JPH11104090A - Heart function diagnostic device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To diagnose conditions regarding heart functions using simple constitution without processing more than one cycle of the waveform of a pulse wave. SOLUTION: A heart function diagnostic device includes: a pulse wave detecting part 10 detecting time waveform of a pulse wave from a living body; a peak point extraction/waveform analysis part 40 specifying the ventricular systole of the heart from the waveform of the pulse wave and calculating the difference of blood pressure value corresponding to the amplitude of a declining wave during the ventricular systole; and an evaluation part 72 calculating the rate of change in the difference of blood pressure value. The contents of diagnosis corresponding to the specified rate of change in the difference of blood pressure value are read from an evaluation content storage part 73 and reported by a reporting part 74.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention analyzes a part or all of a pulse wave waveform detected at a peripheral part of a subject corresponding to a systole of the heart to diagnose the heart function of the subject.・ Related to a cardiac function diagnostic device to be evaluated.

[0002]

2. Description of the Related Art A pulse wave is, generally speaking, a wave of blood that is emitted from the heart and propagates through blood vessels. Therefore, it is known that various medical information can be obtained by detecting and analyzing a pulse wave. As pulse wave research progresses, various techniques are used to analyze pulse waves collected from a living body to obtain information that cannot be understood from blood pressure and heart rate. It has become possible to diagnose. Here, the same inventor as the present application paid attention to the relationship between the shape of the pulse wave waveform and the distortion factor in PCT / JP96 / 01254 (name of the invention: diagnostic device and control device for biological condition). The invention according to this application detects and processes a pulse waveform of a subject, calculates a distortion rate of the pulse waveform, and specifies the shape of the pulse waveform from the distortion rate to thereby determine the shape of the subject's living body. It was possible to diagnose the condition.

Here, the relationship between the shape of the pulse waveform and the distortion factor described in the above application will be briefly described. First, there are various classifications of pulse waveforms, and the shapes are also various. Here, a typical pulse waveform shape according to the classification of Chinese medicine, which is one of Oriental tradition medicines, will be described. FIGS. 27A to 27C are diagrams showing typical pulse waveform shapes according to this classification.
The shape of the pulse wave waveform shown in FIG. 3A is called a “flat pulse” and is a pulse of a normal healthy person. As shown in the figure, the "flat vein" is characterized by a slow and relaxed rhythm, a constant rhythm, and little disturbance. Next, the shape of the pulse wave waveform shown in FIG. 3B is called "smooth vein", which is a pulse of a person having an abnormal blood flow state, and falls immediately after rising suddenly, resulting in an aortic notch. It is characterized by the fact that the peak cuts deeper and the subsequent peak is much higher than usual. The “slip vein” is a disease in which the traffic of the pulse is extremely diverted due to diseases such as edema, hepatorenal disease, respiratory disease, gastrointestinal disease, and inflammatory disease.
It is thought that it occurs smoothly. The shape of the pulse wave waveform shown in FIG. 3C is called a "chord vein", and is a pattern of a person whose blood vessel wall has an increased degree of tension. The feature is that the state lasts for a certain period of time. These "chord veins" are caused by diseases such as hepatobiliary disease, skin disease, high blood pressure, and painful disease. The tension of the autonomic nervous system causes the blood vessel wall to become less elastic, which causes the pumped blood to pulsate. It is considered that this is because the influence of is difficult to appear. In the graphs of FIGS. 6A to 6C, the vertical axis and the horizontal axis are blood pressure (mmH), respectively.
g), time (seconds).

[0004] The shape of such a pulse wave waveform and the distortion factor d have a correlation as shown in FIG. Here, the distortion rate d of the pulse waveform is determined by the following equation (1).

[0005]

(Equation 1)

In this equation (1), A ₁ is the amplitude of the fundamental wave component in the pulse wave, and A ₂ , A ₃ ,.
_n is the amplitude of the second, third and nth harmonic components of the pulse wave, respectively. Thus, detecting a pulse waveform of a subject, for example, by calculating the distortion factor d and respectively determined amplitudes A ₁ to A _n by performing FFT (Fast Fourier Transform) processing,
The shape of the pulse wave waveform can be quantitatively specified by the correlation shown in FIG. 28, and the heart function state of the subject can be diagnosed.

[0007]

However, in the above-mentioned prior art, the relationship between the pulse wave waveform and the cardiac function state is only indirectly described through the waveform distortion rate. Did not directly mention the relationship. For this reason, when analyzing the pulse wave waveform, it is necessary to obtain the magnitude of the amplitude of the fundamental wave and each higher harmonic component by performing FFT processing or the like on at least one cycle of the pulse wave waveform. There is a problem in that diagnosis requires high throughput. This problem is particularly noticeable when the size and weight of the diagnostic device are reduced.

SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and has as its object to identify which part of a pulse wave waveform indicates a cardiac function state, thereby achieving a simple configuration of the heart. An object of the present invention is to provide a cardiac function diagnostic device capable of diagnosing a functional state.

[0009]

According to the present invention, there is provided a pulse wave detecting means for detecting a pulse wave waveform from a living body, and a systole for identifying a systole of the heart from the pulse wave waveform. Phase identification means, analysis means for analyzing a part or all of the waveform corresponding to the systole identified by the systole identification means in the pulse wave waveform, based on the analysis results by the analysis means, And evaluating means for evaluating the cardiac function state of the living body.

[0010]

BEST MODE FOR CARRYING OUT THE INVENTION

<1: First Embodiment> First, a cardiac function diagnostic apparatus according to a first embodiment of the present invention will be described.

<1-1: Rationale of First Embodiment> Needless to say, the heart ejects blood by repeating contraction and expansion. Here, the time during which blood flows out of the heart by one cycle of contraction and expansion is referred to as ejection time. This ejection time tends to become shorter as the number of beats, which is the number of contractions of the heart per unit time, becomes higher due to exercise or the like, as a result of release of catecholamines such as adrenaline. This means that the contractile force of the myocardium is increasing. Also, as this ejection time gets longer,
One cycle of contraction and expansion tends to increase the volume of output from the heart. When a person exercises or the like, a large amount of oxygen needs to be supplied to the heart muscle, skeletal muscle, and the like, so that the product of the number of beats and the amount of stroke, that is, the flow rate of blood sent from the heart per unit time increases. Here, as a result of the increase in the number of beats, the ejection time is shortened, and consequently, the ejection amount is reduced. However, since the rate of increase in the number of beats exceeds the rate of decrease in the amount of stroke, the product of the number of beats and the amount of stroke increases as a whole.

Next, the relationship between the movement of the heart and the blood pressure waveform will be described. FIG. 15A shows an electrocardiographic waveform. Generally, a period from point R to end point U of a T wave in the figure is referred to as a ventricular systole, which corresponds to the ejection time. It is said that the period from point U to the next point R is ventricular diastole. Here, during the ventricular systole, the contraction of the ventricle does not occur uniformly, but becomes slow as the contraction progresses from the outside to the inside. Therefore, the blood pressure waveform at the aortic root immediately after the heart has an upwardly convex shape during the ventricular systole from the opening of the aortic valve to the closing thereof, as shown in FIG.

The blood pressure waveform at the aortic root is represented by
An example of the waveform at the peripheral portion (radial artery) is shown in FIG. That is, FIG. 9C shows an example of a pulse waveform at the erasing unit. The first wave, called an ejection wave, is generated by the ejection of blood from the heart.
It is thought that a second wave called a regression wave is generated due to reflection at a blood vessel bifurcation near the heart, and thereafter, a notch is generated due to aortic valve closure, and a third wave called a notch wave appears. Have been. Therefore, in the pulse wave waveform, the point from the lowest blood pressure value to the notch corresponds to ventricular systole, and the point from the notch to the lowest blood pressure value in the next cycle corresponds to ventricular diastole. . Here, the point corresponding to the aortic valve release in the pulse waveform is the minimum minimum point of the blood pressure value, and the point corresponding to the aortic valve closure in the pulse waveform is
Seen in chronological order, it is the third minimum point that appears from the minimum minimum point, and when viewed from the magnitude of the blood pressure value, it is the second minimum point from the minimum minimum point. Although the pulse waveform shown in FIG. 3C is actually delayed in time with respect to the aortic blood pressure waveform shown in FIG. 3B, for the sake of explanation, this time delay is ignored here. The phases are aligned.

Next, the pulse waveform shown in FIG. The pulse wave waveform detected in the peripheral part of the subject is, as it were, a pressure wave of blood that has passed through a closed system composed of a pulsatile pump heart and a vascular system as a conduit.
In addition to being defined by the pump function of the heart, that is, the cardiac function state, secondly, it is affected by blood vessel diameter, contraction / extension of blood vessels, blood viscosity resistance, and the like. For this reason, it is considered that, by detecting and analyzing the pulse wave waveform, it is possible to evaluate the state of the heart function in addition to the state of the arterial system of the subject.

Here, it is examined which part of the pulse waveform is to be analyzed. First, as mentioned above,
Since the contraction of the ventricle does not occur uniformly, the blood from the heart is pumped at the maximum pressure during the ventricular systole as shown in FIG. On the other hand, blood pumped from the heart reaches the peripheral part under the influence of the vascular system. Therefore, the regression wave generated by the reflection at the blood vessel bifurcation near the heart should be determined by the equilibrium between the pressure characteristic of the blood pumped by the contraction of the ventricle and the blood vessel characteristic of the side from which the blood is pumped. It is.

Considering the significance of the pressure characteristics of the blood pumped by the contraction of the ventricle, the inner volume generally does not change much even when the heart is enlarged, even if the ventricle contracts. It is believed that blood is no longer pumped out of the heart. This is the same even when the contractile force of the heart muscle is reduced for some reason. On the other hand, considering the significance of the latter vascular characteristics, the contraction and extensibility of the blood vessels change depending on the psychological state and diseases of the autonomic nervous system. Because it ’s hard to appear,
It is considered that the reflow wave is less likely to appear, and conversely, if the blood vessels tend to be softened, the effect of the reflection due to the elasticity appears, so that the regression wave is also likely to appear remarkably. Here, the tide wave has an effect on the pressure characteristics of the pumped blood and the blood vessel characteristics on the side from which the blood is pumped, specifically, the characteristics of the heart that pumps the blood and the aortic origin to the peripheral region. It is thought to be formed under the influence of both the characteristics of the arterial system. It is thought that it will be possible to make a comprehensive evaluation. In addition, as a method of analyzing the retiring wave, it is possible to obtain an index that defines the retiring wave, or to analyze the frequency of the retiring wave. Here, as the index, for example, the amplitude and period of the regression wave, and a value obtained by normalizing these values with the ventricular contraction period and the minimum and maximum blood pressure values, and the like can be considered. Deployment is conceivable. In addition, these rates of change over time are also considered useful.

