Patent Publication Number: US-2013231576-A1

Title: Somatic data-measuring apparatus and somatic data measurement method

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     The present application is based on the International Application No. PCT/JP2011/073338 which was filed on Oct. 11, 2011 and claims priority under 35 U.S.C. §119 from Japanese Patent Application No. 2010-229873 which was filed on Oct. 12, 2010. 
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The invention relates to a technology for measuring various somatic data concerning heart, exercise intensity, etc. 
     2. Background Art 
     People, especially those having problems with obesity or metabolic syndrome, walk or jog in order to stay healthy. Furthermore, grade exercise is also useful for rehabilitation in patients of myocardinal infraction and hypertension. 
     In grade exercise, it is difficult to have advantages if load (intensity) is low, and on the contrary, there is a risk that too much load exerts a harmful influence on body. It is thus preferable to find optimal exercise intensity for each of the patients. 
     Japanese Patent Application Publications Nos. 2006-116161 and 2007-14777 suggest a technique concerning optimal exercise intensity. 
     A method of determining an optimal exercise intensity, suggested in Japanese Patent Application Publication No. 2006-116161, includes steps to perform grade exercise in gradual levels, recording amplitude of first heart sound (S 1  sound) generated when atrioventricular valves are closed for each of grade exercise levels, onto a heart sound diagram through a heart sound microphone attached to the patient&#39;s chest, and determining optimal exercise intensity which is at HSBP when the amplitude of heart sound suddenly rises. 
     A method of determining an optimal exercise intensity, suggested in Japanese Patent Application Publication No. 2007-14777, includes steps to detect how much the degree of amplitude of first heart sound varies compared to the degree in which an exercise load intensity varies, detect how much the degree (a rate) of a period in which a heart extends varies in one heart cycle concerned to a degree by which an exercise load intensity varies, and to determine, if a degree by which a rate of heart diastolic time to one heart cycle is equal to or greater than a first standard degree at a bending point at which an amplitude of first heart sound varies, the bending point as optimal exercise intensity. 
     In the above-mentioned Japanese Patent Application Publications Nos. 2006-116161 and 2007-14777, optimal exercise intensity is determined by the value of amplitude of first heart sound alone. However, the judgment made only with amplitude of first heart sound as an index for determining optimal exercise intensity lacks accuracy. If a patient suffers from a heart disease there is a risk that optimal exercise intensity determined by the value of amplitude of first heart sound alone will be excessive, and result in possible harmful influence on the patient. 
     It is known that myocaridnal oxygen consumption is correlated with a degree of exercise load, and thus, can act as an index representing the same. Myocardinal oxygen consumption is calculated as a double product, specifically, (heart rate)×(an internal pressure in a ventricle), in which an internal pressure in a ventricle is replaced with a systolic blood pressure which can be measured at upper arm since it is difficult to measure an internal pressure in a ventricle. Though it is better to evaluate myocardinal oxygen consumption by the double product than to evaluate it only by an amplitude of first heart sound, and it is preferable that myocardinal oxygen consumption is calculated as a triple product defined by (heart rate)×(contractility of heart muscle)×(tension force at a wall of a ventricle) in order to further enhance accuracy. It is known that contraction of heart muscle can be replaced with amplitude of first heart sound, and a tension force at a wall of a ventricle can be replaced with amplitude of second heart sound. 
     However, second heart sound has amplitude smaller than that of first heart sound, and can be disrupted by noises during exercise, which makes it difficult to accurately measure second heart sound. Accordingly, if myocardinal oxygen consumption could be accurately measured, it would be possible to measure optimal exercise intensity, apply optimal exercise remedy to a patient, improve a condition of a patient, and enhance exercise capacity of a patient. 
     SUMMARY OF THE INVENTION 
     Thus, it is a target of the present invention to provide an apparatus for detecting somatic data and a method of doing it both of which make it possible to readily and accurately measure optimal exercise intensity of a target person. 
     The inventors conducted the experiments on a lot of target persons, and discovered a correlation between systolic blood pressure and amplitude of first heart sound. The present invention is based on the discovery. 
     An apparatus for detecting somatic data, in accordance with the present invention includes a first unit for sampling heart sound of a target person while the target person is exercising, a second unit for detecting first heart sound on the basis of the heart sound a third unit for measuring an amplitude of the first heart sound a fourth unit for counting a heart rate of the target person while the target person is exercising, a fifth unit for storing heart rate of the target person to be measured when the target person is resting, and an amplitude of first heart sound of the target person to be measured when the target person is resting, and a sixth unit for computing a double product of a ratio between the heart rate of the target person to be measured when the target person is resting and the heart rate to be measured when the target person exercises, and a ratio between the amplitude of first heart sound of the target person to be measured when the target person is resting and the amplitude of first heart sound of the target person to be measured when the target person exercises, and detecting an optimal exercise intensity of the target person on the basis of the double product. 
     A method of detecting somatic data, in accordance with the present invention, includes first step of sampling heart sound of a target person to be measured while the target person is exercising, second step of detecting first heart sound on the basis of the heart sound, third step of measuring an amplitude of the first heart sound, fourth step of counting a heart rate of the target person to be measured while the target person is exercising, fifth step of storing heart rate of the target person to be measured when the target person is resting, and an amplitude of first heart sound of the target person to be measured when the target person is resting, and sixth step of computing a ratio between the heart rate of the target person to be measured when the target person is resting and the heart rate to be measured when the target person exercises, and a ratio between the amplitude of first heart sound of the target person to be measured when the target person is resting and the amplitude of first heart sound of the target person to be measured when the target person exercises, and detecting optimal exercise intensity of the target person on the basis of the double product. 
