure shows the functional block configuration of the respiratory disease evaluation device described above. [Figure 3] Figure 3(A) shows a configuration in which the sensor unit included in the respiratory disease evaluation device consists of a transmissive photoplethysmography sensor and detects a photoplethysmography signal from the subject's finger. Figure 3(B) shows a configuration in which the sensor unit included in the respiratory disease evaluation device consists of a reflective photoplethysmography sensor and detects a photoplethysmography signal from the subject's finger. [Figure 4] This diagram shows the flow of the respiratory disease evaluation method, from acquiring a photoplethysmography signal using the respiratory disease evaluation device described above to outputting the degree of exacerbation. [Figure 5] Figures 5(A) and 5(B) schematically illustrate the waveform of the photoplethysmography signal and the characteristic quantities, including at least interval, amplitude, and baseline, that should be extracted from the photoplethysmography signal. [Figure 6] 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. [Figure 7] This diagram shows the data flow from the photoplethysmography signal to the calculation of the severity of the condition. [Figure 8] Figures 8(A-1), 8(B-1), 8(C-1), and 8(D-1) illustrate the above-mentioned photoplethysmography signal, interval variation, amplitude variation, and baseline variation acquired when a subject's asthma is stable, respectively. Figures 8(A-2), 8(B-2), 8(C-2), and 8(D-2) illustrate the above-mentioned photoplethysmography signal, interval variation, amplitude variation, and baseline variation acquired when the subject's asthma is exacerbated, respectively. [Figure 9] Figure 9(B) shows the interval index, amplitude index, and baseline index, obtained as intermediate indices by the flow chart in Figure 4, compared between the stable and exacerbated states of the subject. Figure 9(C) shows the SpO2, pulse rate, and respiratory rate, obtained according to Patent Document 1 (US 11160459 A), with the evaluation interval not corresponding to the respiratory period, compared between the stable and exacerbated states of the subject. Figure 9(D) shows the interval index, amplitude index, and baseline index, obtained simulated according to Patent Document 2 (JP 2004-121668 A), with the evaluation interval not corresponding to the respiratory period, compared between the stable and exacerbated states of the subject. The leftmost Figure 9(A) shows the severity as determined by the physician, compared between the stable and exacerbated states of the subject. [Figure 10]Figure 10(A) is an image that includes a line graph showing the degree of exacerbation obtained multiple times over a certain period for a certain asthma patient, following the flow chart in Figure 4. Figure 10(B) is an image that similarly includes a line graph showing the degree of exacerbation obtained multiple times over a certain period for a certain COPD patient. Figure 10(C) is an image that similarly includes a line graph showing the degree of exacerbation obtained multiple times over a certain period for a healthy individual. [Figure 11] Figure 4 shows an image containing a graph of different exacerbation distributions obtained for multiple different subjects, as shown in the flowchart. [Figure 12] Figure 12(A) is a perspective view showing the external appearance of a respiratory disease evaluation device according to another embodiment of the present invention. Figure 12(B) shows the respiratory disease evaluation device in a configuration attached to the wrist of a subject. [Figure 13] Figure 13(A) is a perspective view showing the external appearance of a respiratory disease evaluation device according to yet another embodiment of the present invention. Figure 13(B) shows the respiratory disease evaluation device attached to the base of a subject's finger. [Modes for carrying out the invention]

[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] This 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 any finger on 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 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] The sensor unit 2 may consist of a known reflective photoplethysmography sensor, as shown in Figure 3(B). In this example, the reflective photoplethysmography sensor shown in Figure 3(B) 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 underside of the fingertip 90, and further includes a phototransistor 22 arranged side by side between the light-emitting diodes 21A and 21B. This allows for the detection of a photoplethysmography signal PPG from the subject's finger.

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

[0041] The memory unit 5 includes RAM (Random Access Memory), which is used as a working area necessary for the control unit 4 to execute a program, and ROM (Read Only Memory), which stores the program to be executed by the control unit 4. The memory unit 5 also stores the signals output by the sensor unit 2 and the information obtained by processing those signals in chronological order over a certain period of time.