By the way, the present inventor simulates the behavior of the arterial system from the aortic root to the peripheral part by an electric model in order to determine the state of circulation (blood circulation) in a non-invasive manner. A technique for approximately calculating parameters relating to circulatory dynamics such as resistance and compliance has been proposed (Japanese Patent Laid-Open No. 6-205747: "Pulse wave analyzer", PCT / JP96 / 03211: "Title of invention" Biological condition measuring device ”). In short, this technique provides an electrical model that simulates the behavior of the arterial system, when an electrical signal corresponding to the pressure wave at the aortic root of the subject is given,
By calculating the values of the circulatory dynamics corresponding to each element by determining the values of each element constituting the electrical model so that the response waveform matches the actually detected pulse waveform. It is. For this electrical model,
There are a four-element lumped parameter model as shown in FIG. 18A and a five-element lumped parameter model as shown in FIG. In particular, regarding the latter five-element lumped parameter model, among the factors that determine the behavior of the circulatory dynamics of the human body, the inertia due to blood in the central part and the blood vessel due to blood viscosity in the central part used in the four-element lumped parameter model Resistance (viscous resistance), peripheral blood vessel compliance (viscoelasticity), and peripheral blood vessel resistance (viscous resistance)
In addition, these parameters were modeled as electrical circuits with the addition of aortic compliance.

The correspondence between each element constituting the lumped parameter model and each parameter will be described below. Capacitance C _c : aortic compliance [cm ⁵ / dyn] Electric resistance R _c : vascular resistance due to blood viscosity at central part of arterial system [dyn · s / cm ⁵ ] Inductance L: inertia due to blood at central part of arterial system [Dyn · s ² / cm ⁵ ] Capacitance C: vascular compliance at the peripheral part of the arterial system [cm ⁵ / dyn] Electric resistance R _p : vascular resistance due to blood viscosity at the peripheral part of the arterial system [dyn · s / cm] ⁵ ]

The currents i and i flowing through the lumped parameter model
_p, i _c, i _s is blood flowing through the respective units, each corresponding [cm ⁵ /
s]. Among them, the current i corresponds to the aortic flow, current i _s is equivalent to blood flow pumped out from the left ventricle. The input voltage e corresponds to the left ventricular pressure [dyn / cm ² ], and the voltage v ₁ corresponds to the pressure [dyn / cm ² ] at the aortic root. Further, the terminal voltage v _p of the capacitance C corresponds to the pressure [dyn / cm ² ] at the radial artery. In addition, the diode D is equivalent to an aortic valve, and is turned on (in a state where the valve is open) during a period corresponding to the systole of the ventricle, and is turned off (when the valve is closed) during a period corresponding to diastole. State).

As described above, the arterial system from the aortic root to the peripheral part can be simulated by an electric model shown in FIGS. 18A and 18B. Here, when the arterial system is considered as a kind of electric model, the pulse waveform in the ventricular systole will be considered again. The blood pressure waveform at the aortic root during the ventricular systole is a single gentle wave having a convex shape as shown in FIG. 15B, whereas the pulse wave waveform at the peripheral portion during the ventricular systole is As shown in FIG. 3C, there are two waves, an ejection wave and a retreating wave. Considering this phenomenon by replacing the above electric model with the electric model, if an electric signal corresponding to the waveform of FIG. 3B is applied as a pulse to the input terminal of the electric model, This means that the first waveform responding to the input pulse and the second waveform following this waveform have appeared, and that the second waveform has appeared during the input pulse application period. Therefore, the regression wave corresponding to the second waveform is obtained when the power supply of the heart is connected to the load of the arterial system, and when the power supply of the heart is operating, that is, when the aortic valve is open. , Due to the difference in impedance between the two. And even in this case, the regression wave can be said to be a waveform determined by the characteristics of the heart and the characteristics of the arterial system. For this reason, analyzing the vicinity of the tidal wave leads to the evaluation of inconsistency between the heart and the arterial system in addition to the enlargement of the heart, the function of the myocardium, diseases and psychological conditions affecting blood vessels, and the like. ,it is conceivable that.

Next, the inventor of the present application has determined waveform parameters for defining the characteristics of the pulse waveform as shown in FIG. That is, the waveform parameter is set as follows: the time t ₆ from the rising peak point P0 (minimum minimum point) of one pulse to the rising peak point P6 of the next pulse, and the pulse wave waveform appearing peak point (maximum point and minimum point) P1 to P5 of the blood pressure value (difference) y ₁ ~y _5, and, from the peak point P0, the elapsed time t ₁ ~t ₅ to each peak point P1 to P5 appear Stipulated. In this case, each of y _{1 to} y ₅ indicates a relative blood pressure value based on the blood pressure value at the peak point P0.

Further, the inventor of the present application detected pulse waves from 74 healthy adults aged 22 to 46 years old, obtained these waveform parameters, and measured the pulse rate from the pulse waveforms. . On the other hand, the inventor of the present application examined the individual correlation between each waveform parameter alone and the difference between them for the actually measured beats. As a result, it was found that the pulse rate had a high correlation with the correlation coefficient (R ² ) of 0.92 with respect to the period (t ₆ -t ₄ ) corresponding to the ventricular diastole. For this reason, if a configuration necessary for obtaining the period (t ₆ -t ₄ ) is adopted, the number of beats can be obtained from the correlation with the configuration.

<1-2: Functional Configuration of the Embodiment> The cardiac function diagnostic apparatus according to the present embodiment is configured based on the above-described theoretical basis. Detecting the waveform, secondly, analyzing the detected pulse waveform to identify the ventricular systole, thirdly, obtaining an index defining the regression wave in the identified ventricular systole, fourthly, The index is used to evaluate the subject's cardiac function status.
Here, in the present embodiment, an amplitude (a blood pressure parameter difference (y ₃ −y ₂ ) in terms of waveform parameters) is handled as an index for defining a regression wave, but the present invention is limited to this. It is not the purpose. Further, since it is generally known that the pulse rate is also a useful index for evaluating the cardiac function state, the cardiac function diagnostic apparatus according to the present embodiment evaluates the cardiac function state also with reference to the pulse rate. I decided to. Specifically, even if the person does not exercise very strongly, the number of beats, which is the number of times the heart contracts per unit time, may be high due to tension or stress, and in such a case, Since it may not be appropriate to evaluate the state of the cardiac function, in the present embodiment, the heart condition is provided on condition that the subject's body movement is not so large and the subject's pulse rate is below the threshold. Assess the state of the function. It should be noted that the pulse rate may be positively used as a judgment material for the evaluation of the cardiac function, or may not be detected on the premise described later.

FIG. 1 is a block diagram showing a functional configuration of the cardiac function diagnostic apparatus according to the present embodiment. In this figure,
The pulse wave detection unit 10 is, for example, a peripheral part of a subject (for example,
A pulse wave waveform in the radial artery (radial artery) is detected, and the detection signal is output to the body movement removing unit 30 as MH. On the other hand, the body motion detection unit 20 is configured by, for example, an acceleration sensor, detects the motion of the body of the subject, and outputs the detection signal to the waveform processing unit 21 as a signal TH. The waveform processing unit 21 is configured by a low-pass filter or the like, and performs a waveform shaping process on the signal TH output from the body motion detection unit 20 and outputs the signal TH as a signal MHt indicating a body motion component. The body motion removing unit 30 subtracts the signal MHt indicating a body motion component from the signal MH from the pulse wave detecting unit 10 and outputs the result as a signal MH ′ indicating a pulse wave component.

The cardiac function diagnostic apparatus according to the present embodiment processes a pulse wave waveform detected from a subject. If the subject is accompanied by any movement, the pulse wave detecting unit 1
In addition to the signal MH 'indicating the pulse wave component, the signal MHt indicating the body motion component of the subject is superimposed on the signal MH detected by the zero. Therefore, MH = MHt + MH '
And the signal MH output from the pulse wave detector 10 does not accurately indicate the pulse waveform of the subject.

On the other hand, since the blood flow is affected by blood vessels and tissues, the body movement component MHt included in the signal MH is considered to be not the signal TH indicating the body movement of the subject but the signal TH. Can be For this reason, the waveform TH of the signal TH from the body motion detection unit 20 which directly indicates the body motion of the subject is shaped by the waveform processing unit 21, and the signal MH indicating the body motion component is obtained.
t, which is used as the signal MH by the pulse wave detector 10.
, Thereby removing the influence of the body movement to obtain the signal MH ′ indicating the pulse wave component. Note that the format of the low-pass filter, the number of stages, the constant, and the like in the waveform processing unit 21 are determined from actually measured data.

Next, the peak point extraction / waveform analysis unit 40
For the signal MH 'indicating the pulse wave component, information called "peak information" related to each of the peak points P0 to P6 relating to the waveform parameters is extracted to obtain the waveform parameters shown in FIG. The blood pressure value difference (y ₃ −y ₂ ) and the period (t ₆ −t ₄ ) corresponding to the amplitude of the tide wave are calculated from the parameters. The detailed configuration of the peak point extraction / waveform analysis unit 40 and the content of the peak information will be described later. Further, the peak point extraction / waveform analysis unit 40 determines the blood pressure value difference (y ₃ −
In determining y ₂ ) and time period (t ₆ -t ₄ ), peak points P0 and P4 are specified, which means that ventricular systole and ventricular diastole are necessarily specified. That is, since the peak point P0 corresponds to the rising start point of the ejection wave, finding this means specifying the start point of ventricular systole (end point of ventricular diastole), and the peak point P4 is Since this corresponds to a notch associated with aortic valve closure, it means specifying the end point of ventricular systole (start point of ventricular diastole). Therefore, the peak point extraction / waveform analyzer 40 necessarily has a function of specifying the ventricular systole and the ventricular diastole.

Now, the beat count conversion table 60 stores the time period (t
The correlation between _6- t ₄ ) and the number of beats is stored in advance, and the period (t _6- t ₄ ) obtained by the peak point extraction / waveform analysis unit 40 is converted into the number of beats. If the number of beats is directly or accurately obtained, the time t ₆ may be obtained by the peak point extraction / waveform analysis unit 40 and calculated from this converted value.

Next, the evaluation permitting section 70
Is less than or equal to the threshold value and the number of beats converted by the beat count conversion table 60 is equal to or less than the threshold value, the blood pressure value difference obtained by the peak point extraction / waveform analysis unit 40 is determined. (Y ₃ −y ₂ ) is output together with the current time. The data storage unit 71 stores the evaluation permission unit 7
The blood pressure value difference (y ₃ −y ₂ ) output by 0 and the time are stored as a set.

The evaluator 72 executes the following processing to determine the rate of change of the blood pressure value difference (y ₃ -y ₂ ). That is, first, the evaluation unit 72 sets the data storage unit 7
Read recently stored pressure value difference to 1 and (y ₃ -y ₂₎ time and, secondly, the blood pressure value difference between the present time outputted by the evaluation permission unit 70 from (y ₃ -y _2), read By subtracting the blood pressure value difference (y ₃ -y ₂ ), a change in the blood pressure value difference is obtained,
Third, the elapsed time is obtained by subtracting the read time from the current time, and fourth, the change in the blood pressure value difference is divided by the elapsed time to calculate the rate of change. Evaluation content storage unit 73
Is to store a plurality of evaluation contents in advance corresponding to the change rate of the blood pressure value difference, and to read out and output the evaluation contents corresponding to the change rate calculated by the evaluation unit 72. The notifying unit 74 outputs the diagnosis content read by the diagnosis content storage unit 73 and the time transition created by the time transition creating unit 75 to the outside by display, voice, or the like. Further, the temporal transition creating unit 75 includes the evaluation permitting unit 70
Output from the blood pressure value difference (y ₃ -y ₂₎ and time, or the data storage unit 71 stored in the chronologically blood pressure value difference from (y ₃ -y ₂₎ and time, the blood pressure value difference (y ₃ -y ₂ ) is created and output.