     In accordance with the present invention, the first unit first samples heart sound of a target person, and outputs the sampled heart sound as heart sound data. The second unit detects first heart sound on the basis of the heart sound data, and the third unit measures an amplitude on the basis of the first heart sound, and outputs the same as first heart sound amplitude data. Then, the fourth unit counts a heart rate of the target person, and outputs the same as heart rate data. Then, the sixth unit computes, as double product data, a double product of the heart rate data to the first heart sound amplitude data, and detects an optimal exercise intensity on the basis of the double product. Since a double product of an amplitude of first heart sound indicative of myocardinal oxygen consumption to a heart rate is more effective as an index accurately reflecting a condition of a load exerted on a heart than an index of amplitude of first heart sound alone, even if the target person had heart disease, it is possible to accurately measure a degree of load exerting on a patient&#39;s heart. 
     The sixth unit detects an exercise intensity at which a line approximate to a distribution of said double product is bending, as optimal exercise intensity, for instance. 
     The sixth unit may be designed to divide the double product into a first group covering the double product before bending point appears and a second group covering the double product after bending point appeared compute a regression line of the first group as a first approximation line, computes a regression line of the second group as a second approximation line, select, among combinations of the first approximation line and the second approximation line, a combination which minimize a sum of a residual sum of squares of the first approximation line and a residual sum of squares of the second approximation line, and detect an intersection point of the first and second approximation lines of the selected combination as the optimal exercise intensity, ensuring it is possible to obtain an optimal exercise intensity with high accuracy. 
     It is preferable that the apparatus includes also a seventh unit which puts the optimal exercise intensity detected by the sixth unit into a relational expression derived from a correlation between the optimal exercise intensity and a maximum volume of oxygen taken by a target person during grade exercise, obtained by measuring a plurality of target persons, to thereby detect a maximum volume of oxygen taken by the target person during grade exercise. 
     Since the seventh unit makes it possible to detect a maximum volume of oxygen taken by the target person while he/she is exercising, on the basis of optimal exercise intensity detected by the sixth unit, and a relational expression derived from a correlation between the optimal exercise intensity and the maximum volume of oxygen, it is possible to compute aerobic exercise capacity of the target person. Since optimal exercise intensity can be calculated on the basis of a double product of an amplitude of first heart sound to a heart rate, and a maximum volume of oxygen taken by a target person can be calculated on the basis of the optimal exercise intensity, it is possible to specifically measure aerobic exercise capacity of the target person on the basis of the thus calculated maximum volume of oxygen. 
     The fifth unit preferably stores central blood pressure to be measured when the target person is resting, in which case, it is preferable that the apparatus further includes an eighth unit for computing central blood pressure while the target person is being tested on the basis of central blood pressure to be measured while the target person is resting, in accordance with a ratio between the amplitude of first heart sound of the target person to be measured while the target person is resting as standard data and received from the first heart sound amplitude measuring means, and the amplitude of first heart sound of the target person to be measured while the target person is being tested. 
     The eighth unit may be designed to estimate central blood pressure of the target person while the target person is being tested, in accordance with a relational expression between central blood pressure and amplitude of the first heart sound, the relational expression being defined for each of target persons on the basis of central blood pressure and amplitude of first heart sound of a target person both to be measured while the target person is resting, and-central blood pressure and amplitude of first heart sound of a target person both to be measured while the target person exercises. Thus, it is possible to compute central blood pressure in accordance with a relational expression corresponding to each of target persons, and hence, central blood pressure can be computed with accuracy. Herein, the phrase “the target person is exercising” indicates that he/she is performing exercise, namely, he/she is moving his/her body. 
     It is preferable that the second unit includes a second-A unit for measuring electrocardiogram of the target person, a second-B unit for detecting an R-wave out of the electrocardiogram a second-C unit for generating a gate signal, in accordance with timing at which the R-wave is generated, indicative of a certain period including first heart sound corresponding to the R-wave, and a second-D unit for detecting first heart sound on the basis of the heart sound taken while the gate signal is being generated. 
     The second-A unit measures electrocardiogram of the target person, and the second-B unit detects an R-wave. The second-C unit generates a gate signal, in accordance with a timing at which the R-wave is generated, indicative of a certain period including first heart sound corresponding to the R-wave, and hence, the second-D unit can detect first heart sound included the gate signal. 
     In the method in accordance with the present invention, it is preferable that the sixth step includes detecting an exercise intensity at which a line approximate to a distribution of the double product is bending, as optimal exercise intensity. 
     In the method in accordance with the present invention, it is preferable that the sixth step includes dividing the double product into a first group covering the double product before a bending point appears and a second group covering the double product after a bending point appeared, computing a regression line of the first group as a first approximation line, computing a regression line of the second group as a second approximation line, selecting, among combinations of the first approximation line and the second approximation line, a combination which minimizes a sum of a residual sum of squares of the first approximation line and a residual sum of squares of the second approximation line, and detecting an intersection point of the first and second approximation lines of the selected combination as the optimal exercise intensity. 
     It is preferable that the method in accordance with the present invention further includes seventh step of putting the optimal exercise intensity detected in the sixth step into a relational expression derived from a correlation between the optimal exercise intensity and a maximum volume of oxygen taken by a target person during grade exercise, obtained by measuring a plurality of target persons, to thereby detect a maximum volume of oxygen taken by the target person during grade exercise. 
     In the method in accordance with the present invention, it is preferable that central blood pressure is measured when the target person is resting and stored in the fifth step, in which case, the method further includes eighth step of computing a central blood pressure while the target person is being tested on the basis of a central blood pressure to be measured while the target person is resting in accordance with a ratio between the amplitude of first heart sound of the target person to be measured while the target person is resting as standard data and received from the first heart sound amplitude measuring means, and the amplitude of first heart sound of the target person to be measured while the target person is being tested. 
