Patent Publication Number: US-2020282262-A1

Title: Method and equipment for monitoring the effectiveness of physical activities,  especially sports activities

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is the § 371 National Stage Entry of International Application No. PCT/HU2018/050031, filed on Jun. 22, 2018, which claims the benefit of Hungarian Patent Application No. P1700468, filed on Nov. 17, 2011, the contents of which applications are herein incorporated by reference in their entirety. 
    
    
     FIELD OF THE INVENTION 
     The invention relates-to a method for monitoring the effectiveness of physical activities, primarily sports activities and to a device for the collection of predetermined biological parameters such as heart and respiration data, ambient temperature, etc. and activity parameters. 
     BACKGROUND OF THE INVENTION 
     There are numerous solutions that analyze the movements and the heart rate during a physical activity, such as a training. A common feature of known solutions is that one or more sensors are fixed, either individually or as an integrated part of an apparatus, on the person performing the activity, then some time-tested algorithms record, analyze and evaluate the measured one or more parameters, and the results are displayed to the user in an increasingly spectacular way, preferably using their portable computing device, such as their smartphones. 
     U.S. Pat. No. 7,753,861 B1 describes a chest strap comprising a device for monitoring the activity of a user performing some sports. The device contains an acceleration sensor, the signal of which is used to derive, besides the motion characteristics, also some biological signals like breathing, heart rate, which are then subjected to statistical processing. The essence of this solution is that the statistics are produced in a general format that is understood and managed by many devices. 
     US 2016143592 A1 describes a portable electronic equipment and the method for measuring a person&#39;s heart rate or muscle activity (EMG). The equipment includes one or more heart beat or muscle activity sensors for generating a heart rate signal or muscle activity signal, and a motion detector for generating a motion signal corresponding to the motion. In addition, it has the processing means for detecting first events corresponding to the individual heart beat or muscle activation from the cardiac function signal or from the muscle activity signal, and for detecting additional events from the motion signal corresponding to movement changes exceeding a predetermined threshold value. Then from the first events it generates their very first sequence; and the heart beat or muscle activity parameters are determined from the very first sequence. In doing so, they omit from the very first sequence the first events that coincide with further events or occur with the same frequency as those further events. In this way, the method allows the removal of motion-induced elements of the ECG and EMG signals for a more accurate sports performance monitoring and characterization, but it does not use the ECG signals to display the athlete&#39;s or user&#39;s current health status and draw conclusions. 
     The solution described in DE 102015120045 A1 uses ECG lead and acceleration sensor. The combined assessment of the two sensors&#39; signals targets to eliminate the effect of motion noise on the heart rate signal, in order to display more reliable data. 
     However, there is no known solution, either in theory or in practice, that would examine, the health consequences of training, especially on cardiac level, in relation to the above; although according to statistical data a non-negligible number of people suffer health damage due to excessive training, disregarding their physical condition. 
     SUMMARY OF THE INVENTION 
     The object of the present invention is to provide a system that allows us
     to continuously collect the typical parameters needed to evaluate the current state of health of a person performing the exercise (hereinafter user or athlete),   to prevent the occurrence of dangerous situations due to previous “overstrain” or other medical reason,   to provide automatic suggestions for training intensity correction for those who run alone or without monitoring or have no continuous expert supervision.   

     The fundamental realization that has led to the invention is that it is possible to create a system, i.e. a method and an apparatus for the above-mentioned purposes using the increasingly popular “fitness” devices that can detect, report and transmit certain physical characteristics—and that people are happy to buy and use nowadays—together with smartphones that are also popular, provided that we can make this system able to provide additional functions beyond the known conventional functions offered by present devices. 
     In the case of known solutions, biological status sensors, such as pulse sensors, are not suitable for deeper analysis in the medical sense, but even if they were, see ECG electrodes, their usual placement is suboptimal for medical interpretation, which excludes the recognition of dangerous medical situations or consequences, such as IHD (ischemic heart disease), VT/VF (ventricular tachycardia/ventricular fibrillation), heart overload, etc.; and, as a result, it is impossible to match the basic objective of the training with the individual&#39;s health status. 