<1-2-1: Detailed Configuration of Peak Point Extraction / Waveform Analysis Unit> Here, the details of the peak point extraction / waveform analysis unit 40 will be described. FIG. 2 is a block diagram showing the detailed configuration. In the figure, a microcomputer 4
Reference numeral 01 controls each component, and has a register (not shown) therein. The waveform memory 402 is a RAM
The value of the signal MH ′ supplied through the A / D converter 403 and the low-pass filter 404,
That is, the waveform value W of the signal indicating the pulse wave component is sequentially stored. The waveform value address counter 405 counts the sampling clock φ while the microcomputer 401 outputs the waveform sampling instruction START and outputs the count result to the waveform value address ADR1 of the waveform value W.
(Write address). This waveform value address ADR1 is monitored by the microcomputer 401. The selector 406 selects an address to the waveform memory 402. When the microcomputer 401 does not output the select signal S1, the selector 406 selects the waveform value address ADR1 output by the waveform value address counter 405. , When the select signal S1 is output, the read address ADR4 output by the microcomputer 401
Select

On the other hand, the differentiating circuit 411 time-differentiates the waveform value W sequentially output from the low-pass filter 404 and outputs the resultant. The zero cross detection circuit 412 outputs a zero cross detection pulse Z when the time derivative of the waveform value W becomes zero due to the waveform value W becoming a maximum value or a minimum value. More specifically, the zero cross detection circuit 41
2 is the peak point P0 of the waveform parameter shown in FIG.
This circuit is provided for detecting P6, and outputs a zero cross detection pulse Z when a waveform value W corresponding to these peak points is input.

Next, the peak address counter 413
Waveform sampling instruction ST by microcomputer 401
While the ART is being output, the zero-cross detection pulse Z is counted, and the count result is used as the peak address ADR.
2 is output. Moving average calculation circuit 414
Accumulates the time differential value of the waveform value W output by the differentiating circuit 411 up to the present time for a predetermined number in the past, calculates the average value thereof, and expresses the result as the slope of the pulse wave up to the present time. It is output as inclination information SLP.

The peak information memory 415 is provided for storing the peak information shown in FIG. 3, and the details of the contents are as follows. Waveform value address ADR1 This is the waveform value address output from the waveform value address counter 405 when the waveform value W output from the low-pass filter 404 reaches the maximum value or the minimum value. In other words, it is the address where the waveform value W corresponding to the local maximum value or the local minimum value is written in the waveform memory 402. Peak type B / T This is information indicating whether the waveform value W written to the waveform value address ADR1 is a local maximum value T (Top) or a local minimum value B (Bottom). Waveform value W is a waveform value corresponding to the maximum value or the minimum value. Stroke information STRK is a change in waveform value from the immediately preceding peak value to the peak value. Slope information SLP This is the average value of the time derivative of a predetermined number of waveform values in the past up to the peak value.

<1-3: Operation of Embodiment> Next, the operation of the cardiac function diagnostic apparatus according to the embodiment shown in FIG. 1 will be described.

<1-3-1: Initial Measurement Operation> This heart function diagnostic apparatus performs the following measurement at regular time intervals. Therefore, the measurement operation performed for the first time will be described first. The body movement component accompanying the body movement of the subject is superimposed on the signal MH output by the pulse wave detection unit 10, but the body movement component is removed by the body movement component removal unit 30, and only the pulse wave component is removed. The signal MH ′ is supplied to the peak point extraction / waveform analysis unit 40. The peak point extraction / waveform analysis unit 40 accumulates and analyzes the data of the signal MH ′ as described later, specifies the waveform parameters of the pulse wave waveform, and among them, the blood pressure corresponding to the amplitude of the tide wave. Value difference (y ₃ -y ₂ ) and the period corresponding to ventricular diastole (t _6-
t ₄ ) are obtained. Of these, the period (t _6-
t ₄ ) is converted into a beat count by the beat count conversion table 60.

In the evaluation permitting section 70, when the signal TH from the body motion detecting section 20 is equal to or less than the threshold value and the number of beats converted by the beat count conversion table 60 is equal to or less than the threshold value. The peak point extraction / waveform analysis unit 40
The blood pressure value difference (y ₃ −y ₂ ) obtained by the above is output as it is together with the current time. Thereby, the blood pressure value difference (y ₃ −) obtained when the subject is in a resting / resting state
While only y ₂ ) is to be evaluated, the blood pressure value difference (y ₃ −y ₂₎ obtained when the body is moving on the strength corresponding to the threshold value or in a state such as tension or stress. ) Will be excluded from the evaluation. The blood pressure value difference (y ₃ −y ₂ ) and the current time output by the evaluation permitting section 70 are sequentially stored in the data storage section 71 in chronological order. The blood pressure value difference (y ₃ −y ₂ ) and the time stored here are read out in the next measurement and used as the basis for calculating the rate of change in the amplitude of the recurrent wave.

<1-3-1-1: Operation of Peak Point Extraction / Waveform Analysis Unit> The operation of the peak point extraction / waveform analysis unit 40 shown in FIG. 2 will now be described. Peak point extraction and waveform analysis section 40, after acquiring the pulse wave waveform, determined waveform parameters, further blood pressure difference to determine the (y ₃ -y ₂₎ and period (t ₆ -t _4), Perform in several stages. Therefore, regarding the operation of the peak point extraction / waveform analysis unit 40,
The description will be made in each stage.

<1-3-1-1-1: Accumulation of Pulse Waveform and Collection of Peak Information> First, in the peak point extracting / waveform analyzing section 40, the signal MH 'is stored in the waveform memory 402 in FIG. While being accumulated, the peak information of the pulse wave waveform indicated by the signal MH ′ is collected. This operation is executed in the following manner. First, when the microcomputer 401 outputs a signal START for instructing the start of pulse wave waveform collection, the waveform value address counter 405 and the peak address counter 41
3 is released. As a result, the count of the sampling clock φ is started by the waveform value address counter 405, and the count value of the waveform value address A
DR1 is supplied to the waveform memory 402 via the selector 406 as a write address. Then, the signal MH ′ indicating the pulse wave component output from the body motion signal removing unit 30 is A /
The signal is input to the D converter 403, is sequentially converted into a digital signal according to the sampling clock φ, and is sequentially output as the waveform value W via the low-pass filter 404. The waveform value W thus output is stored in the waveform memory 402
, And at that time the waveform value address AD
The data is written to the storage area specified by R1. By the above operation, for example, a series of waveform values W in the pulse waveform illustrated in FIG.

On the other hand, in parallel with this accumulation operation, the collection of the peak information and the writing to the peak information memory 205 are executed as follows. First, the waveform value W of the signal MH 'indicating the pulse wave component is time-differentiated by the differentiating circuit 411, and the result is supplied to the zero-cross detection circuit 412 and the moving average calculation circuit 414, respectively. Each time the time differential value of the waveform value W is supplied in this way, the moving average calculation circuit 414 calculates the average value (ie, moving average value) of a predetermined number of time differential values in the past, and slopes the calculation result. Output as information SLP. Here, a positive value is output as the slope information SLP when the waveform value W is rising or has finished rising and has reached the maximum state, and when the waveform value W has fallen or has finished falling and has reached the minimum state, the slope information SLP has changed. SLP
Is output as a negative value.

For example, when the pulse wave waveform shown in FIG. 4 is output from the low-pass filter 404, the peak point P′1 is the maximum point, and therefore, zero is output from the differentiating circuit 411 as a time derivative. Therefore, the zero cross detection pulse Z is output by the zero cross detection circuit 412. As a result,
The microcomputer 401 calculates the waveform value address ADR1, the waveform value W, the count value of the waveform value address counter 405, the peak address ADR2 (in this case, ADR2 = 0) which is the count value of the peak address counter, and the slope information SLP by the microcomputer 401 at that time. It is captured. Further, the peak address ADR2, which is the count value of the peak address counter 203, becomes "1" by outputting the zero cross detection pulse Z.

On the other hand, the microcomputer 401 determines the peak type B based on the sign of the acquired inclination information SLP.
/ T is created. Thus, the waveform value W of the peak point P'1
Is output, the inclination information SL at that time is output.
Since P becomes a positive value, the microcomputer 401
Is the value of the peak information B / T as "T" corresponding to the maximum point. Then, the microcomputer 401 designates the peak address ADR2 (ADR2 = 0 in this case) fetched from the peak address counter 413 as the write address ADR3 as it is, and the waveform value W, the waveform value W
Value address ADR1, peak type B /
T, the slope information SLP is written to the peak information memory 415 as the first peak information. When the peak information is written for the first time, the stroke information STRK is not created or written because there is no previous peak information.

Thereafter, in the pulse waveform shown in FIG. 4, the waveform value W corresponding to the peak point P'2 is
04, the zero-cross detection pulse Z is output in the same manner as described above, and the waveform value address ADR1, the waveform value W,
Peak address ADR2 (= 1), slope information SLP (<
0) is captured by the microcomputer 401. Then, similarly to the above, the microcomputer 401
Thus, the peak type B / T is determined based on the inclination information SLP. Here, since the peak point P'2 is a minimum point, the slope information SLP at that time becomes a negative value,
The value of the peak information B / T is “B” corresponding to the minimum point. The microcomputer 401 supplies an address smaller than the peak address ADR2 by “1” to the peak information memory 415 as a read address ADR3. As a result, the first written waveform value W is read. And the microcomputer 4
In step S01, the difference between the waveform value W fetched this time from the low-pass filter 404 and the first waveform value W read from the peak information memory 415 is calculated, and the stroke information STRK is obtained. The peak type B / T and the stroke information STRK obtained in this manner are used together with the waveform value address ADR1, the waveform value W, and the inclination information SLP as the peak information memory 41 as the second peak information.
5 is written to the storage area corresponding to the peak address ADR3 = 1. Thereafter, the same operation is performed when the peak points P′3, P′4,... Are detected. Then, at a predetermined timing, the microcomputer 401 stops outputting the waveform collection instruction START, and the collection of the waveform value W and the peak information ends.

<1-3-1-1-2: Identify Pulse Waveform for One Beat> In this manner, the peak information of the peak points P′1 to P′1 of the pulse wave waveform illustrated in FIG. However, this alone does not mean that the waveform parameters defined in FIG. 16 have been obtained. In other words, the waveform parameters correspond to the waveform parameters determined in FIG. 16 only after specifying one pulse waveform shown in FIG. Therefore, it is necessary to specify a pulse waveform for one beat from the collected peak information of the peak points P′1. This specific processing is executed as follows.

First, in this specification, the characteristic of the pulse wave waveform, that is, the blood pressure value of the pulse wave waveform becomes the lowest at the peak point P0 corresponding to the start point of the ventricular systole, and corresponds to the ejection wave immediately thereafter. The characteristic that the peak value is highest at the peak point P1 is used. Therefore, the microcomputer 401 sequentially reads the inclination information SLP and the stroke information STRK corresponding to each peak point P′1, P′2,... From the peak information memory 415. Next, the microcomputer 401 sets each stroke information STR
The stroke information corresponding to the positive slope is selected from K (that is, the corresponding slope information SLP has a positive value). Just extract. That is,
First, the microcomputer 401 first selects a peak point which is a local maximum point, and secondly, extracts a peak point having a large change from the immediately preceding peak point from the peak point. Here, a predetermined number of peak points is extracted, which is intended to examine a plurality of periods.