     In the method in accordance with the present invention, it is preferable that the eighth step includes estimating a central blood pressure of the target person while the target person is being tested, in accordance with a relational expression between a central blood pressure and an amplitude of the first heart sound, the relational expression being defined for each of target persons on the basis of a central blood pressure and an amplitude of first heart sound of a target person both to be measured while the target person is resting, and a central blood pressure and an amplitude of first heart sound of a target person both to be measured while the target person exercises. 
     In the method in accordance with the present invention, it is preferable that the second step includes measuring electrocardiogram of the target person, detecting an R-wave out of the electrocardiogram, generating a gate signal, in accordance with timing at which the R-wave is generated, indicative of a certain period including first heart sound corresponding to the R-wave, and detecting first heart sound on the basis of the heart sound taken while the gate signal is being generated. 
     The present invention further provides a computer-readable storage medium containing a set of instructions for causing a computer to carry out a method of detecting somatic data, the set of instructions comprising first instruction for detecting first heart sound on the basis of heart sound of a target person to be measured while the target person exercises, second instruction for measuring an amplitude of the first heart sound, third instruction for storing a heart rate of the target person to be measured when the target person is resting, and an amplitude of first heart sound of the target person to be measured when the target person is resting, and fourth instruction for computing a double product of a ratio between the heart rate of the target person to be measured when the target person is resting and the heart rate to be measured when the target person exercises, and a ratio between the amplitude of first heart sound of the target person to be measured when the target person is resting and the amplitude of first heart sound of the target person to be measured when the target person exercises, and detecting an optimal exercise intensity of the target person on the basis of the double product. 
     It is preferable that the sixth step includes detecting an exercise intensity at which a line approximate to a distribution of the double product is bending, as optimal exercise intensity. 
     It is preferable that the fourth instruction includes dividing the double product into a first group covering the double product before a bending point appears and a second group covering the double product after a bending point appeared, computing a regression line of the first group as a first approximation line, computing a regression line of the second group as a second approximation line, selecting, among combinations of the first approximation line and the second approximation line, a combination which minimize a sum of a residual sum of squares of the first approximation line and a residual sum of squares of the second approximation line, and detecting an intersection point of the first and second approximation lines of the selected combination as the optimal exercise intensity. 
     It is preferable that the instructions further includes fifth instruction for putting the optimal exercise intensity detected by the fourth instruction into a relational expression derived from a correlation between the optimal exercise intensity and a maximum volume of oxygen taken by a target person during grade exercise, obtained by measuring a plurality of target persons, to thereby detect a maximum volume of oxygen taken by the target person during grade exercise. 
     It is preferable that a central blood pressure is measured when the target person is resting and stored in the third instruction, in which case, the instructions may further include sixth instruction for computing a central blood pressure while the target person is being tested on the basis of central blood pressure to be measured while the target person is resting, in accordance with a ratio between the amplitude of first heart sound of the target person to be measured while the target person is resting as standard data and received from the first heart sound amplitude measuring means, and the amplitude of first heart sound of the target person to be measured while the target person is being tested. 
     It is preferable that the sixth instruction includes estimating a central blood pressure of the target person while the target person is being tested, in accordance with a relational expression between a central blood pressure and an amplitude of the first heart sound, the relational expression being defined for each of target persons on the basis of a central blood pressure and an amplitude of first heart sound of a target person both to be measured while the target person is resting, and a central blood pressure and an amplitude of first heart sound of a target person both to be measured while the target person exercises. 
     It is preferable that the first instruction includes measuring electrocardiogram of the target person, detecting an R-wave out of the electrocardiogram, generating a gate signal, in accordance with a timing at which the R-wave is generated, indicative of a certain period including first heart sound corresponding to the R-wave, and detecting first heart sound on the basis of the heart sound taken while the gate signal is being generated. 
     The advantages obtained by the aforementioned present invention will be described hereinbelow. 
     In accordance with the present invention, it is possible to easily detect optimal exercise intensity only by measuring amplitude of first heart sound and heart rate, with higher accuracy than when optimal exercise intensity computed by amplitude of first heart sound alone. Furthermore, the present invention makes it possible to easily compute myocardinal oxygen consumption as a double product of amplitude of first heart sound to a heart rate without using a triple product of a heart rate, contraction of heart muscle, and a tension force at the wall of a ventricle. 
     The above and other objects and advantageous features of the present invention will be made apparent from the following description made with reference to the accompanying drawings, in which reference characters designate the same or similar parts throughout the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates a target person whose heart stress is to be measured by the apparatus for detecting somatic data, in accordance with the first embodiment of the present invention. 
         FIG. 2  is a block diagram of the apparatus illustrated in  FIG. 1 . 
         FIG. 3A  is a block diagram of an example of the heart sound sampling means, and  FIG. 3B  is a block diagram of an example of the electrocardiogram measuring means. 
         FIG. 4A  indicates a position at which heart sound and electrocardiogram are measured, and  FIG. 4B  is a perspective view of a sensor unit. 
         FIG. 5  illustrates examples of an electrocardiogram and a heart sound diagram. 
         FIGS. 6A ,  6 B,  6 C and  6 D are graphs each indicating a relation between amplitude of first heart sound and central blood pressure in each of four target persons. 
         FIG. 7  is a graph indicating a relation between exercise intensity and a double product. 
         FIG. 8  is a graph indicating relations among exercise intensity, a double product, and secretion quantity of adrenalin. 
         FIG. 9  is a graph indicating a relation between a double product and a triple product. 
         FIG. 10  is a graph indicating a relation between optimal exercise intensity and maximum volume of oxygen taken by a target person. 
         FIG. 11  is a block diagram of the apparatus for detecting somatic data, in accordance with the second embodiment of the present invention. 
     