     The object is achieved on the one hand by a method for monitoring the effectiveness of physical activities, especially sports activities, comprising the steps of detecting predefined parameters of a user&#39;s body using one or more sensors placed on an upper body of the user, transmitting the detected parameters as electrical signals to an evaluating electronics, evaluating the parameters on the basis of predetermined criteria by the evaluating electronics, displaying visually the result of this evaluation, adjusting the sensors anatomically to the body size of the user so that the top row of permissible sensor positions arranged in a matrix is at the height of the user&#39;s collarbone and its lowest row is at the height of the user&#39;s navel, dividing the monitoring into three main phases: an idle phase (NYSZ), a load phase (TSZ) and a recovery phase (RSZ) following the exercise, accompanied by a prior preparatory section (ESZ), including examining in the idle phase (NYSZ) the user&#39;s health/physical state of fitness for training, taking into account the medical history of the user and at least one training protocol recorded at the preliminary preparatory section (ESZ), and based on measured heart rate and heart rate variability parameters exceeding the preset limits, issuing a health hazard warning, detecting in the load phase (TSZ) any dangerous changes developing during training, associating pre-set warning and stop criteria to said detected dangerous changes, and determining pathological diagnostic ECG wave parameters from the detected abnormal waveforms, such as PQ, QRS, QT, QT section&#39;s integral, J-point or ST 60  elevation or depression indicative of ischemia, frequent ventricular ectopic beats, setting an optimum load for a stroke volume per cardiac cycle and initiate a change of pace to achieve the required dynamic load protocol, monitoring in the recovery phase (RSZ) after the load phase (TSZ) a heart rate assuagement section and then calculating the parameters of the heart rate variability in the time and frequency domains, and taking the result into account when evaluating the idle phase (NYSZ) during the monitoring related to the next training session. 
     The object is achieved on the other hand by a device for monitoring the effectiveness of physical activities, especially sports activities, comprising: at least two electrodes placed on an upper body of a user, wherein said at least two electrodes are fixed in an electrode strap, evaluating electronics attached to the electrode strap, communicating with the at least two electrodes, and a display unit realized with a mobile personal digital computing device communicating with the evaluating electronics. The at least two electrodes are unipolar or bipolar lead electrodes arranged in the strap and are located to anatomically fit the body size of the user so that the top row of the permissible measuring point matrix determining the location of the electrodes is located at the height of the user&#39;s collarbone, its lowest line is located at the height of the user&#39;s navel, and in the case of the electrode strap, applicable both for male and female body geometry, the connection between the cervical band and the waist strap is provided by a connecting band running along the collarbone insensitive to the body geometry, the electrodes are in a releasable communication connection with a data processing unit used as the evaluation electronics, and the data processing unit communicates with the display unit using wireless connection. 
     The most important additional services offered by the method of the invention—over current solutions that often measure HR, i.e. heart rate based only on pulse measurement—include: 
     When examining the physical health condition for training—based on parameters like resting heart rate (HR) and, if available, a heart rate and heart rate variability (HRV) in a regeneration phase of a previous load—, an acoustic and/or visual signal may be given, for example, on the display unit of the equipment, in the indicator color of a potential hazard, if the newer training could trigger the over-load of the heart muscle. 
     During the examination of physical and health status following the training, the heart rate recovery (HRR) and regeneration phase heart rate variability (HRV) parameters can be measured in calm condition in the time and frequency domains; and further relevant parameters can be determined by calculations such as parameters describing sympathetic and parasympathetic control, respiratory frequency, etc. 
     Like exercise ECG tests, we can detect dangerous changes during training; here, preferably, we can distinguish between warning and stoppage criteria. The detected abnormal changes in the electrocardiogram (ECG) waveforms can be used to measure and calculate the pathological diagnostic ECG wave parameters, PQ, QRS, QT values, the QT section&#39;s integral representing the so-called ventricular repolarization heterogeneity, point J, indicative of ischemia, as well as ST 60  elevation or depression and frequent ventricular ectopic beats. 