Next, the microcomputer 401 specifies the stroke information STRK corresponding to the extracted peak point, which corresponds to the median value. This gives 1
Stroke information corresponding to the rising part of the pulse wave waveform of the beat (for example, the part indicated by reference numeral STRKM in FIG. 4) is specified. Note that this specification is based on the premise that peak information has been collected for pulse wave waveforms for a plurality of cycles, and is intended to exclude those considered to be measurement abnormalities. Then, the microcomputer 401
The peak point corresponding to the peak address "1" before the peak address of the stroke information is defined as the peak point P0 of the waveform parameter, and the peak points corresponding to the following peak addresses are sequentially determined as P1 to P6 of the waveform parameter. And specify. For example, referring to FIG.
Is specified as the peak point P0 serving as a waveform parameter calculation reference, and the following peak points P'7 to P'12 are sequentially specified as waveform parameter peak points P1 to P6. Is done. That is, the peak points P1 to P6 are specified in chronological order based on the peak point P0.
Thus, each of the peak points P1 to P6 is specified in time series with reference to the peak point P0 that is the minimum minimum point. For example, a peak point P4 that determines ventricular systole and ventricular diastole
Is specified as the second minimum point that appears second in time series from the peak point P0. In addition, each peak point P1-P6
May be specified based on the magnitude relationship of the values with reference to the peak point P0 that is the minimum minimum point. For example, the peak point P4
May be specified as the second minimum point from the bottom of the value, that is, the minimum point next to the peak point P0.

<1-3-1-1-3: Calculation of Waveform Parameters> The microcomputer 401 calculates each waveform parameter by referring to each piece of peak information corresponding to the pulse waveform for one beat. For example, the peak points P′6 to P′12
Is determined as the peak points P0 to P6 serving as the reference of the waveform parameter, it is obtained as follows. Waveform value W of the peak point P'6~P'11 of blood pressure values y ₁ ~y ₅ Peak Information
It is multiplied by coefficients, respectively, and y ₁ ~y _5. The coefficient is determined by the sensitivity of the pulse wave detector 10, the characteristics of the A / D converter 403, the circuit configuration of the low-pass filter 404, and the like. Subtracting the waveform address corresponding to peak point P'6 from the waveform address corresponding to the time t ₁ peak point P'7, it calculates the t ₁ multiplied by the cycle of the sampling clock φ with respect to the results. Similar to the time t ₂ ~t ₆ above t _1, respectively calculated on the basis of the waveform address difference between each corresponding peak point. The microcomputer 401 stores each waveform parameter obtained as described above in an internal register.

<1-3-1-1-4: blood pressure difference (y ₃ -y
₂ ) and Calculation of Period (t ₆ -t ₄ )> The microcomputer 401 first reads out blood pressure value differences y ₂ , y ₃ , t ₄ and t ₆ of each waveform parameter from an internal register, blood pressure value difference based on the second, read y ₂ and y ₃ (y ₃ -y ₂₎ is calculated and a third, read t ₄ and time based on t ₆ (t ₆ -t ₄₎ Is calculated, and each is output. In this way, the blood pressure value difference (y ₃ -y ₂₎
The period (t ₆ -t ₄ ) is calculated, and is used as a basis for evaluation in the evaluation permission unit 70 and the evaluation unit 72.

As described above, in the first measurement operation, if the subject is in a resting / quiet state, the evaluation permitting unit 7
The blood pressure value difference (y ₃ −y ₂ ) output at 0 and its time are sequentially stored in the data storage unit 71 in chronological order. The blood pressure value difference (y ₃ −y ₂ ) is not stored in the data storage unit 71 by the evaluation permitting unit 70 unless the subject is in a resting / resting state. Therefore, in the subsequent and subsequent measurements, the time when the calculated blood pressure value difference (y ₃ −y ₂ ) is stored in the data storage unit 71 is a substantial first measurement operation. The blood pressure value difference (y ₃ −y ₂ ) and the time stored here are read out in the next measurement and used as a basis for calculating the rate of change of the rising time of the ejection wave. .

<1-3-2: Second and subsequent measurement operations> The first measurement operation is completed as described above, and after a lapse of a predetermined time from the previous measurement, the same measurement is performed again, and the subject rests. In the calm state, the blood pressure value difference (y ₃ −y ₂ ) corresponding to the rising of the ejection wave and the time at that time are output by the evaluation permitting unit 70, respectively. Here, the evaluation unit 72 first reads out the blood pressure value difference (y ₃ −y ₂ ) and the time thereof that have been recently stored from the data storage unit 71, and secondly, calculates the blood pressure value difference at the present time. blood pressure difference pressure value difference read from the _{(y 3 -y 2) (y} 3 -
By subtracting y ₂ ), a change in the measurement period is obtained. Third, the read time is subtracted from the current time to obtain the elapsed time from the previous measurement to the current measurement, and fourth, the quotient obtained by dividing the change by the elapsed time is obtained. As a result, the rate of change of the amplitude in the tide wave is calculated.

When the rate of change of the amplitude in the tide wave is calculated, the contents of diagnosis corresponding to the rate of change are read out from the evaluation content storage unit 73, and the contents are notified to the subject or doctor by the notification unit 74. You. Thereafter, the same measurement operation is repeatedly performed, and each time the rate of change is calculated, the corresponding diagnosis is notified.

<1-4: Notification Mode> Here, various examples of the notification of the notification unit 74 in the present embodiment will be described. First, as shown in FIG. 5, for example, the rate of change is ranked in six stages, and diagnostic messages corresponding to those rankings are stored as evaluation contents, and the blood pressure value calculated by the evaluation unit 72 is stored. Difference (y ₃ -y
It is conceivable to adopt a configuration in which a diagnostic message corresponding to the change rate in ₂ ) is read and notified. Further, instead of the diagnostic message, a face chart as shown in FIG. 6 may be displayed corresponding to the change rate of the calculated blood pressure value difference (y ₃ −y ₂ ). Further, as described above, the amplitude of the retreat wave is considered to be formed under the influence of both the pressure characteristics of the blood to be pumped and the blood vessel characteristics of the side from which the blood is pumped, so that the blood pressure value the difference (y ₃ -y ₂₎ itself may be configured to announce.

The temporal transition by the temporal transition creating section 75 is created, for example, as follows. Specifically, since the storage content of the data storage unit 71 is a set of a time and a blood pressure value difference (y ₃ −y ₂ ) measured at the time, the time of the read data is expressed on the x-axis. by taking each blood pressure difference (y ₃ -y ₂₎ on the y-axis, the time course of the blood pressure value difference (y ₃ -y ₂₎ it is created. in this case,
As shown in FIG. 7, the x-axis is an elapsed time based on the oldest read time, and the y-axis is a blood pressure value difference (y ₃ −y) with respect to the oldest read time.
The size of ₂ ) may be set to “1.0”, and other times may be indicated by the ratio. In the illustrated example, the measurement is 2
Shows the case where it is performed at minute intervals.

In the heart function diagnosis apparatus according to the present embodiment, the body movement detecting unit 20 detects the body movement component of the subject. However, the diagnosis is performed on the assumption that the subject does not move. If this is the case, the signal MH is directly converted into a signal MH ′ indicating only the pulse wave component by the pulse wave detecting unit 10.
Therefore, the body motion detecting section 20 and the waveform processing section 21 are unnecessary. In addition, in the present apparatus, the number of beats is calculated from the period (t ₆ -t ₄ ) corresponding to the ventricular diastole. However, it is needless to say that the number of beats may be calculated from the time t _{6 of the} waveform parameter. In addition, if the diagnosis is performed on the assumption that the subject's pulse rate is sufficiently low, the configuration itself for calculating the pulse rate becomes unnecessary. For this reason, the beat count conversion table 60 for detecting the beat count and the evaluation permitting unit 70 taking into account the beat count are optional requirements. Further, in the above-described embodiment, the rate of change of the amplitude in the tidal wave was obtained from the current value and the latest value stored in the data storage unit 71. However, the present invention is not limited to this. Absent. For example, it may be obtained from the current value and the value of a predetermined number in the past, or may be obtained from the average value from the current time to the predetermined number in the past and the average value in the past. Further, in the above embodiment, using the amplitude as an index that defines the Taicho wave has been evaluated the amplitude in blood pressure difference (y ₃ -y _2), evaluated by the blood pressure value difference (y ₃ -y ₄₎ Is possible,
Further, as described in the next application example, it is considered that a value obtained by normalizing the amplitude of the tide wave with the difference between the maximum blood pressure value and the minimum blood pressure value is an effective evaluation index. Further, as an index that defines the Taicho wave, the other, or the period t ₃ when corresponding to the time the peak point of Taicho wave appear by a period corresponding to the width of Taicho wave (t ₄ -t
_2), further, these times, considered to be in effect evaluation index normalized with the time t ₄ when corresponding to ventricular systole.

As described above, according to the cardiac function diagnostic apparatus according to the embodiment, the peak point of the pulse wave waveform detected from the subject is extracted, and the blood pressure value difference (y ₃ -y) corresponding to the amplitude of the tide wave is extracted.
₂ ) and, if necessary, the rate of change.
The subject's cardiac function status can be evaluated and diagnosed to some extent. Therefore, it is not necessary to perform the frequency analysis processing on the pulse wave waveform, so that the processing load can be reduced, which can greatly contribute to downsizing and simplification of the apparatus.

<1-5: Application Example> Next, an application example of the above-described cardiac function diagnostic apparatus according to the first embodiment will be described.

<1-5-1: (y ₃ -y ₂ ) /
y ₁ > In the above embodiment, the blood pressure value difference (y ₃ −y ₂ ) corresponding to the amplitude of the ejection wave was used as an evaluation index. here,
When reconsidering the significance of the blood pressure value difference (y ₃ -y ₂ ), as described above, the blood pressure value difference (y ₃ -y ₂ ) depends on the pressure characteristics of the blood pumped by the contraction of the ventricle and the blood pressure. Is considered to be determined by the characteristics of the blood vessel on the side from which blood is ejected. However, pressure characteristics and blood vessel characteristics generally differ from person to person. For this reason, the blood pressure difference (y ₃ −
Regardless of the evaluation of y ₂ ), it is considered that mutual evaluation across a plurality of subjects is not appropriate, regardless of the evaluation of the same subject. Therefore, a value obtained by normalizing the blood pressure value difference (y ₃ −y ₂ ) by the blood pressure value difference y ₁ which is a difference between the maximum blood pressure value and the minimum blood pressure value in the pulse wave waveform, that is, (y ₃ −y ₂ ) / y ₁
Instead of the (y ₃ -y ₂₎ (or (y ₃ -y ₂₎ with)
It is appropriate to use it as an evaluation index.

The configuration for this is as follows. The microcomputer 401 in FIG. 2 calculates and outputs the blood pressure value difference y ₁ and the blood pressure value difference (y ₃ −y ₂ ) stored in its internal register. Peak point extraction / waveform analysis unit 40 shown in FIG.
In the subsequent stage, instead of (y ₃ -y ₂ ) (or (y
₃ -y _{2) together) (y 3 -y 2) /} y 1 is possible using as an index, and _{(y 3 -y 2) / y} 1 itself,
The cardiac function status is evaluated based on the rate of change. The same is true in that a time transition of (y ₃ −y ₂ ) / y ₁ may be created and notified. After all, the configuration of such an application is
The configuration including FIGS. 1 and 2 is substantially the same as the configuration including the example described above as an index for defining the tidal wave.