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     First Embodiment 
     The apparatus for detecting somatic data, in accordance with the first embodiment of the present invention, is explained hereinbelow with reference to the drawings. 
     As illustrated in  FIG. 1 , the apparatus  1  for detecting somatic data measures a target person&#39;s condition when he/she is resting or when he/she is exercising through using exercise machine A to thereby provide various somatic data. 
     As illustrated in  FIG. 2 , the apparatus  1  includes an electrocardiogram measuring means  2 , a heart sound sampling means  3 , a heart rate measuring means  4 , a controlling means  5 , a display means  6 , and a printing means  7 . 
     As illustrated in  FIG. 3A , the electrocardiogram measuring means  2  may be designed to include a measurement electrode  21 , an amplifying means  22 , and an A-D converting means  23 , for instance. The measurement electrode  21  includes two terminals for receiving an electric potential which generates on a target person&#39;s body when his/her heart pulsates, as electrocardiogram signals. The amplifying means  22  is comprised of an amplifier for amplifying the electrocardiogram signals. The A-D converting means  23  has a function of converting the amplified electrocardiogram signals into digital electrocardiogram data, and outputting the digital electrocardiogram data to the controlling means  5 . 
     As illustrated in  FIG. 3B , the heart sound sampling means  3  may be designed to include an acceleration sensor  31 , an amplifying means  32 , and an A-D converting means  33 , for instance. In the first embodiment, the measurement electrode  21  and the acceleration sensor  31  are equipped together in a sensor unit  8  (see  FIG. 4 ). 
     The acceleration sensor  31  senses acceleration in every movement direction, and has a function of sensing heart sound derived from pulsation of a target person&#39;s heart, as acceleration, and outputting the sensed acceleration as a heart sound signal. As illustrated in  FIG. 4B , the acceleration sensor  31  is attached to a target person by means of an adhesive means such as a double-sided adhesive tape attached to a surface thereof. Any type of the acceleration sensor  31  can be employed, if it could sense acceleration in every direction. 
     For instance, the acceleration sensor  31  may be designed to be of an electrostatic capacity detection type in which acceleration is sensed by detecting a variation in a capacity between a movable part and a fixed part of a sensor element, a piezo-resistance type in which acceleration is sensed by detecting deformation of a spring caused by acceleration through the use of a piezo-resistance element equipped in the spring connecting a movable part with a fixed part of a sensor element, or a heat detection type in which acceleration is sensed by detecting, as a thermal resistance, a variation in convection of thermal air current generated by a heater, if the acceleration sensor  31  were designed to be of MEMS type. It is preferable that the acceleration sensor  31  is small-sized when attached to a target person in order not to disturb the target person while exercising, if the acceleration sensor  31  were designed to be any one of the above-mentioned types. The amplifying means  32  is comprised of an amplifier for amplifying a heart sound signal. The A-D converting means  33  has a function of converting the amplified heart sound signal into digital heart sound data, and outputting it to the controlling means  5 . 
     As illustrated in  FIG. 1 , a lengthy single cable  9  extending to the controlling means  5  from the sensor unit  8  connects the electrocardiogram measuring means  2  to the connecting means  5 , and further connects the heart sound sampling means  3  to the controlling means  5 . Thus, a target person is not pulled by the cable  9  each time he/she exercises, to ensure he/she is not disturbed when he/she is performing grade exercise. 
     The heart rate measuring means  4  outputs a heart rate of a target person as heart rate data. The heart rate measuring means  4  may be designed to be able to be attached to a target person&#39;s earlobe, wrist or waist, or in the vicinity of a heart, for instance. In the first embodiment, the heart rate measuring means  4  is designed to be a clip type sandwiching an earlobe of a target person. 
     As illustrated in  FIG. 2 , the controlling means  5  measures a central blood pressure, a secretion volume of adrenalin, and a load exerted on the heart by computation, and may be comprised of a personal computer executing a program for measuring somatic data. 
     The controlling means  5  includes an electrocardiogram input means  501 , a heart sound input means  502 , a reference timing detecting means  503 , a gate signal generating means  504 , a first heart sound detecting means  505 , a first heart sound amplitude measuring means  506 , a central blood pressure estimating means  507 , a heart rate input means  508 , a heart rate counting means  509 , an exercise intensity computing means  510 , an exercise load input means  511 , a suppressing means  512 , an annunciating means  513 , a display controlling means  514 , a print controlling means  515 , an aerobic exercise capacity detecting means  516 , and a storage means  517 . 
     The electrocardiogram input means  501  is comprised of an interface inputting the electrocardiogram data from the electrocardiogram measuring means  2  into the controlling means  5 , and storing the same in the storage means  517 . The heart sound input means  502  is comprised of an interface inputting heart sound data from the heart sound sampling means  3 , and storing the same in the storage means  517 . 
     The reference timing detecting means  503  has a function of detecting an R-wave on the basis of the electrocardiogram data stored in the storage means  517 . The gate signal generating means  504  has a function of outputting a gate signal indicative of a certain period including first heart sound corresponding to the R-wave detected by the reference timing detecting means  503 , that is, a period just prior to second heart sound. The first heart sound detecting means  505  has a function of detecting a peak waveform, as first heart sound, on the basis of the heart sound data made while the gate signal is being output. The first heart sound amplitude measuring means  506  measures an amplitude of the first heart sound detected by the first heart sound detecting means  505 , and outputs the amplitude as first heart sound amplitude data. 
     The central blood pressure estimating means  507  has a function of making computation on the basis of the first heart sound amplitude data taken while a target person is being tested and received from the first heart sound amplitude measuring means  506 , the first heart sound data (“resting” amplitude data) taken while a target person is resting and stored in the storage means  517 , and central blood pressure data (“resting” central blood pressure data) indicative of a central blood pressure while a target person is resting, estimating a central blood pressure (a-systolic blood pressure) to be measured while a target person is being tested, and outputting the estimated central blood pressure as central blood pressure data. 
     The heart rate input means  508  is comprised of an interface inputting the heart rate data from the heart rate measuring means  4  into the controlling means  5 , and storing the same in the storage means  517 . The heart rate counting means  509  has a function of counting a heart rate on the basis of the heart rate data. 
     The exercise intensity computing means  510  has a function of multiplying the first heart sound amplitude data received from the first heart sound amplitude measuring means  506  with the heart rate data received from the heart rate counting means  509  to thereby calculate a double product as double product data (heart load data), and detecting a bending point at which a gradient bends relative to an exercise intensity, on the basis of the double product data. 
     The exercise load input means  511  is comprised of an interface inputting the exercise intensity data from the exercise machine A into the controlling means  5 , and storing the exercise intensity data in the storage means  517 . 
     The suppressing means  512  has a function of outputting a suppression signal to the exercise machine A in accordance with the optimal exercise intensity detected by the exercise intensity computing means  510  in order to prevent a grade exercise carried out by a target person from exceeding the optimal exercise intensity. 
     The annunciating means  513  has a function of making annunciation when the exercise intensity computing means  510  detects the bending point of the gradient or when exercise intensity exceeds a predetermined intensity beyond the bending point. Though the predetermined intensity is over the optimal exercise intensity, it is preferable that the predetermined intensity indicates such exercise load that is not an excessive load to a heart. The predetermined intensity can be determined for each target person. The annunciating means  513  may be designed to generate continuous or intermittent sounds or voice messages, turn on or flicker a lamp (not illustrated), or display messages on the display means  6  through the display controlling means  514 . 
     The display controlling means  514  has a function of controlling display in the display means  6 . The print controlling means  515  has a function of controlling printing carried out by the printing means  7 . 
     The aerobic exercise capacity detecting means  516  has a function of detecting a maximum volume of oxygen taken by a target person during he/she is being loaded at maximum by exercise in accordance with both a relational expression (hereinbelow, the relational expression is called “aerobic exercise capacity calculation expression”) derived from a correlation between the optimal exercise intensity and a maximum volume of oxygen taken by a target person during grade exercise, the optimal exercise intensity detected by the exercise intensity computing means. The aerobic exercise capacity calculation expression is a linear function expressing a regression line indicative of a tendency of the distribution of a maximum volume of oxygen taken by a target person while he/she is exercising, and his/her optimal exercise intensity both obtained by sampling a plurality of target persons. 