     The two main regulatory tasks of training can be achieved: we can ensure optimum load for the maximum stroke volume per cardiac cycle and initiate a change of pace to achieve the required dynamic load protocol by means of an acoustic and/or visual signal. The necessary intervention—essentially feedback—, in the case of a preferred embodiment, is performed by the athlete him or herself; for example, by changing the pace of running, based on analyzes that form an essential element of the method. 
     As a result of the aforementioned features, the device implementing the method of the invention is equally suitable for athletes and for rehabilitation training. The novelty of the device is that it can detect a frontal or rear wall ischemia as a stoppage criterion from a single unipolar lead signal (see  FIG. 1B ); thus, it can be seen as a tool to aid the training&#39;s regulatory functions, which can customize the athlete&#39;s performance in the desired direction based on acoustic and/or visual signals of abnormal heart rate. The current devices are not capable of that. 
     The method and apparatus of the invention will provide data in a variety of details to be used at different levels of competence, i.e. the user, the trainer and the physician, to allow the tracking of the improvement of the training parameter with trend curves and, if required, preprocessed data can be transferred to a database or even into the cloud. 
     The method and equipment can be used both for athletes and for rehabilitation activities in the case of the adjustment parameters corresponding to the state of health. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The invention will now be described in more detail with reference to an example method and apparatus, referring to the accompanying drawing, on which 
         FIGS. 1A, 1B  show Dower&#39;s and unipolar electrode arrangement for the implementation of the method of the invention, schematically illustrating the electrode strap and the processing and display units of the apparatus, 
         FIG. 2  shows a possible design of the equipment&#39;s processing unit in schematic form, assuming a unipolar electrode arrangement, 
         FIG. 3  shows a possible design of the equipment&#39;s processing unit in schematic form, assuming a Dower&#39;s electrode arrangement, 
         FIGS. 4A, 4B  show a flowchart of a possible embodiment of the method of the invention 
         FIG. 5  explains the linear baseline estimation, and 
         FIG. 6  shows explanation and examples of ECG wave parameters in healthy and pathological (ischemic) cases. 
     
    
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
     Unlike commercially available, currently used sensor arrangements, we propose two types of new arrangement, a new unipolar solution (see  FIG. 1B ), and a solution consisting of three bipolar leads, not yet used for this purpose (see  FIG. 1A ). In both cases, our aim is to provide a solution for the detection of pathological, i.e. ischemic alterations, VT/VF tendency, and ventricular function disturbances resulting from overload; and based on this, the system shall automatically recommend load intensity reduction or suspension, or even the interruption of the training. 
       FIG. 1A  shows a Dower&#39;s electrode arrangement;  FIG. 1B  shows a unipolar electrode arrangement as part of the apparatus of the present invention. 
     As shown in  FIG. 1A , three electrodes D_I, D_E, D_A are attached to a narrower strap  2  that is mounted on the user&#39;s chest before the activity. The fourth electrode D_S of the arrangement is conveniently located on the connecting strip  3  connected to strap  2  so as to ensure that electrode D_S is situated in the correct position. In this example, breathing sensor  22  is fixed on strap  2 , although its accurate positioning is not critical. In practice, connecting strip  3  is coupled with bands  4  which, when tied to the user&#39;s neck, secure connecting strip  3  against falling. The terminals of the bipolar D_E, D_A, D_S, D_I electrodes and the breathing sensor  22  are connected to connector  5  secured on strap  2 , using releasable connectors. 
     Viewing  FIG. 1A , it may cause some confusion that, for the sole purpose of explanation, we show an outstretched representation of the electrode placement of  192  electrode arrangement, known in the art, in order to make placement of the electrodes D_E, D_A, D_S, D_I unambiguous, but in reality, electrodes D_E, D_A , D_S, D_I and the breathing sensor  22  are carried exclusively by strap  2 . 