<1-5-2: Data transfer to external device>
When the heart function diagnostic device is required to be reduced in size and weight, a configuration in which the configurations shown in FIGS. 1 and 2 are integrated as one device has no room for evaluation and diagnosis by a doctor or the like. Becomes Therefore, after detecting the pulse waveform of the subject, the data transfer blood pressure difference to be supplied to the evaluation authorization unit 70 in FIG. 1 (y ₃ -y ₂₎ or _{(y 3 -y 2) / y} 1 to the external device Then, a configuration is possible in which a third party such as a doctor can perform detailed diagnosis and analysis.

A communication I / F (interface) 76 shown by a broken line in FIG. 1 is a configuration for this purpose. Communication I
/ F76 has a data buffer inside, and (y ₃ −
After accumulating (y ₂ ) or (y ₃ -y ₂ ) / y ₁ , time and number of beats for a predetermined measurement period, the data is transferred to the communication I / F 76 for transmission to an external device for diagnosis and analysis. It has a configuration. Here, the communication I / F 76 has an LED and a phototransistor for transferring data by optical communication with an external device.

FIG. 8 is a block diagram showing the configuration of such an external device. As shown in this figure, the external device includes a device main body 600, a display 601, a keyboard 602, a printer 603, and the like, and is the same as a normal personal computer except for the following points. That is, the device main body 600 constructs the configuration after the evaluation permitting unit 70 in FIG. 1 and has an LED 604 for converting transmission data into light and transmitting it, while a phototransistor for converting received light into data. 605. The LED 604 and the phototransistor 605 have a communication I / F 7 of the cardiac function diagnostic device.
LEDs having the same or similar characteristics as those of the LED and the phototransistor provided in 6 are used. Here, a near infrared type (for example, a center wavelength of 94
0 nm) is desirable. When a near-infrared light type is used, a visible light cutoff filter for blocking visible light is provided on the front surface of the device main body 600, and serves as a communication window 606 for optical communication.

The cardiac function diagnosing device having such a configuration can be used alone (y ₃ -y) when data transfer is not performed.
₂ ) While the evaluation and diagnosis of the above-mentioned subject's cardiac function state are performed based on the change rate of (y ₃ −y ₂ ) / y ₁ , while the data transfer is performed, the peak point extraction / waveform analysis unit 40 is used.
(Y ₃ -y ₂ ) or (y ₃ -y ₂ ) / y calculated by
_{A set of 1} and the number of beats converted by the beat count conversion table 60 is stored in the data buffer of the communication I / F 76 for a predetermined measurement period. Here, when a third party such as a doctor operates the keyboard 601 to instruct a data request, the external device transmits a data request signal via the LED 604 and then enters a standby state for receiving data. On the other hand, when the phototransistor of the communication I / F 76 on the side of the cardiac function diagnostic apparatus receives the data request signal, the set data stored in the data buffer of the communication I / F 76 is transmitted by the LED of the communication I / F 76. By receiving the set data phototransistor 605, the external device, the blood pressure value difference corresponding to the amplitude of Taicho wave in a subject (y ₃ -y ₂₎ or it was normalized (y ₃ -y ₂₎ / The data of y ₁ and the measurement time will be obtained. Thereafter, in the external device, by constructing the configuration after the evaluation permitting unit 70 in FIG. 1, the subject's mind is determined based on the rate of change of (y ₃ -y ₂ ) or (y ₃ -y ₂ ) / y _1. The function status can be evaluated and diagnosed, and a diagnosis of a doctor or the like can be made based on the accumulated data.

In the data transfer, in addition to this, the body movement state of the subject is also transmitted to the external device, and conversely, the ranking and the diagnostic message corresponding to the change rate are transmitted to the external device. It is conceivable that the content is set and transmitted to the cardiac function device.

<2: Second Embodiment> Next, a second embodiment of the present invention will be described.
A cardiac function diagnostic device according to an embodiment will be described.

<2-1: Theoretical Basis of the Second Embodiment> As described above, the tidal wave is affected by both the pressure characteristic of the pumped blood and the blood vessel characteristic of the pumped side. It is thought that it is formed in response to this. On the other hand, it has been conventionally known that a frequency component obtained by frequency analysis of a pulse waveform can be information representing a biological characteristic of the subject (for example, see PCT / JP96 / 01254). For this reason, it is considered that analyzing the frequency component of the tide wave in the pulse wave waveform has a certain significance.

On the other hand, the inventor of the present application detects pulse waves from 74 healthy adults, obtains these pulse wave waveform parameters, and performs FFT processing similarly to PCT / JP96 / 01254 described above. Using the above equation (1), the distortion rate d of the pulse waveform was determined. As a result of individually examining the correlation between the obtained distortion rate d and each waveform parameter alone or the difference between them, the distortion rate d indicates the blood pressure value difference (corresponding to the amplitude of the notch wave). (y ₅ -y ₄ ) was found to have a high correlation with a correlation coefficient (R ² ) of 0.77.
This correlation is shown in FIG. This means that the high-order harmonic components are concentrated in the vicinity of the switching mark wave defining blood pressure values difference (y ₅ -y ₄₎ in the pulse waveform. That is, in a configuration in which the pulse wave waveform is simply subjected to frequency analysis, the frequency components near the retreating wave are almost completely buried in the components near the notch wave. Therefore, in order to analyze the component of the tidal wave in the pulse wave waveform, it is considered necessary to perform a process of extracting a component near the tidal wave from the pulse wave waveform. Therefore, in the second embodiment, first,
In the pulse wave waveform, the portion near the regression wave to be processed is specified. Thirdly, what is most similar to this analysis result is specified from the analysis results obtained in advance for typical symptoms, and fourthly, the contents of diagnosis corresponding to the specified symptom are announced. Configuration.

<2-2: Functional Configuration of Second Embodiment> Next, a cardiac function diagnostic apparatus according to a second embodiment configured based on such a premise will be described. FIG. 9 is a block diagram illustrating a functional configuration of the cardiac function diagnostic device according to the present embodiment. In this figure, the parts different from the cardiac function diagnostic apparatus shown in FIG. Part 40
And the like. Hereinafter, these differences will be mainly described.

The peak point extraction / waveform analysis unit 40 extracts each peak point of the pulse wave waveform from the signal MH 'indicating the pulse wave component, calculates the waveform parameters, and determines the period (t ₆ -t ₄ ). Is the same as that of the first embodiment, but in this embodiment, the pulse wave waveforms from the peak points P1 to P4 corresponding to the vicinity of the tide wave among the pulse wave waveforms stored in the internal waveform memory 402 The MD is read and supplied to the wavelet transform unit 200.

The wavelet transform unit 200 performs a wavelet transform on the pulse wave waveform MD read from the peak point extracting / waveform analyzing unit 40 and converts the pulse wave analysis data MKD by a configuration described later. To generate. Generally, in time-frequency analysis in which a signal is simultaneously captured from both the time and frequency sides, a wavelet is a unit for cutting out a signal portion. The wavelet transform indicates the size of each part of the signal extracted in this unit. Here, as a basis function for defining the wavelet transform, a function ψ localized in time and frequency
When (x) is introduced as a mother wavelet, the wavelet transform of the function f (x) by the mother wavelet ψ (x) is defined as follows.

[0070]

(Equation 2)

In this equation (2), b is a parameter used when translating (translating) the mother wavelet ψ (x), while a is a parameter when scaling (expanding or contracting). . Therefore, in equation (2), the wavelet ψ ((x−b) / a)
Is a translation of the mother wavelet ψ (x) by b and expansion and contraction by a. In this case, the mother wavelet ψ (x) corresponding to the scale parameter a
Are expanded, so that 1 / a corresponds to the frequency. The detailed configuration of the wavelet transform unit 200 will be described later.

Next, the frequency correction section 210 corrects the pulse wave analysis data MKD by the wavelet transform section 200 to generate correction analysis data MKD '. Specifically, the above equation (2) has a term of “1 / √a” corresponding to the frequency, but when comparing data between different frequency regions, it is necessary to correct the effect of this term. is there. Therefore, the frequency correction unit 210 is provided, and the wavelet data is multiplied by the coefficient √a to generate the analysis correction data MKD ′. As a result, the pulse wave analysis data MKD is corrected based on each corresponding frequency so that the power density per frequency becomes constant.

On the other hand, the sample storage section 220 stores an analysis result corresponding to a typical pulse waveform shape. In the present embodiment, for example, "slip vein"
Pulse wave waveforms corresponding to the shapes of "Heart vein" and "String vein"
Wavelet transform is performed in a period corresponding to the vicinity of the regression wave in the ventricular systole, and further, the frequency is corrected, and the analysis result corresponding to these is used as a sample, for example, as shown in FIG.
As shown in (b), a time component and a frequency component are stored in a data format divided into eight.

Next, the evaluation unit 80 stores the sample storage unit 22
0 of the samples stored in the frequency correction unit 21.
The data closest to the corrected analysis data MKD ′ based on 0 is determined from the position where the high component exists, the distribution of each component, and the like, and the biological state of the subject is specified. However, if the number of beats at the time of diagnosis deviates from the value obtained when the sample was obtained, there is a possibility that an erroneous determination is made.
0 is a supplementary input of the number of beats in the distortion rate conversion table 60,
If the difference from the number of beats when the sample is obtained is equal to or more than a certain value, the diagnosis is not performed.

<2-2-1: Configuration of Wavelet Transformer> Here, the detailed configuration of the wavelet transformer 200 will be described. Such a wavelet conversion unit 200
Performs the arithmetic processing of the above equation (2), and its configuration is made up of the following elements as shown in FIG. That is,
The wavelet conversion unit 200 includes a basis function storage unit W1 for storing a mother wavelet ψ (x), a scale conversion unit W2 for converting a scale parameter a, a buffer memory W3, a translation unit W4 for performing translation, and It comprises a multiplication unit W5. The mother wavelet ψ (x) stored in the basis function storage unit W1 is a Gabor wavelet, a Mexican hat,
Haar wavelet, Meyer wavelet,
Shannon wavelet or the like can be applied. Also,
The wavelet transform unit 200 receives a signal indicating a period T from the peak point P1 to the peak point P4 corresponding to the vicinity of the tidal wave, and outputs pulse wave analysis data at time intervals obtained by dividing the period T into eight. Has become.

<2-3: Operation of Second Embodiment> Next, the operation of the second embodiment shown in FIG. 9 will be described. Although the body movement component accompanying the body movement of the subject is superimposed on the signal MH output by the pulse wave detection unit 10, the body movement component removal unit 30
As a result, the body motion component is removed, and a signal MH ′ indicating only the pulse wave component is supplied to the peak point extraction / waveform analysis unit 40. As in the first embodiment, the peak point extraction / waveform analysis unit 40 accumulates and analyzes data of the signal MH ′, calculates waveform parameters of the pulse waveform, and calculates a period in the pulse waveform from these waveform parameters. After obtaining (t ₆ -t ₄ ), the following operation is further performed. That is, in FIG. 2, after calculating each waveform parameter, the microcomputer 401 of the peak point extraction / waveform analysis unit 40 first calculates the waveform values of the peak points specified as the peak points P1 and P4 from the peak information memory 415. Third, a select signal S1 is output, and thirdly, the waveform value address of the peak point corresponding to the read peak point P1 is
The waveform is advanced by the sampling clock φ to the waveform value address of the peak point corresponding to the peak point P4, and is output as the read address ADR4 of the waveform memory. As a result, the pulse waveform MD from the peak point P1 to the peak point P4, that is, the pulse waveform MD corresponding to the vicinity of the regression wave in the ventricular systole is read from the waveform memory 402.