     The storage means  517  is comprised of nonvolatile memory into which data can be written and from which data can be read. As the storage means  517 , a hard disc device having a high capacity and enabling high-speed access can be employed. The storage means  517  stores therein heart sound data, electrocardiogram data and heart rate data when measured. Furthermore, the storage means  517  stores therein an amplitude of first heart sound, a central blood pressure, a heart rate, and a double product of an amplitude of first heart sound and a heart rate, all of which are measured when a target person is resting, as “resting” amplitude data, “resting” blood pressure data, “resting” heart rate data, and “resting” double product data. 
     In the first embodiment, the heart sound input means  502 , the reference timing detecting means  503 , the gate signal generating means  504 , and the first heart sound detecting means  505  define the first heart sound detecting means  51 . 
     The display means  6  may be designed to be comprised of CRT, LCD or organic EL display. The printing means  7  may be designed to be comprised of an ink-jet printer, a laser printer, a dot-impact printer or a thermal transfer printer all of which are capable of printing onto a paper. 
     The operation of the apparatus for detecting somatic data in accordance with the first embodiment of the present invention, having the above-mentioned structure, and a method of detecting somatic data are explained hereinbelow with reference to the drawings. 
     When a target person exercises, the sensor unit  8  including the acceleration sensor  31  and the measurement electrode  21  is attached to the target person. The acceleration sensor  31  is attached to a breast of the target person. The acceleration sensor  31  is preferably located above a sternum, as illustrated in  FIG. 4A , and more preferably above a manubrium of sternum BP. The heart rate measuring means  4  is attached to an earlobe, wrist or waist, or in the vicinity of a heart. 
     Then, the target person starts exercising. In the exercise, the target person to which the sensor unit  8  is attached rides on the exercise machine A, specifically, a bicycle ergometer, and pedals continuously. 
     The heart sound signal transmitted from the acceleration sensor  31  is amplified by the amplifying means  32 , and the A-D converting means  33  converts the heart sound signal having been amplified every certain period of time into heart sound data, namely, sampled digital data (heart sound detecting step). The electrocardiogram signal transmitted from the measurement electrode  21  is amplified by the amplifying means  22 , and the A-D converting means  23  converts the electrocaridogram signal having been amplified every certain period of time into electrocardiogram data, namely, sampled digital data (electrocardiogram detecting step). 
     The heart sound input means  502  of the controlling means  5  receives the heart sound data from the heart sound sampling means  3 , and stores the heart sound data into the storage means  517  together with the exercise intensity data received from the exercise machine A. The electrocardiogram input means  501  receives the electrocardiogram data from the electrocardiogram measuring means  2 , and stores the electrocardiogram data into the storage means  517  together with the exercise intensity data received from the exercise machine A. The heart rate input means  508  receives the heart rate data from the heart rate measuring means  4 , and stores the heart rate data into the storage means  517  (heart rate detecting step). The heart rate counting means  509  reads the heart rate data out of the storage means  517 , calculates a heart rate, and stores the heart rate into the storage means  517  as heart rate data (heart rate counting step). 
     The reference timing detecting means  503  detects an R-wave on the basis of the electrocardiogram data stored in the storage means  517 . Herein, an R-wave is explained hereinbelow with reference to  FIG. 5 . 
     Since an R-wave is observed at the end of heart&#39;s expansion, it is possible to use an R-wave as a reference for detecting both first heart sound generated when an auriculoventricular valve (a mitral valve, a tricuspid valve) is closed and second heart sound generated when an arterial valve (an aortic valve, a pulmonary valve) is closed while the heart is pulsating. 
     An R-wave has a higher peak than that of a P-wave, a Q-wave, a S-wave and a T-wave, and rises up more steeply than others. Accordingly, the reference timing detecting means  503  can relatively readily detect an R-wave by detecting electrocardiogram data having a highest peak. 
     On detection of an R-wave, the reference timing detecting means  503  transmits a signal indicating the detection of an R-wave, to the gate signal generating means  504  (reference timing detecting step). 
     On receipt of the signal indicating the detection of an R-wave, the gate signal generating means  504  generates a gate signal G indicative of a certain period including the first heart sound  51  corresponding to the R-wave, in accordance with a timing of the R-wave. The certain period may be determined as a period between a timing at which the R-wave is generated and the second heart sound S 2 . A period between the generation of an R-wave and the second heart sound S 2  depends on individual, and further depends on exercise workload. Furthermore, a period between the generation of an R-wave and the first heart sound S 1  depends on each of target persons&#39; conditions. Accordingly, the certain period would not include the first heart sound S 1 , if the gate signal G were too short, and would include not only the first heart sound S 1 , but also the second heart sound S 2 , if the gate signal G were too long. Thus, a period determined by statistically measuring young to elderly persons is used as the certain period in the first embodiment. 
     The first heart sound detecting means  505  extracts a peak wave (the first heart sound S 1 ) on the basis of the heart sound data taken while the gate signal G is being output (first heart sound detection step). 
     Heart sound extracted while the gate signal G is being output surely includes first heart sound S 1 . In other words, by limiting a range in which data corresponding to the first heart sound S 1  is extracted among the heart sound data by value of the gate signal G, it is possible to remove the second heart sound S 2  and noises. Immediately after a target person starts grade exercise, the first heart sound S 1  is higher than the second heart sound S 2  in some cases, in which it is not possible to discriminate the first and second sounds from each other only by amplitude. That is, it is difficult to identify the first heart sound only on the basis of the heart sound data. Consequently, in the apparatus  1  for detecting somatic data, in accordance with the first embodiment of the present invention, a gate signal as a reference is generated on the basis of an R-wave, and a peak waveform is detected as the first heart sound S 1  in a period indicated by the gate signal, ensuring it possible to extract data of the first heart sound S 1 . 
     The first heart sound amplitude measuring means  506  measures an amplitude V 1  of a peak waveform, and stores the amplitude V 1  into the storage means  517  as first heart sound amplitude data (first heart sound amplitude measuring data). 
     The first heart sound amplitude measuring means  506  is able to read ten first heart sound amplitude data out of the storage means  517 , calculate an average of them, and store the average as single first heart sound amplitude data into the storage means  517 . By averaging a certain number of first heart sound amplitude data, even if the amplitudes of the first heart sound S 1  had a fluctuation, it is possible to reduce its overall influence. Though ten first heart sound amplitude data is simply averaged in the first embodiment, a plurality of first heart sound amplitude data may be averaged by other statistical processes (first heart sound averaging step). 
     The central blood pressure estimating means  507  divides the first heart sound amplitude data measured by the first heart sound amplitude measuring means  506  when a target person is being tested, by the first heart sound amplitude data (amplitude data measured while a target person is resting) measured as reference data while a target person is resting and transferred to the storage means  517  from the first heart sound amplitude measuring means  506 , to thereby have a ratio. The central blood pressure estimating means  507  further computes a central blood pressure of a target person being tested on the basis of the central blood pressure data measured while a target person is resting, read out of the storage means  517 , in accordance with the ratio, and outputs it as central blood pressure data (central blood pressure estimating step). The computation is carried out on the basis of a relational expression between amplitude of first heart sound and a central blood pressure. Herein, the relational expression between amplitude of first heart sound and central blood pressure is explained hereinbelow with reference to  FIG. 6 . 
     The graphs illustrated in  FIGS. 6A to 6D  indicate an amplitude of first heart sound and central blood pressure (systolic blood pressure) of four target persons, having been measured with a grade exercise intensity gradually increased from resting condition to a condition in which a heavy load acts on them. The central blood pressure was measured by a conventional method, that is, by inserting a catheter through wrist and locating the catheter in the vicinity of a heart. The four target persons are all men in their twenties in good health. Each of the graphs has an axis of abscissas (x-axis) indicating a ratio between amplitude of first heart sound measured when a target person is resting and an amplitude of first heart sound measured when a target person exercises, and an axis of ordinates (y-axis) indicating a ratio between a central blood pressure (a systolic phase) measured when a target person is resting and a central blood pressure measured when a target person exercises. 
     Thus, it was found that amplitude of first heart sound has a correlation with a central blood pressure, as shown in the graphs illustrated in  FIGS. 6A to 6D . The correlation can be expressed as the approximation straight line L 11  to L 14 . 
     For instance, a relational expression indicating the approximation line L 11  of a target person A can be expressed by the following expression (1). 
         y=− 0.0138 x   2 +0.1683 x+ 0.8535  (1)
 