     In  FIG. 1B , however, strap  6  is shown and applied; which, in itself, by its size and shape, enables the  192  electrode arrangement. Since it is in contact with the user&#39;s body on a larger surface, it is preferably perforated. On strap  6 , four unipolar  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  electrodes are fixed as well, in a way that each of electrodes  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  is located in the portion of strap  6  in contact with a distinct part of the user&#39;s body, and the arrangement includes a fifth CT central terminal, which acts as a central terminal. These parts are marked with dotted lines in  FIG. 1B , and the following parts can be distinguished: section  8  contacting the front surface of the user&#39;s body, sections  9  and  10  contacting the two side surfaces of the user, and sections  11  contacting the back of the user. Here as well, the terminals of  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  electrodes are connected to connector  5  secured on strap  6 , providing releasable connectors. 
     Not surprisingly for the skilled in the art, both strap  2  and strap  6  are provided with the coupling elements usual in this field, such as buckles and Velcro fasteners, which are not illustrated in the figures for clarity purposes and because of their obviousness. Straps  2  and  6  in the figures show the correct placement of electrodes D_E, D_A, D_S, D_I,  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4 . These can be mounted in a garment such as a compression t-shirt to ensure a more stable sensor-body surface contact. 
     An essential element of both presented electrode arrangements is that the positions of the electrodes D_E, D_A, D_S, D_I,  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  are not arbitrary but anatomically determined. User-dependent placement is determined by basic research results related to the equidistant layout used for  192  electrode body surface potential mapping, also known in the literature. For details, see e.g. the referenced work of Kozmann G. et al:  IEEE Trans Biomed Eng.  1991. November; 38(11):1061-8. [G. Kozmann et al:  IEEE Trans Biomed Eng.  November 1991; 38(11):1061-8]. 
     In order to realize the method of the invention, besides the breast strap  1  outlined in  FIGS. 1A and 1B , an evaluating electronics is needed, constituted by data processing unit  12  in the example shown, and also a display unit providing information to the user, preferably and in the example shown, a smartphone  13 . 
     In the embodiment of the present invention, the main functional units of the data processing unit  12  constructed as a separate lightweight unit, attached to connector  5  in a releasable way but without the risk of being lost, are shown in  FIGS. 2 and 3  representing the deviations justified by the type of electrode used. The data processing unit  12  is shown in  FIG. 2  and the unipolar  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  electrodes are connected via a weighted network built from resistors of the same R 1 -R 4  values to one of the inputs of an input amplifier stage  14  while the other input of the amplifier is connected to the CT terminal. Breathing sensor  22  is connected to an additional input amplifier stage  15 . The outputs of amplifier stages  14 ,  15  are connected to a multiplexer  16 , as usual. The output of the multiplexer  16  is connected to the input of analog-to-digital converter  17 , the latter being out-put to processor  18 , the data output of which is connected to Bluetooth stage  19  arranging the communication between the data processing unit  12  and smartphone  13 , providing wireless connection and communication with smartphone  13  in the known way. The latter one may be in contact with cloud services  20 , if required. 
     The energy supply of the data processing unit  12  is provided by power supply  21  as is customary in the art, which is connected to the individual stages via wired connections symbolically indicated in the diagrams. Power supply  21  is preferably an easily replaceable or rechargeable battery. 
     Processing and evaluation of the measured parameters is performed in the data processing unit  12 , which is controlled by smartphone  13 . In the latter, we do not carry out substantive processing, except for control, it is only used for displaying the results, instructions, and auxiliary data. For example, the geographic data of the training path is provided during the results communication using the smartphone  13 , when the smartphone  13  has positioning capability. It will be apparent to those skilled in the art that the processing can be carried out with any suitable device to which the received signals and data can be transmitted, also with the help of smartphone  13 , such as the cloud service  20 . 
     The data processing unit  12  shown in  FIG. 3  differs from that shown in  FIG. 2  in using Dower D_I, D_E, D_A, D_S electrodes as input sensors. These and the breathing sensor  22  connect to input amplifier stages  23 ,  24 ,  25 ,  26  of data processing unit  12 , and the outputs of the amplifier stages  23 ,  24 ,  25 ,  26  are connected to the inputs of the multiplexer  16 . With regard to the further design and operation details of the data processing unit  12  we refer to the description related to  FIG. 2 . 