The pulse wave waveform MD corresponding to the vicinity of the tide wave is subjected to wavelet transform by the wavelet transform unit 200 as described later, and as a result, the pulse wave analysis data MKD divided into eight in the time domain and the frequency domain.
Is generated. The pulse wave analysis data MKD further includes:
The frequency is corrected by the frequency correcting unit 210 to become corrected analysis data MKD ′. On the other hand, the beat count conversion table 60
In, the period (t ₆ -t ₄ ) calculated by the peak point extraction / waveform analysis unit 40 is converted into the number of beats. Next, in the evaluation unit 80, first, the difference between the number of beats based on the distortion rate conversion table 60 and the number of beats when the sample stored in the sample storage unit 220 is determined is determined. It is determined whether or not the difference is equal to or greater than a threshold value. If the difference is equal to or greater than the threshold value, a signal indicating that diagnosis is not performed is output. The sample stored in the sample storage unit 220 is compared with each other, the sample closest to the analysis correction data MKD ′ is determined, the biological state of the subject is specified, and a signal indicating the state is output. Then, the content of the diagnosis corresponding to the specified biological condition (or the content not performing the diagnosis)
Is read from the evaluation content storage unit 73, and the notification unit 74 notifies the subject of the read content by displaying or notifying by voice or the like, as in the first embodiment.

<2-3-1: Operation of Wavelet Transformer> Here, the operation of the wavelet transform unit 200 will be described. First, when the mother wavelet ψ (x) is read from the basis function storage unit W1, the scale conversion unit W2 converts the scale parameter a. Here, since the scale parameter a corresponds to the period, when a becomes large, the mother wavelet ψ
(X) is extended on the time axis. In this case, the mother wavelet ψ (x) stored in the basis function storage unit W1
Is constant, the data amount per unit time decreases as a increases. The scale conversion unit W2 performs an interpolation process to compensate for this, and a
Becomes smaller, a thinning process is performed, and the function ψ (x / a)
Generate This data is temporarily stored in the buffer memory W3. Next, the parallel moving unit W4 is connected to the buffer memory W3.
By reading the function ψ (x / a) at a timing corresponding to the translation parameter b, the function ψ (x / a
The function） (x−b / a) is generated by performing the parallel movement of a).

Then, the multiplication unit W5 multiplies the variable 1 / 変 数 a, the function ψ (x−b / a) and the pulse wave data MD to perform wavelet transform, and generates pulse wave analysis data MKD. FIG. 11B shows the pulse wave waveform shown in FIG.
This shows pulse wave analysis data MKD obtained by performing a wavelet transform in a period near the tidal wave. It should be noted that the waveform memory 402 in FIG.
It should be noted that the pulse wave waveform MD corresponding to the vicinity of the tidal wave up to is read out. The pulse wave analysis data MKD is 0 Hz to 0.5 Hz, 0.5 Hz as shown in FIG.
Hz-1.0Hz, 1.0Hz-1.5Hz, 1.5H
z ~ 2.0Hz, 2.0Hz ~ 2.5Hz, 2.5Hz
~ 3.0Hz, 3.0Hz ~ 3.5Hz, 3.5Hz ~
It is divided into eight frequency regions such as 4.0 Hz, and is obtained at a time interval obtained by dividing a period T from a peak point P1 as a starting point near the regression wave in the ventricular systole to a peak point P4 as an ending point into eight. After all, pulse wave analysis data MK
D is composed of 64 data from M11 to M88. The generated pulse wave analysis data MKD is subjected to frequency correction by the frequency correction unit 210, output as corrected analysis data MKD ', and used as a basis for evaluation by the evaluation unit 80.

In the wavelet transform, since the frequency resolution and the time resolution are in a trade-off relationship with each other, pulse wave analysis data can be obtained at shorter time intervals if the frequency resolution is sacrificed. Further, in the second embodiment, the diagnosis is performed by performing the wavelet transform on the pulse wave waveform corresponding to the vicinity of the ventricular systole, but the present invention may be further limited to the case where the peak points P2 to P4. In addition, in the second embodiment, the number of beats is obtained from the period (t ₆ -t ₄ ) corresponding to the ventricular diastole. However, the number of beats may be obtained from the time t _{6 of the} waveform parameter. In addition, if the diagnosis is performed on the assumption that the subject's pulse rate is sufficiently low, the configuration itself for obtaining the pulse rate is unnecessary. For this reason, the beat count conversion table 60 for detecting the beat count and the evaluation unit 80 taking into account the beat count are optional requirements.
This is the same as the embodiment.

As described above, according to the cardiac function diagnostic apparatus according to the second embodiment, the peak point of the pulse waveform detected from the subject is extracted, the ventricular systole is specified, and the tidal wave during that period is specified. With a configuration that performs wavelet transform on the pulse wave waveform in the vicinity, the frequency component in the vicinity of the regression wave that is buried in the frequency component in the vicinity of the notch wave can be obtained with a configuration that simply analyzes the frequency of the pulse wave waveform. It becomes possible to evaluate the heart function state of the subject from the frequency components near the tidal wave. Furthermore, about the pulse wave waveform,
Since the frequency analysis processing does not need to be performed for the period or more, the processing load can be reduced, which can greatly contribute to miniaturization and simplification of the apparatus.

<2: Third Embodiment> Next, a third embodiment of the present invention will be described.
A cardiac function diagnostic device according to an embodiment will be described.

<3-1: Rationale of Third Embodiment> The heart function diagnostic apparatus according to the second embodiment described above uses the wavelet transform in analyzing a pulse wave waveform corresponding to the vicinity of a retidal wave. The cardiac function diagnostic apparatus according to the third embodiment uses FFT as the frequency analysis processing. However, unlike the wavelet transform, in the configuration in which the FFT processing is performed only in the vicinity of the regression wave, harmonic components accompanying the processing appear in the analysis result. And multiplying by a window function corresponding to the vicinity of the retreating wave to extract a pulse wave waveform corresponding to the period by smoothing the waveform.
T processing was performed.

<3-2: Functional Configuration of Third Embodiment> FIG. 12 is a block diagram showing a functional configuration of a cardiac function diagnostic apparatus according to the present embodiment. In this figure, the difference from the cardiac function diagnostic apparatus shown in FIG.
0, a window function reading unit 240, a multiplication unit 250, an FFT processing unit 260, a sample storage unit 270, and a function of the peak point extraction and waveform analysis unit 40 in addition to the provision of the evaluation unit 90. Therefore, the following description will focus on these differences.

The peak point extraction / waveform analysis section 40 extracts each peak point of the pulse wave waveform from the signal MH 'indicating the pulse wave component, calculates the waveform parameters, and determines the period (t ₆ -t ₄ ). Is the same as that of the first embodiment, but in this embodiment, the pulse wave waveforms from the peak points P1 to P4 corresponding to the vicinity of the tide wave among the pulse wave waveforms stored in the internal waveform memory 402 The MD is read and supplied to the input terminal of the multiplication unit 250. Also, the window function storage unit 230
The function shown in FIG. 13 is stored in the form of a table in advance. In practice, for example, x = −π is changed to “0000”, x
= Π is stored as a continuous address with “FFFF”. The window function reading unit 240 reads the window function stored therein by supplying the generated read address to the window function storage unit 230 in synchronization with the sampling clock φ. More specifically, when the pulse wave waveform MD corresponding to the peak points P1 to P4 is read from the waveform memory 402 (see FIG. 2), the window function reading unit 240 sets the peak points P1 and P4 as the window functions. The read address is supplied so as to match x = -π and + π, respectively.

Multiplying section 250 multiplies the pulse wave waveform corresponding to the vicinity of the retreating wave by a window function to obtain an FFT
This is to smooth the pulse waveform to be processed. F
The FT processing unit 260 performs a known FFT process on the smoothed pulse wave waveform. On the other hand, the sample storage unit 270 stores an analysis result corresponding to a typical pulse waveform shape. In the present embodiment, similarly to the second embodiment, the window function stored in the window function storage unit 230 for the pulse wave waveforms corresponding to “smooth pulse”, “flat pulse” and “chord pulse” in advance. Is stored as a sample.

Next, the evaluation unit 90 stores the sample storage unit 27
0 of the samples stored in the FFT processing unit 21
The shape closest to the analysis result based on 0 is determined from the position where a strong component exists, the distribution of each component, and the like, and the shape of the pulse wave waveform is specified. However, similarly to the second embodiment, if the number of beats at the time of diagnosis deviates from the number of beats at the time of obtaining a sample, there is a possibility that an erroneous determination is made. The number of beats of 60 is input as an auxiliary, and if the difference from the number of beats at the time of obtaining the sample is equal to or more than a certain value, diagnosis is not performed.

<3-3: Operation of Third Embodiment> Next, the operation of the third embodiment will be described. The body movement component accompanying the body movement of the subject is superimposed on the signal MH output by the pulse wave detection unit 10, but the body movement component is removed by the body movement component removal unit 30, and only the pulse wave component is removed. The signal MH ′ is supplied to the peak point extraction / waveform analysis unit 40.
As in the first embodiment, the peak point extraction / waveform analysis unit 40 accumulates and analyzes data of the signal MH ′ to calculate waveform parameters of the pulse waveform, and calculates a period (in the pulse waveform) from these waveform parameters. t ₆ -t ₄ ), and
The following operation is performed. That is, in FIG. 2, the microcomputer 401 of the peak point extraction / waveform analysis unit 40
After calculating each waveform parameter, firstly, the waveform value addresses corresponding to the peak points P1 and P4 are respectively read from the peak information memory 415, and secondly, these are supplied to the window function reading unit 240, and thirdly. , And outputs a select signal S1,
Fourth, the read waveform value address of the peak point corresponding to the read peak point P1 is advanced by the sampling clock φ to the waveform value address of the peak point corresponding to the peak point P4, and this is read out from the read address ADR4 of the waveform memory. Output as As a result, from the waveform memory 402, the pulse wave waveform MD from the peak point P1 corresponding to the starting point of the waveform extraction to the peak point P4 corresponding to the end of the extraction, that is, the pulse wave corresponding to the vicinity of the regression wave in the ventricular systole. The waveform MD is read.

Next, the window function reading unit 240 determines that the peak point P
The waveform value address corresponding from 1 to the peak point P4 is
The window function addresses "0000" to "F" shown in FIG.
The read address of the window function is determined so as to correspond to "FFF". For example, if the waveform value address of the peak point corresponding to the peak point P1 is "1000" and the peak point P
The waveform value address of the peak point corresponding to 4 is "1FFF"
, The read address of the window function to the window function storage unit 230 is “0000”, “0010”, “0020”,.
.. Is incremented by the sampling clock φ every "10". As a result, the window function read from the window function storage unit 230 is scaled to coincide with the peak points P1 to P4 corresponding to the period near the regression wave of the pulse waveform. Then, as shown in FIG. 14A, the pulse wave waveform MD from the peak points P1 to P4 read from the waveform memory 402 of the peak point extraction / waveform analysis unit 40 has the waveform shown in FIG. As described above, the window function scaled in accordance with the pulse wave waveform MD is multiplied by the multiplication unit 250, and the multiplication result shown in FIG. 10C is subjected to the FFT processing by the FFT processing unit 260.