     Estimating by Pearson&#39;s correlation coefficients, since the contribution rate R 2  was 0.9256, it was found that the relational expression (1) had a high correlation, and could be applied to almost all cases. 
     Accordingly, supposing that “x1” indicates the first heart sound amplitude data indicating an amplitude of first heart sound measured when a target person is resting, “x2” indicates the first heart sound amplitude data indicating an amplitude of first heart sound measured when a target person is being tested, “y1” indicates the central blood pressure data indicating central blood pressure measured when a target person is resting, and “y2” indicates the central blood pressure data indicating central blood pressure measured when a target person is being tested, the central blood pressure “y2” indicating central blood pressure measured when a target person is being tested can be expressed by the following equation (2). 
         y 2=(−0.0138( x 2 /x 1) 2 +0.1683( x 2 /x 1)+0.8535)× y 1  (2)
 
     The central blood pressure estimating means  507  can accurately calculate central blood pressure to be measured when a target person is being tested (or, is exercising), by carrying out the calculation in accordance with the relational expression (2). 
     Similarly, the relational expressions (3) to (5) indicating the approximation straight line L 12  to L 14  of the target persons B to D are as follows. 
         y=− 0.0451 x   2 +0.3727 x+ 0.6989  (3)
 
         y=− 0.0058 x   2 +0.1388 x+ 0.8871  (4)
 
         y=− 0.0242 x   2 +0.2697 x+ 0.6874  (5)
 
     With respect to the target persons B to D, the contribution rates R 2  for the target persons B, C and D were 0.9082, 0.972 and 0.9258, respectively, indicating a high correlation. Accordingly, it is possible to estimate central blood pressure of the target persons B to D in accordance with the computation based on the relational expressions (3) to (5). 
     It is preferable that the computation used by the central blood pressure estimating means  507  for estimation of central blood pressure is determined for each of target persons. Specifically, an amplitude of first heart sound and central blood pressure (systolic blood pressure) are measured for each of target persons by a conventional process with a grade exercise intensity gradually increased from a resting condition to a condition in which heavy load acts on them, to thereby introduce a relational expression between central blood pressure and amplitude of first heart sound. Then, the relational expression is converted into an expression used for computing central blood pressure to be measured when a target person is being tested, and the obtained expression is stored in the storage means  517  in association with identification data (for instance, a name or an ID number) of each of target persons. When a target person exercises, the central blood pressure estimating means  507  reads the expression associated with a target person out of the storage means  517 , and computes central blood pressure to be measured while a target person is being tested, ensuring that the measurement can be carried out with high accuracy even when a target person is exercising. 
     It was impossible in a conventional process to accurately measure central blood pressure while a target person is exercising, because the measurement was carried out by inserting a catheter through wrist and locating the catheter in the vicinity of a heart. In the apparatus for detecting somatic data in accordance with the first embodiment, it is possible to accurately and readily measure central blood pressure regardless of whether a target person is resting or exercising, by measuring an amplitude of first heart sound, and estimating central blood pressure to be measured when a target person is exercising, on the basis of the amplitude of first heart sound. Thus, it is possible to safely and effectively evaluate exercise and/or exercise remedy for the purpose of keeping healthy, by means of an inexpensive tool. 
     Even if the expression were not prepared for a certain target person, it would be possible to estimate his/her central blood pressure by using an expression prepared for other target person, since central blood pressure has a correlation with amplitude of first heart sound, though accuracy is slightly reduced. 
     Hereinbelow the calculation of a double product carried out by the exercise intensity computing means  510  is explained. When a request of calculating a double product is input through an input means (not illustrated), and is stored in the storage means  517 , the exercise intensity computing means  510  computes a double product of heart rate data and first heart sound amplitude data both stored in the storage means  517 , and outputs the computed double product as double product data (data indicative of a load acting on a heart). 
     In the first embodiment, the double product data is comprised of a double product data of a rate between a heart rate measured when a target person is resting and a heart rate measured when a target person is tested (exercises), and a rate between an amplitude of first heart sound measured when a target person is resting and an amplitude of first heart sound measured when a target person is tested. 
     The exercise intensity (exercise intensity data) and the double product (data indicative of load acting on the heart) of the target person is shown in  FIG. 6B , who is a man in his twenties in good health, are plotted in the graph illustrated in  FIG. 7 . The graph illustrated in  FIG. 7  has an axis of ordinates (Y-axis) indicative of a double product, and an axis of abscissas (X-axis) indicative of exercise intensity. The data shown in the graph is obtained by the exercise intensity computing means  510 , specifically, by reading the first heart sound amplitude data to be measured when a target person is resting and the heart rate data to be measured when a target person is resting, out of the storage means  517 , computing a ratio between the first heart sound amplitude data to be measured when a target person is resting and the first heart sound amplitude data to be measured when a target person exercises, and further a ratio between the heart rate data to be measured when a target person is resting and the heart rate data to be measured when a target person exercises, and multiplying those ratios to thereby compute the double product data. 
     The graph indicates that the bending point P at which a gradient of the approximation line L suddenly increases is the optimal exercise intensity. 
     Herein, how the exercise intensity computing means  510  determines the bending point P is explained in detail. 
     Supposing that “x” indicates an exercise intensity and “y” indicates a double product, it is supposed that there are obtained n data (x 1 , y 1 ), (x 2 , y 2 ) , , , (x n , y n ). Supposing that a line suitable as a regression line can be expressed as “y=ax+b”, “a” and “b” can be calculated in accordance with the following expressions (6) and (7). 
     