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

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

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

[0045] The power supply unit 8 consists of dry cell batteries (not shown in the figure; in this example, two AAA batteries), and when the push-button switch 9 is turned on, it supplies power from these batteries to each part of the respiratory disease evaluation device 1. The power supply unit 8 may also have a power-off function that automatically stops the power supply if no pulse is detected for a certain period of time.

[0046] In this example, the sensor unit 2, control unit 4, memory unit 5, display unit 6, operation unit 9, communication unit 7, and power supply unit 8 are all housed together in the main unit 1M, allowing the respiratory disease evaluation device 1 to be compactly constructed. This makes it convenient for users of the respiratory disease evaluation device 1 (including subjects such as patients, and medical professionals such as doctors or nurses).

[0047] (Device operation) Figure 4 shows the flow of the respiratory disease evaluation method, from acquiring the photoplethysmography signal using the respiratory disease evaluation device 1 to outputting the degree of exacerbation.

[0048] With the main unit 1M (and 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. Then, 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 refers to 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 points sp, sp. However, since the signal intensity at the peak point pp is greater than the signal intensity at the rising edge 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 refers to the difference in signal intensity between the rising edge point sp and the peak point pp of a certain pulse wave (peak). The "baseline" Ba of the pulse wave waveform refers to the signal intensity at the rising edge point sp.

[0051] In this embodiment, three feature quantities are extracted from the pulse wave waveform represented by the photoplethysmography 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 formed 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 7 respiratory periods in this example), respectively. For reference, Figure 6(A) also shows the movement of the subject's thoracic cage during each breath as the waveform of the thoracic cage signal Ch.

[0053] Next, as shown in step S106 of Figure 4, the control unit 4 acts as a respiratory period identification unit, in this example detecting 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. Figure 6(A) illustrates three consecutive respiratory periods Tb0, Tb1, and Tb2. 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 variation calculation unit and, in this example, sets the one-breath period Tb1 shown in Figure 6(A) as the evaluation interval. Furthermore, as shown in step S108, it calculates the interval variation TcD1, the amplitude variation AmD1, and the baseline variation BaD1 during this one-breath period Tb1.

[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 (1 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 (1 respiratory period) Tb1. That is, AmD1 = AmMax - AmMin.

[0057] As shown in Figure 6(D), the baseline variability BaD1 is defined as the difference between the maximum value BaMax and the minimum value BaMin of the baseline in the evaluation interval (1 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, interval index Pc1, amplitude index Pa1, and baseline index Pb1, which numerically represent the degree of individual deterioration, from the amplitude fluctuation amount TcD1, amplitude fluctuation amount AmD1, and 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 (1 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 level.

[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: the stable period data 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. In other words, TcD1 / TcRef1=Pc1 AmD1 / AmRef1=Pa1 BaD1 / BaRef1=Pb1 … (Eq.1) That is the case.

[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, baseline variation) during a stable period for a certain subject. 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) TIFF2026085459000002.tif57148

[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) That is the case.

[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) 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 subject during stable (symbolized by St) and exacerbated (symbolized by Ex) asthma conditions, respectively, as shown in Figures 8(A-1) and 8(A-2). 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). 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 was set to N=10.

[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 asthma exacerbation in the subjects.

[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 box plots comparing stable St and exacerbation Ex for the above sample group, with the evaluation interval independent of the respiratory period, and SpO2 (%), pulse rate (bpm), and respiratory rate (bpm) measured as described in Patent Document 1 (US 11160459 A). A Wilcoxon signed-rank test was performed on these results, similar to that in Column 9(B). The t-values ​​were t=18 for SpO2, t=23 for pulse rate, and t=18 for respiratory rate (the p-values ​​were p=0.333 for SpO2, p=0.646 for pulse rate, and p=0.333 for respiratory rate). 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, the SpO2 (%), pulse rate (bpm), and respiratory rate (bpm) measured as described in Patent Document 1 cannot be said to reflect the degree of exacerbation of the subject's asthma.

[0071] Column 9(D) shows box plots comparing stable St and exacerbation Ex when the intervals for the above sample group are calculated using a simulated interval index (represented by the symbol Pc1′), amplitude index (represented by the symbol Pa1′), and baseline index (represented by the symbol Pb1′), respectively, with the evaluation intervals not corresponding to the respiratory period. 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 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, 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 cannot be said to 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] (Variation 1) In the example above, 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 may be set as the evaluation interval, for example, three consecutive respiratory periods as shown in Figure 6(A).