Next, the evaluation unit 90 first obtains the difference between the number of beats in the distortion rate conversion table 60 and the number of beats when the sample stored in the sample storage unit 270 is obtained. , Determine whether the difference is greater than or equal to a threshold,
If the value is equal to or more than the threshold value, a signal indicating that diagnosis is not performed is output. A sample that is closest to the analysis result is determined, and a signal that specifies the biological state of the subject is output. Then, the diagnosis content (or the content not performing the diagnosis) corresponding to the specified biological condition is read from the evaluation content storage unit 73, and the read content is displayed by the notification unit 74, or a sound is output. Or the like, and the subject is notified.

In the third embodiment, the window function is a cosine function. However, the present invention is not limited to a trigonometric function such as a cosine function, as long as it can smooth a pulse waveform. Also, in the present embodiment, the pulse wave waveform corresponding to the vicinity of the regression wave in the ventricular systole is multiplied by the window function to obtain the FFT.
The processing is performed and the diagnosis is performed based on the analysis result. However, the diagnosis may be further limited to the peak points P1 to P4, or may be expanded to the peak points P0 to P4. In addition, in the third embodiment, the number of beats is calculated from the period (t ₆ -t ₄ ) corresponding to the ventricular diastole. However, the number of beats may be calculated from the waveform parameter time t _6. In addition, if the diagnosis is performed on the assumption that the subject's pulse rate is sufficiently low, the configuration itself for obtaining the pulse rate is unnecessary. For this reason, the beat count conversion table 60 for detecting the beat count and the evaluation unit 90 taking into account the beat count are optional requirements.
This is the same as in the second embodiment.

As described above, according to the cardiac function diagnosis apparatus of the third embodiment, the peak point of the pulse wave waveform detected from the subject is extracted, and the pulse wave waveform near the regression wave in the ventricular systole is extracted. By multiplying the multiplication result by a window function corresponding to the pulse waveform and performing FFT processing on the multiplication result, the frequency component of the pulse waveform is simply analyzed in the frequency component in the vicinity of the notch wave in the configuration in which the pulse waveform is simply frequency-analyzed. Since the frequency component near the tidal wave that is buried can be obtained, it is possible to evaluate the cardiac function state of the subject from the frequency component near the tidal wave. Further, since it is not necessary to perform the frequency analysis processing for the pulse wave waveform for one cycle or more, the processing load can be reduced, which can greatly contribute to miniaturization and simplification of the apparatus.

<4: Appearance Configuration of Each Embodiment> Next, some examples of the configuration of the cardiac function diagnostic apparatus according to the above-described first to third embodiments will be described.

<4-1: Wristwatch Type A> First, a configuration example in which the heart function diagnostic device 1 according to each embodiment is a wristwatch type will be described with reference to FIG. As shown in FIGS. 1A and 1B, a heart function diagnostic device 1 mainly includes a device main body 100 having a wristwatch structure and a device main body 10 having a wristwatch structure.
0 and the cable 101 connected to the
And a pulse wave detection unit 10 provided on the distal end side. The main body 100 includes a wristband 1
02 is attached. For more information, see Wristband 1
It is wrapped around the subject's left arm from the 12 o'clock direction of 02 and the other end is fixed in the 6 o'clock direction of the apparatus main body 100. In the 6 o'clock direction of the apparatus main body 100, the connector 103
Is provided. A connector piece 104 serving as an end of the cable 101 is detachably attached to the connector section 103. When the connector piece 104 is removed, as shown in FIG.
1, 112, and L for performing the data transfer described above.
An ED 113 and a phototransistor 102 are provided.

On the other hand, the pulse wave detector 10 is attached to the base of the subject's index finger while being shielded from light by the sensor fixing band 11, as shown in FIG. As described above, when the pulse wave detector 10 is attached to the base of the finger, the length of the cable 101 can be shortened.
Also, when the distribution of body temperature from the palm to the fingertip is measured, when the temperature is cold, the temperature at the fingertip drops significantly, whereas the temperature at the root of the finger does not drop relatively. Therefore, if the pulse wave detector 10 is attached to the base of the finger, even when going out on a cold day,
A pulse wave waveform can be accurately detected. In addition, a display unit 110 made of a liquid crystal panel is provided on the front side of the apparatus main body 100. The display unit 110 has a segment display area, a dot display area, and the like, and displays the current time, diagnosis contents, and the like. That is, the display unit 110 corresponds to the notification unit 74 in each embodiment.

On the other hand, an acceleration sensor (not shown) is incorporated inside the apparatus main body 100, and detects a body movement caused by the swing of the arm of the subject or the vertical movement of the body. That is, this acceleration sensor corresponds to the body motion detection unit 20 in each embodiment. A CPU for controlling various calculations and conversions (not shown) is provided inside the apparatus main body 100 (not shown).
01 is also used. Further, a button switch SW1 for performing various operations and instructions is provided on an outer peripheral portion of the apparatus main body 100.
And SW2 are provided.

<4-1-1: Detailed Configuration of Pulse Wave Detector> Next, the configuration of the pulse wave detector 10 will be described with reference to FIG. As shown in this figure, the pulse wave detection unit 10
D12, a phototransistor 13, and the like.
When the switch SW is turned on and a power supply voltage is applied, light is emitted from the LED 12. This irradiation light is received by the phototransistor 13 after being reflected by blood vessels and tissues of the subject. Therefore, a voltage obtained by converting the photocurrent of the phototransistor 12 into a voltage is output as the signal MH of the pulse wave detector 10.

Here, the emission wavelength of the LED 12 is selected near the absorption wavelength peak of hemoglobin in blood. Therefore, the light receiving level changes according to the blood flow. Accordingly, the pulse wave waveform is detected by detecting the light receiving level. In addition, as the LED 12, In
GaN-based (indium-gallium-nitrogen-based) blue LE
D is preferred. The emission spectrum of the blue LED has an emission peak at, for example, 450 nm, and the emission wavelength range is
It is in the range from 350 nm to 600 nm. In this case, a GaAsP-based (gallium-arsenic-phosphorus-based) may be used as the phototransistor 13 corresponding to an LED having such light emission characteristics. The light-receiving wavelength region of the phototransistor 13 has, for example, a main sensitivity region of 300.
In the range from nm to 600 nm, there is a sensitivity region even below 300 nm. When such a blue LED and a phototransistor are combined, a pulse wave is detected in a wavelength region from 300 nm to 600 nm, which is an overlapping region thereof, resulting in the following advantages.

First, of the light included in the external light, light having a wavelength region of 700 nm or less tends to hardly penetrate the finger tissue. , Does not reach the phototransistor 33 via the finger tissue, and only light in a wavelength region that does not affect detection reaches the phototransistor 33. On the other hand, since light in a wavelength region lower than 300 nm is almost absorbed by the skin surface, even if the light receiving wavelength region is set to 700 nm or less, the substantial light receiving wavelength region is 300 nm to 700 nm.
nm. Therefore, the influence of external light can be suppressed without covering the finger in a large scale. In addition, hemoglobin in blood has a large absorption coefficient for light having a wavelength of 300 nm to 700 nm, and is several times to about 100 times or more larger than the absorption coefficient for light having a wavelength of 880 nm. Therefore, as in this example, in accordance with the absorption characteristics of hemoglobin, the wavelength region where the absorption characteristics are large (300 n
When the light of (m to 700 nm) is used as the detection light, the detection value changes with high sensitivity according to the change in blood volume, so that the S / N ratio of the pulse wave waveform MH based on the change in blood volume can be increased.

<4-2: Wristwatch Type B> Next, another example of the configuration when the heart function diagnostic apparatus 1 is a wristwatch type will be described with reference to FIG. In this configuration, the pulse waveform of the subject is not detected photoelectrically by an LED, a phototransistor, or the like, but is detected by using a pressure sensor. As shown in FIG. 1A, the pulse wave diagnostic apparatus 1 is provided with a pair of bands 102, 102, and the elastic rubber 131 of the pressure sensor 130 is provided on the fastening side of one fastener 120. Are provided to protrude. The band 102 having the fastener 120 is used to supply a detection signal from the pressure sensor 130 to a flexible printed circuit (FPC).
(Printed Circuit) A structure in which a substrate is covered with a soft plastic (details are not shown).

At the time of use, the elastic wave 131 provided on the fastener 120 is positioned near the radial artery 140 as shown in FIG. Is wound around the left arm 150 of the subject. For this reason, a pulse wave can be constantly detected. Note that this winding does not differ from the usual use state of the wristwatch. When the elastic rubber 131 is pressed in the vicinity of the radial artery 140 of the subject in this way, the blood flow fluctuation (that is, a pulse wave) of the artery is transmitted to the pressure sensor 130 via the elastic rubber 131, and the pressure sensor 130 transmits the blood pressure fluctuation to the blood pressure. Is detected.

<4-3: Necklace Type> Further, it is conceivable that the cardiac function diagnostic apparatus 1 according to each embodiment is a necklace type as shown in FIG. In this figure, the pressure sensor 130 is provided at the distal end of the cable 101, and is attached to the carotid artery of the subject using, for example, an adhesive tape 170 as shown in FIG. In FIG. 22, a main part of the device is incorporated in a device main body 100 shaped like a broach having a hollow portion, and a display unit 11 is provided on the front surface thereof.
0, and switches SW1 and SW2 are provided. In addition,
A part of the cable 101 is embedded in the chain 160, and supplies the signal MH output from the pressure sensor 130 to the apparatus main body 100.

<4-4: Eyeglass Type> As an example of the form of the heart function diagnostic apparatus 1 according to each embodiment, an eyeglass type shown in FIG. 24 can be considered. As shown in this figure, the apparatus main body is divided into a case 100a and a case 100b, each of which is separately attached to the vine 181 of glasses, and electrically connected to each other via a lead wire embedded inside the vine 181. . A liquid crystal panel 183 is attached to the side of the lens 182 of the case 100a, and a mirror 184 is fixed to one end of the side at a predetermined angle. A drive circuit for the liquid crystal panel 183 including a light source (not shown) and a circuit for creating display data are incorporated in the case 100a.
Is composed. The light emitted from this light source is reflected by a mirror 184 via a liquid crystal panel 183 and is reflected by a lens 18.
2 is projected. The main part of the device is incorporated in the case 100b, and the above-described switches SW1 and SW2 are provided on the upper surface thereof. On the other hand, pressure sensor 1
Reference numeral 30 is electrically connected to the case 100b via the cable 101, and is attached to the carotid artery like the necklace. The lead wire connecting the case 100a and the case 100b may be crawled along the vine 181. Further, in this example, the apparatus main body is divided into two cases, the case 100a and the case 100b, but these may be constituted by a case in which these are integrated.
Further, the mirror 184 may be movable so that the angle with the liquid crystal panel 183 can be adjusted.

<4-5: Card Type> As another embodiment, a card type as shown in FIG. 25 can be considered. The card-type apparatus main body 100 is, for example, housed in a left breast pocket of a subject. The pressure sensor 130 is electrically connected to the apparatus main body 100 via the cable 101, and is attached to the subject's carotid artery, as in the case of necklaces and glasses.

<4-6: Pedometer Type> Further, as another embodiment, a pedometer type as shown in FIG. The main body 100 of the pedometer is attached to the subject's waist belt 191 as shown in FIG. The pressure sensor 130 is electrically connected to the apparatus main body 100 via the cable 101, is fixed to the femoral artery at the hip joint of the subject by an adhesive tape, and is protected by the supporter 192. At this time, it is desirable to take measures such as sewing the cable 101 into clothes so as not to disturb the daily life of the subject.