       
         
           
             
               
                 
                   a 
                   = 
                   
                     
                       
                         n 
                          
                         
                           
                             ∑ 
                             
                               k 
                               = 
                               1 
                             
                             n 
                           
                            
                           
                               
                           
                            
                           
                             
                               x 
                               k 
                             
                              
                             
                               y 
                               k 
                             
                           
                         
                       
                       - 
                       
                         
                           ∑ 
                           
                             k 
                             = 
                             1 
                           
                           n 
                         
                          
                         
                             
                         
                          
                         
                           
                             x 
                             k 
                           
                            
                           
                             
                               ∑ 
                               
                                 k 
                                 = 
                                 1 
                               
                               n 
                             
                              
                             
                                 
                             
                              
                             
                               y 
                               k 
                             
                           
                         
                       
                     
                     
                       
                         n 
                          
                         
                           
                             ∑ 
                             
                               k 
                               = 
                               1 
                             
                             n 
                           
                            
                           
                               
                           
                            
                           
                             x 
                             k 
                             2 
                           
                         
                       
                       - 
                       
                         
                           ( 
                           
                             
                               ∑ 
                               
                                 k 
                                 = 
                                 1 
                               
                               n 
                             
                              
                             
                                 
                             
                              
                             
                               x 
                               k 
                             
                           
                           ) 
                         
                         2 
                       
                     
                   
                 
               
               
                 
                   ( 
                   6 
                   ) 
                 
               
             
             
               
                 
                   b 
                   = 
                   
                     
                       
                         
                           ∑ 
                           
                             k 
                             = 
                             1 
                           
                           n 
                         
                          
                         
                             
                         
                          
                         
                           
                             x 
                             k 
                             2 
                           
                            
                           
                             
                               ∑ 
                               
                                 k 
                                 = 
                                 1 
                               
                               n 
                             
                              
                             
                                 
                             
                              
                             
                               y 
                               k 
                             
                           
                         
                       
                       - 
                       
                         
                           ∑ 
                           
                             k 
                             = 
                             1 
                           
                           n 
                         
                          
                         
                             
                         
                          
                         
                           
                             x 
                             k 
                           
                            
                           
                             y 
                             k 
                           
                            
                           
                             
                               ∑ 
                               
                                 k 
                                 = 
                                 1 
                               
                               n 
                             
                              
                             
                                 
                             
                              
                             
                               x 
                               k 
                             
                           
                         
                       
                     
                     
                       
                         n 
                          
                         
                           
                             ∑ 
                             
                               k 
                               = 
                               1 
                             
                             n 
                           
                            
                           
                               
                           
                            
                           
                             x 
                             k 
                             2 
                           
                         
                       
                       - 
                       
                         
                           ( 
                           
                             
                               ∑ 
                               
                                 k 
                                 = 
                                 1 
                               
                               n 
                             
                              
                             
                                 
                             
                              
                             
                               x 
                               k 
                             
                           
                           ) 
                         
                         2 
                       
                     
                   
                 
               
               
                 
                   ( 
                   7 
                   ) 
                 
               
             
           
         
       
     