     The smartphone  13 —or, for example, a smart watch fixed to the user&#39;s arm—provides voice and/or light signals to inform the user during training to control the training intensity, based on received heart rate feedback. 
     The chest strap  1  is located to anatomically fit the body size of the user. The medically permissible measuring points, i.e., the matrix of D_I, D_E, D_A, D_S electrode positions are assigned to the user&#39;s body so that the top row of the matrix, together with the top D_S electrode, contacts the user&#39;s body at the height of the user&#39;s collarbone while the lowest row of matrix, together with one or more of the lowest D_I, D_E, D_A electrodes, contact the user&#39;s body at the height of the user&#39;s navel. The distance between the lower and the upper rows of the matrix is divided equidistantly so that the positions of the D_I, D_E, D_A, D_S electrodes can be adjusted to any individual body size. 
     The sum of the signals of the CT central terminal needed for unipolar lead and those of the  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  electrodes connected via the weighted network built from the same R 1 -R 4  valued resistors results in zero potential under the Kirchhoff&#39;s Loop Rule. 
     The number of electrodes  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  in the figure is four, but it can be any further multiples of two. The implementation uses dome shaped, elastic conductive rubber contact surface used in the medical field, which provides good contact even with slightly convex and concave body curvature. The  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  electrodes are spaced so far from each other that muscle noise could be considered to be uncorrelated, thus providing a spatial noise filtering. 
     In the Dower arrangement, the strap  2  is designed so that it can be applied to both male and female body geometry, which is allowed by the fact that the connection between the cervical band  4  and the waist strap  2  is provided by connecting band  3  running along the collarbone insensitive to the body geometry. For the D_I, D_E, D_A, D_S electrodes formed from conductive rubber, the above remark applies in this case as well. 
     The method of the present invention is intended to monitor and evaluate the efficiency and to check the safety of a user&#39;s physical activity, in particular their sports activity, by sensing predefined parameters of the user&#39;s body using one or more sensors placed on the upper body of the user. In our method, the user is a person performing training who has the sensors temporarily fixed on his chest for the duration of the activity. The use of such sensors in our method includes the well-known D_I, D_E, D_A, D_S,  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  electrodes employed in the field of ECG testing, and devices capable of sensing other parameters such as breathing or ambient temperature, like the breathing sensor  22 . As common in such methods, the detected parameters are transmitted as electrical signals to the evaluating electronics, which means that the electrodes and sensors are connected with evaluating electronics, the latter being implemented in our method by the data processing unit  12 . Similarly to known prior art solutions, the parameters, i.e. the measured signals, are evaluated on the basis of predetermined criteria and the results of this evaluation are displayed visually, but the novelty of our procedure lies in the evaluation itself, illustrated in detail below. 
     The method of the invention essentially consists of three plus one phases, as shown in  FIGS. 4A and 4B , separated the phases by horizontal dashed lines. The plus one section is a so-called ESZ preparatory section whereby we will make available all the data we need to accomplish the activities needed to achieve the objective during the method. As such data, we consider the inputting of the user&#39;s medical history in a processable form, and inputting and recording of variations and protocols of subsequent trainings. 
     The first of the three main phases referred to is an NYSZ idle phase, which is a pre-exercise phase. In doing so, we determine, preferably measure, the HR 0  resting heart rate of the user and, using the measured data, we calculate the values of HR max  maximum heart rate that is allowable during training, and HR target  target heart rate to be achieved during exercise. We use the regression relationship, known from the literature, to estimate the VO2 max  parameter characterizing the load capacity, which indicates the maximum amount of oxygen absorbable and deliverable by the lungs. 
     In a subsequent TSZ load phase, besides the continuous monitoring and evaluation of the training target and parameters affecting the safety of the user performing the training, we control the running of the planned training program by means of a software program previously stored in the data processing unit  12 —which is not the subject of the invention, so it is not necessary to describe it in detail—automatically, or possibly controlled by smartphone  13 , as well as we ensure that the measured heart rate during the exercise does not exceed the value determined by the maximum stroke volume per cardiac cycle, a.k.a. stroke volume. At such a load, the heart rate does not increase even during a long training. 