[0074] (Modification 2) In the example above, 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 from the interval index Pc1, amplitude index Pa1, and baseline index Pb1 included in the intermediate index, with the index having the largest value (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 (= 4.1), which has the largest value, 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 a severity 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 severity I1 (weighted average method). In that case, if the weighting coefficients are, for example, α, β, and γ, the severity I1 will be: (α·Pc1+β·Pa1+γ·Pb1) / 3=I1 … (Eq.3) It is calculated by the following. The weighting coefficients α, β, and γ can be determined experimentally, for example, to increase the correlation between the exacerbation degree I1 calculated by this equation (Eq.3) and the severity determined by the physician (shown in column 9(A) of Figure 9).

[0076] (Variation 3) In the example above, the control unit 4 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, 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 unit 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 that 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 with COPD, the exacerbation grade 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, the user can intuitively grasp the trend of remission or worsening of the subject's COPD symptoms by looking at this image.

[0080] Furthermore, Figure 10(C) shows an example where, when the subject is healthy, the exacerbation grade 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 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 in 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 a background color. Furthermore, the plot points I1d, I1d, ... may be colored with only one color (for example, black).

[0082] (Modification 4) In the example above, the interval reference value TcRef1, amplitude reference value AmRef1, and baseline reference value BaRef1 were, but are not limited to, data from the subject's own respiratory disease (asthma in this example) during a stable period. 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 pre-set 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 pre-set 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 variation BaD1, instead of the previously described baseline reference value BaRef1, the mean value of clinical data from the above 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 were assumed to be the interval fluctuation TcD1 = 20.4 (bpm), the amplitude fluctuation AmD1 = 0.075 (dimensionless), and the baseline fluctuation BaD1 = 0.056 (dimensionless). (Table 2) TIFF2026085459000003.tif73149

[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. In other words, (Pc² + Pa² + Pb²) / 3 = I² … (Eq. 5) Therefore, according to the numerical example above, the exacerbation degree I2 is calculated as 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, amplitude fluctuation AmD1, and baseline fluctuation BaD1. As a result, the degree of asthma exacerbation in the subject can be evaluated with greater accuracy.

[0088] (Variation 5) As explained in Modification 4 above, clinical data from multiple different subjects (asthma patients), including interval index Pc2, amplitude index Pa2, baseline index Pb2, and exacerbation degree I2, are 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 at the time of examination for each case. (Table 3) TIFF2026085459000004.tif83147

[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 of the distribution of exacerbation degree I2 obtained for multiple different subjects (asthma patients) along vertical axes V1 and V2 on a plane Q2 which includes a left vertical axis V1 as a third axis representing exacerbation degree I2 and a right vertical axis V2 representing attack intensity. 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 (but is not limited to these values). In this example, the background colors for 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 ​​for Th21, Th22, and Th23 are not limited to Th21=-0.50, Th22=0.50, and Th23=2.00. The threshold values ​​for Th21, Th22, and Th23 can be determined experimentally to maximize the correlation between the calculated exacerbation level I2 and the seizure intensity (on a 4-point scale) as assessed by a physician.

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

[0093] (Experimental variation 6) In the example above, 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 with 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] (Example 7) In the example above, 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 the calculation process (flowchar 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 transmitter. The smartphone 30 and personal computer 40 are assumed to be equipped with input / output interfaces 37 and 47 which act as receivers and are capable of receiving the photoplethysmography signal PPG, respectively. 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, the ring member 211 is attached to the base 290 of the subject's finger, as shown in Figure 13(B). 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 examples (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 (Computer 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 above embodiments 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. [Explanation of symbols]