     In the judgement conducted by the exercise intensity computing means  510  for an optimal exercise intensity, since the graph of the double product in which exercise load gradually increases indicates an exponential curve, the data is divided into two groups at a boundary of appearance of the bending point P, specifically, first group covering the data obtained before the bending point P appears, and second group covering the data after the bending point P appeared. 
     Then, the exercise intensity computing means  510  computes regression lines as first and second approximation straight lines in accordance with the above-mentioned expressions (1) and (2) on the basis of both the first group data and the second group data. Then, the exercise intensity computing means  510  selects, among a lot of combinations of the first and second approximation straight lines, a combination of the first and second approximation straight lines which minimizes a residual sum of squares of the first and second approximation straight lines. Then, the exercise intensity computing means  510  judges “x” of the intersection (the bending point P) of the selected first approximation straight line L 21  with the selected second approximation straight line L 22 , as optimal exercise intensity. 
     In the way as mentioned above, the exercise intensity computing means  510  computes the approximation line L comprised of polygonal lines, on the basis of data indicative a load acting on a heart, that is, data of a double product obtained by multiplying an amplitude of first heart sound indicative of a cardiac contractile force with a heart rate, and detects optimal exercise intensity on the basis of a bending curve indicating exercise intensity. 
     Furthermore, a double product of amplitude of first heart sound and a heart rate has a high correlation with secretion quantity of adrenalin. This is considered because a double product of amplitude of first heart sound and a heart rate has a high correlation with oxygen consumption in a heart, and hence, reflects increasing neurotransmitter which induces secretion of adrenalin. 
     For instance,  FIG. 8  illustrates a graph having an axis of ordinates (Y-axis) indicative of both a double product and a secretion quantity of adrenalin (blood concentration) and an axis of abscissas (X-axis) indicative of an exercise intensity in such a condition that grade exercise intensity is gradually increased by causing a target person to perform grade exercise from a condition in which he/she is resting to a condition in which heavy load acts on him/her. A secretion quantity of adrenalin was measured by a conventional process, that is, by taking blood from a target person who is exercising. In light of the graph of  FIG. 8 , it is understood that a double product of amplitude of first heart sound and a heart rate has a correlation with a secretion quantity of adrenalin. It is further understood that the approximation line L 5  teaches that a bending point P at which a gradient of the approximation line L remarkably increases indicates optimal exercise intensity, and that the bending point P defines an intensity threshold at which a secretion quantity of adrenalin starts to increase significantly. 
     Accordingly, it was difficult in a conventional process to measure a secretion quantity of adrenalin while a target person is exercising, because a secretion quantity of adrenalin was measured by taking blood of a target person each time he/she was tested, it is now possible to detect optimal exercise intensity through the use of a double product of an amplitude of first heart sound and a heart rate, and further possible to readily and accurately measure an intensity threshold at which a secretion quantity of adrenalin starts to increase significantly. 
     The apparatus  1  for detecting somatic data in accordance with the first embodiment measures optimal exercise intensity by value of a double product. A triple product of amplitude of first heart sound, a heart rate, and second heart sound may be employed for measuring optimal exercise intensity. As illustrated in  FIG. 9 , it was found that a correlation between a double product and a triple product is almost equal to one. Consequently, in the apparatus  1  for detecting somatic data, the exercise intensity computing means  510  detects optimal exercise intensity by value of a double product without computing a triple product. 
     On detection of an optimal exercise intensity, the exercise intensity computing means  510  stores the detected optimal exercise intensity into the storage means  517  together with predetermined identification data (for instance, a name or an ID number) identifying a target person. By storing the optimal exercise intensity into the storage means  517  in association with identification data, the apparatus  1  for detecting somatic data can record optimal exercise intensity in association with each target person. 
     Since the graph of  FIG. 7  can be illustrated during steps carried out by the exercise intensity computing means  510  for detecting an optimal exercise intensity, the graph may be displayed in the display means  6  through the display controlling means  514 , or printed onto paper medium by means of the print means  7  through the printing controlling means  515 . 
     By detecting an optimal exercise intensity in the above-mentioned way, since the annunciating means  513  makes annunciation when grade exercise is equal to or greater than an optimal exercise intensity, or when grade exercise exceeds an optimal exercise intensity and then becomes equal to or greater than a predetermined exercise intensity, it is possible for a target person to avoid exercising at a harmful load. 
     Furthermore, if optimal exercise intensity for a certain target person was recorded, the annunciating means  513  reads an optimal exercise intensity associated with identification data of the certain target person, out of the storage means  517 , compares the optimal exercise intensity with exercise intensity data received from the exercise machine A to thereby make annunciation. Thus, when the certain target person performs grade exercise again, he/she can perform optimal grade exercise without measuring optimal exercise intensity again. 
     It is explained herein below how the aerobic exercise capacity detecting means  516  detects a maximum volume of oxygen taken by a target person. 
     The graph illustrated in  FIG. 10  has an x-axis indicative of optimal exercise intensities (bending points of double products) of a plurality of target persons, and a y-axis indicative of a maximum volume of oxygen taken by a target person. 
     As is understood in light of the graph of  FIG. 10 , the approximation line (regression line) indicating a relation between optimal exercise intensity and maximum volume of oxygen taken by a target person can be expressed by the following relational expression (8). 
         y= 11.4 x+ 806  (8)
 
     Estimating the relational expression (8) with Pearson&#39;s correlation coefficients, since the correlation coefficient R is equal to 0.760 (significance level P&lt;0.01), it is understood that the relational expression (8) indicates a high correlation. 
     The aerobic exercise capacity detecting means  516  can calculate a maximum volume of oxygen taken by a target person by putting optimal exercise intensity detected by the exercise intensity computing means  510 , into the relational expression (8), that is, the expression for calculating aerobic exercise capacity. 
     As mentioned above, the exercise intensity computing means  510  computes the double product data of a target person, and hence, it is possible to measure optimal exercise intensity. The optimal exercise intensity being measured, the aerobic exercise capacity detecting means  516  can compute aerobic exercise capacity of the target person, and then, it is possible to compute a maximum volume of oxygen taken by the target person on the basis of the computed aerobic exercise capacity. 
     Second Embodiment 
     The apparatus  10   x  for detecting somatic data in accordance with the second embodiment of the present invention is characterized by the heart rate computed on the basis of R-wave or first heart sound. In  FIG. 11 , parts corresponding to those illustrated in  FIG. 2  have been provided with the same reference numerals, and are not explained. 
     The heart rate counting means  509   x  equipped in the controlling means  5   x  of the apparatus  10   x  illustrated in  FIG. 11  counts a heart rate by measuring a period P 1  (see  FIG. 5 ) between R-wave detected by the reference timing detecting means  503  and a subsequent R-wave. 
     Furthermore, the heart rate counting means  509   x  is able to count a heart rate on the basis of the period P 1  in accordance with the first heart sound S 1  detected by the first heart sound detecting means  505 . 
     As mentioned above, it is possible to count a heart rate on the basis of a period between R-waves or first heart sounds both measured during steps carried out for measuring an exercise intensity, without particularly providing means (the heart rate measuring means  4 ) for counting a heart rate unlike the apparatus  1  for detecting somatic data in accordance with the first embodiment. 
     INDUSTRIAL APPLICABILITY 
     The present invention is suitable for measuring central blood pressure which is a blood pressure of a region from which aorta extends, and a stress acting on heart, and suitable in particular for measuring an optimal exercise intensity. 
     While the present invention has been described in connection with certain preferred embodiments, it is to be understood that the subject matter encompassed by way of the present invention is not to be limited to those specific embodiments. On the contrary, it is intended for the subject matter of the invention to include all alternatives, modifications and equivalents as can be included within the spirit and scope of the following claims. 
     The entire disclosure of Japanese Patent Application No. 2010-229873 filed on Oct. 12, 2010 including specification, claims, drawings and summary is incorporated herein by reference in its entirety.