<5: Notification by Notification Unit> Next, the notification of the notification unit 74 of each embodiment will be described. In each embodiment, the notification unit 74 has been described as notifying the analysis / diagnosis result by display or sound, but the present invention is not limited to this. That is, it is possible to notify by various senses other than sight and hearing. For example, as a notification that appeals to tactile sensation, a configuration in which an electrode is provided on the back surface of a wristwatch or the like and an electrical stimulus is provided by energizing the electrode may be considered. Further, as a structure that allows a protrusion to be put in and taken out from the back of a portable device such as a wristwatch, a configuration in which a mechanical stimulus is provided by the protrusion can be considered. On the other hand, as a notification that appeals to the sense of smell, a configuration in which a device for discharging a fragrance or the like is provided in the device, the content of the notification is made to correspond to the scent, and the fragrance is discharged according to the content of the notification may be considered. Incidentally, a micropump or the like is suitable for a mechanism for discharging a fragrance or the like. Of course, these may be used alone or in combination with a plurality of means.

[0107]

As described above, according to the present invention,
It is possible to diagnose the cardiac function status of the subject without processing one or more cycles of the pulse wave waveform detected from the subject. Therefore, the state of the cardiac function can be diagnosed with a simpler configuration, which can greatly contribute to the reduction in size and weight of the device.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of a cardiac function diagnostic device according to a first embodiment of the present invention.

FIG. 2 is a block diagram showing a detailed configuration of a peak point extraction / waveform analysis unit in the embodiment.

FIG. 3 is a diagram for explaining storage contents of a peak information memory;

FIG. 4 is a diagram showing an example of a pulse waveform stored in a waveform memory.

FIG. 5 is a diagram showing a correspondence between a change rate and evaluation contents.

FIG. 6 is a diagram showing a correspondence between a change rate and display contents.

FIG. 7 is a diagram showing an example of a display showing a temporal transition of the amplitude of a tidal wave.

FIG. 8 is a diagram illustrating an example of a configuration of an external device.

FIG. 9 is a block diagram showing a configuration of a cardiac function diagnostic device according to a second embodiment of the present invention.

FIG. 10 is a block diagram illustrating a detailed configuration of a wavelet transform unit according to the embodiment.

FIG. 11A is a diagram for explaining a pulse wave waveform read from a waveform memory and subjected to wavelet transform in the same embodiment, and FIG. 11B is a diagram showing an analysis result thereof.

FIG. 12 is a block diagram illustrating a configuration of a cardiac function diagnostic device according to a third embodiment of the present invention.

FIG. 13 is a diagram showing a window function stored in a window function storage unit in the embodiment.

FIG. 14A is a diagram showing a pulse wave waveform read from a waveform memory in the same embodiment, and FIG.
It is a diagram showing a window function read from the window function storage unit,
(C) is the result of multiplication of the pulse waveform and the window function,
FIG. 4 is a diagram for explaining a waveform subjected to FT processing.

15A is an electrocardiogram, FIG. 15B is a diagram showing an aortic blood pressure waveform, and FIG. 15C is a diagram showing a pulse wave waveform at a peripheral portion.

FIG. 16 is a diagram for explaining correspondence between a pulse waveform and a waveform parameter.

FIG. 17 is a diagram showing a correlation between a blood pressure value difference (y ₅ −y ₄ ) and a distortion factor d.

FIG. 18A is a circuit diagram showing a configuration of a four-element lumped parameter model simulating a human artery system;
(B) is a circuit diagram showing a configuration of a five-element lumped parameter model.

FIGS. 19 (a) to (c) are views showing the external configuration when the configuration of the embodiment is a wristwatch type.

FIG. 20 is a diagram illustrating a configuration of a pulse wave detection unit according to the embodiment.

21A is a diagram illustrating an external configuration when the configuration of the embodiment is another wristwatch type, and FIG. 21B is a diagram illustrating a mounted state thereof.

FIG. 22 is a diagram illustrating an appearance configuration when the configuration of the embodiment is a necklace type.

FIG. 23 is a diagram showing a state in which a pulse wave detection unit is attached to a carotid artery.

FIG. 24 is a diagram illustrating an appearance configuration when the configuration of the embodiment is a spectacle type.

FIG. 25 is a diagram showing an external configuration when the configuration of the embodiment is a card type.

26A is a diagram showing an external configuration when the configuration of the embodiment is a pedometer type, and FIG. 26B is a diagram showing a mounted state thereof.

FIGS. 27A to 27C are diagrams each showing a typical pulse waveform shape;

FIG. 28 is a diagram showing a correlation between a distortion factor d and a pulse waveform.

[Explanation of symbols]

10 pulse wave detecting section (pulse wave detecting means), 20 body motion detecting section (body motion detecting means), 30 body motion component removing section (body motion component removing means), 40 peak point extraction・ Waveform analysis unit (systole identification means, peak point detection means, analysis means), 6
0: Beat conversion table, 72, 80, 90 ... Evaluation unit (evaluation means, change rate calculation means), 73 ... Evaluation content storage unit, 74 ... Notification unit (notification means), 76 ... Communication I /
F, 200: Wavelet transform unit, 260: FF
T processing unit (200 or 260 is frequency analysis means),
210: frequency correction unit (normalization means), 220, 26
0: sample storage unit (storage means), 230: window function reading unit, 240: window function storage unit (230 and 24)
0: function generating means), 250: multiplying unit (multiplying means)

Claims (19)

[Claims] 1. A pulse wave detecting means for detecting a pulse waveform from a living body, a systole specifying means for specifying a systole of the heart from the pulse waveform, and a systolic specifying means of the pulse wave waveform. Analysis means for analyzing a part or all of the waveform corresponding to the specified systole, and evaluation means for evaluating the cardiac function state of the living body based on the analysis result by the analysis means, Heart function diagnostic device. 2. The systolic phase specifying means detects a minimum point of a pulse waveform of at least one cycle or more, and corresponds to a valve closing from a minimum point corresponding to opening of the aortic valve of the heart in the pulse waveform. 2. The cardiac function diagnostic apparatus according to claim 1, wherein a minimum point is specified as a systole of the heart. 3. The systolic phase specifying means sets the point having the smallest value among the detected minimum points as the minimum point corresponding to the aortic valve release of the heart, and the second lowest value from the bottom. 3. The cardiac function diagnostic apparatus according to claim 2, wherein the minimum point is a point corresponding to the aortic valve closure of the heart. 4. The systolic phase specifying means sets a point having a minimum value among the detected minimum points as a minimum point corresponding to aortic valve opening of the heart, and counting from the minimum minimum point. 3. The cardiac function diagnostic apparatus according to claim 2, wherein the third minimum point that appears is a point corresponding to aortic valve closure of the heart. 5. The evaluation means comprises: storage means for preliminarily storing analysis results corresponding to a typical cardiac function state and diagnosis contents corresponding thereto; and storage of diagnosis contents corresponding to analysis results by the analysis means. The cardiac function diagnostic apparatus according to claim 1, further comprising: a reading unit that reads out from the unit. 6. A pulse rate calculating means for calculating a pulse rate from a pulse waveform detected by the pulse wave detecting means, wherein the evaluation means includes a pulse rate calculated by the pulse rate calculating means together with an analysis result by the analyzing means. The cardiac function diagnostic apparatus according to claim 1, wherein the cardiac function state of the living body is evaluated based on the number. 7. The cardiac function diagnosis apparatus according to claim 1, further comprising a notification unit that notifies an evaluation result by the evaluation unit. 8. The analysis means analyzes a waveform determined by the characteristics of the heart and the arterial system among the pulse wave waveforms corresponding to the systole specified by the systole identification means, and defines the waveform. The cardiac function diagnostic apparatus according to claim 1, wherein an index is calculated, and the evaluation unit evaluates a cardiac function state of the living body using the index calculated by the analysis unit. 9. The analysis means, as a waveform determined by the characteristics of the heart and the arterial system, a second one of the pulse wave waveforms corresponding to the systole identified by the systole identification means, 9. The cardiac function diagnostic apparatus according to claim 8, wherein analysis is performed. 10. A change rate calculation means for calculating a change rate of the index, wherein the evaluation means evaluates a cardiac function state of the living body in accordance with the change rate calculated by the change rate calculation means. The cardiac function diagnostic apparatus according to claim 8, wherein: 11. The evaluation means classifies the rate of change into a plurality of levels in advance according to the magnitude of the value, and associates the evaluation content with each level, while calculating the rate of change by the rate-of-change calculating means. The cardiac function diagnostic apparatus according to claim 10, wherein the evaluation content corresponding to the stage to which the change rate belongs is evaluated as the cardiac function state of the living body. 12. The apparatus for diagnosing cardiac function according to claim 8, further comprising means for creating a temporal transition regarding the index. 13. A body movement detecting means for detecting a body movement waveform indicating a body movement of the living body, a body movement component existing in the pulse wave waveform is generated from the body movement waveform, and the body is detected from the pulse wave waveform. Body movement component removing means for removing a moving component, wherein the analyzing means obtains a waveform determined by the characteristics of the heart and the arterial system from the pulse wave waveform from which the body movement component has been removed by the body movement component removing means. 9. The cardiac function diagnostic apparatus according to claim 8, wherein analysis is performed. 14. The frequency analyzing part or the whole of a waveform corresponding to the systole specified by the systolic specifying part among the pulse wave waveforms detected by the pulse wave detecting part. The analysis means, wherein the evaluation means evaluates a cardiac function state of the living body based on the frequency analysis result.
The cardiac function diagnostic apparatus according to the above. 15. The frequency analysis unit performs a wavelet transform on a part or all of a waveform corresponding to a systole identified by the systole identification unit in a pulse wave waveform detected by the pulse wave detection unit. 15. The cardiac function diagnostic apparatus according to claim 14, wherein the analysis unit generates analysis data for each frequency domain, and the evaluation unit evaluates a cardiac function state of the living body based on the analysis data. 16. A body movement detecting means for detecting a body movement waveform indicating the body movement of the living body, a body movement component existing in the pulse wave waveform is generated from the body movement waveform, and the body is detected from the pulse wave waveform. 16. A body movement component removing unit for removing a moving component, wherein the frequency analysis unit performs a wavelet transform on the pulse wave waveform from which the body moving component has been removed by the body moving component removing unit.
The cardiac function diagnostic apparatus according to the above. 17. A normalization means for normalizing power per frequency with respect to the analysis data, wherein the evaluation means determines a cardiac function of the living body based on the analysis data normalized by the normalization means. The cardiac function diagnostic device according to claim 15, wherein the condition is evaluated. 18. The frequency analysis means for extracting a part or all of a waveform corresponding to a systole specified by the systole specification means from a pulse wave waveform detected by the pulse wave detection means. Function generating means for generating a function of: a multiplying means for multiplying the pulse wave waveform detected by the pulse wave detecting means with the function generated by the function generating means; The cardiac function diagnostic apparatus according to claim 14, further comprising processing means for performing series expansion. 19. A body movement detecting means for detecting a body movement waveform indicating a body movement of the living body, a body movement component existing in the pulse wave waveform is generated from the body movement waveform, and the body is detected from the pulse wave waveform. 19. A body movement component removing unit for removing a moving component, wherein the multiplying unit multiplies the pulse wave waveform from which the body movement component has been removed by the body moving component removing unit by a function. The cardiac function diagnostic apparatus according to the above.