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

Claims

1. A respiratory disease assessment device configured to evaluate the degree of exacerbation of a subject's respiratory disease, A sensor unit that acquires a photoplethysmography signal corresponding to the pulse rate of the subject in a time series, A feature extraction unit extracts feature quantities for each beat that include at least the interval, amplitude, and baseline of the pulse wave waveform shown by the above time-series photoplethysmography signal, based on the pulse wave waveform shown above. The system includes a respiratory period identification unit that identifies the respiratory period corresponding to each breath of the subject based on the pulse wave waveform, wherein the respiratory period is a period that includes multiple consecutive beats. A variation calculation unit calculates the variation in the interval, the variation in the amplitude, and the variation in the baseline within an evaluation interval set to correspond to one or more consecutive respiratory periods, based on the pulse wave waveform described above. An exacerbation degree calculation unit calculates an exacerbation degree that numerically represents the degree of exacerbation of the respiratory disease of the subject, based on the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline within the evaluation interval. A respiratory disease evaluation device characterized by being equipped with [a specific feature].

2. In the respiratory disease evaluation device according to claim 1, The system includes an intermediate indicator calculation unit that calculates interval indicators, amplitude indicators, and baseline indicators, which numerically represent the degree of individual deterioration, using predetermined interval reference values, amplitude reference values, and baseline reference values, based on the amount of variation in the interval, the amount of variation in the amplitude, and the amount of variation in the baseline, respectively. The above-mentioned deterioration calculation unit calculates the deterioration degree based on the above-mentioned interval index, above-mentioned amplitude index, and above-mentioned baseline index. A respiratory disease evaluation device characterized by the following features.

3. In the respiratory disease evaluation device according to claim 2, The above interval reference value, amplitude reference value, and baseline reference value include data from the subject's own respiratory disease during a stable period. A respiratory disease evaluation device characterized by the following features.

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

5. A respiratory disease evaluation device according to any one of claims 1 to 4, The respiratory disease mentioned above is either bronchial asthma or chronic obstructive pulmonary disease. A respiratory disease evaluation device characterized by the following features.

6. A respiratory disease evaluation device according to any one of claims 1 to 4, The system further includes an output unit that outputs the above degree of deterioration as an image, The image above is a line graph on a plane that includes a first axis representing the elapsed time and a second axis representing the degree of exacerbation, showing the degree of exacerbation obtained multiple times over a certain period for a given subject. A respiratory disease evaluation device characterized by the following features.

7. A respiratory disease evaluation device according to any one of claims 1 to 4, The system further includes an output unit that outputs the above degree of deterioration as an image, The image above includes a plane containing a third axis representing the degree of exacerbation, and contains a graph of the distribution of exacerbation levels obtained for multiple different subjects along the third axis. A respiratory disease evaluation device characterized by the following features.

8. In the respiratory disease evaluation device according to claim 1, The housing comprises the sensor unit, the feature extraction unit, the respiratory period identification unit, the variation amount calculation unit, and the exacerbation degree calculation unit, all integrated into one unit. A respiratory disease evaluation device characterized by the following features.

9. In the respiratory disease evaluation device according to claim 1, A first housing integrally houses the sensor unit and a transmission unit that transmits the output of the sensor unit, A second housing integrally houses a receiving unit that receives the output of the above-mentioned sensor unit wirelessly or via wired connection from the above-mentioned transmitting unit, the above-mentioned feature extraction unit, the above-mentioned respiratory period identification unit, the above-mentioned variation amount calculation unit, and the above-mentioned exacerbation degree calculation unit. A respiratory disease evaluation device characterized by being equipped with [a specific feature].

10. A respiratory disease assessment method configured to evaluate the degree of exacerbation of a subject's respiratory disease, The photoplethysmography signal corresponding to the pulse rate of the subject described above is acquired in time series by a sensor. Based on the pulse waveform represented by the above time-series photoplethysmography signal, feature quantities including at least the interval, amplitude, and baseline of the pulse waveform are extracted for each beat. Based on the pulse wave waveform described above, the respiratory period corresponding to each breath of the subject is identified, and this respiratory period is a period containing multiple consecutive beats. From the pulse wave waveform described above, the variation in the interval, the variation in the amplitude, and the variation in the baseline are calculated for each evaluation interval set to correspond to one or more consecutive respiratory periods. Based on the variation in the interval, the variation in the amplitude, and the variation in the baseline within the evaluation interval, the degree of exacerbation, which numerically represents the degree of exacerbation of the respiratory disease in the subject, is calculated. A method for evaluating respiratory diseases, characterized by including the following.

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