     During an RSZ regeneration phase, following the TSZ load phase, the HRR1 and HRR2 heart rate parameters for one-minute and two-minute rest are determined as the HRR heart rate reserves one minute and two minutes after the completion of the TSZ load phase, i.e. the end of training. We determine the SDNN variation of successive ECG R-wavelengths sampled after the third minute of the RSZ regeneration phase; and the energy of power density spectrum in the low frequency band (LF: 0.04-0.15 Hz) and high frequency band (HF: 0.15-0.4 Hz), calculated using the Fourier transformation of the RSZ regeneration phase&#39;s tachogram; and the quotient of the two, the LF/HF parameter; and also sum up and record the events of the training. 
     During the method of the invention, we can intervene in the planned course of the trainings at three stages:
     a) In the case of both electrode arrangements presented, based on the measurement data of the NYSZ idle phase, we can suggest skipping or easing the planned daily workout, e.g. due to cardiac fatigue reflected in abnormal LF/HF values due to a previous grueling training, or if the frequency of ec-topic beats in the NYSZ idle phase is more than fifteen per minute or even due to abnormal “ventricular repolarization heterogeneity”.   b) In dangerous situations arising from the load during the TSZ load phase, like the detection of frequent ectopic beats, ischemic signs, hazard of sudden cardiac arrest (SCA), we can suggest the interruption of the load i.e. training, similarly to exercise ECG tests performed under medical supervision.   c) After the load, the heart rate assuagement section is monitored and then parameters of the heart rate variability in the time and frequency domains are calculated. We feedback the information obtained by this process for the evaluation of the first phase of the next training, when it is established that the elapsed time, such as last day&#39;s rest, was not sufficient to restore the reduced physiological value of LF/HF.   

     The novelty of the unipolar lead arrangement is that if the position of the electrodes  7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  corresponds to the figure shown, then the measured signal—in addition to indicating the heart rate and showing the more important time parameters of the ECG waves (PQ, QRS, QT), arrhythmia, with abnormal depression or elevation of ST 60  or point J for ischemia induced by the load, which is a negative or positive displacement from the resting value—shows this fact as well as its ventricular localization, that is, whether anterior or inferior, as shown in  FIG. 6 , where a waveform corresponding to an EÁ healthy state and a waveform of an KÁ abnormal state is illustrated, separated by a vertical dot line from each other. On the EÁ healthy state waveform, the locations of sections PQ, QRS, QT, ST and point J can be easily recognized, as in the case of KÁ abnormal state waveform the locations of point J, point ST 60  and in this case the position of the ST depression. 
     In the case of Dower&#39;s measurements, the approximate conversion of U AI , U EI , U SI  potential differences measured between the D_A and D_I, D_E and D_I, D_S and D_I electrodes to Frank&#39;s orthogonal X, Y, Z leads are done by the equations described in U.S. Pat. No. 4,850,370. The position of the electrodes E, A, S, I in the indexes, in relation to the 192 lead system, is shown in  FIG. 1  of the document. The transformation equations used in the present method: 
         X= 0.610  U   AI +0.171 U   EI    
         Y= 0.354  U   AI −1,000 U   SI  
 
         Z= 0.869 U AI −0.605 U   EI  
 
     Breathing frequency detection is optional, for example by the known inductive displacement sensor  22  breathing sensor. 
     In the ESZ preparatory section at the beginning of the example procedure we will set the employed measurement protocol and, based on the age and medical history data entered, determine the value of personalized maximum allowable heart rate HR max , using the following formula 
       HR max =220−age(in years)
 
     then we use the Karvonen formula to calculate the target heart rate of HR target , aimed to be reached and maintained during training: 
       HR=((HR max −HR 0 )×intensity %)+HR 0 ),
 
     where HR 0  is the resting heart rate. 
     The determination of the intensity % value in the formula is started by dividing the HR o  and HR max  domains into ten sections. Then, using the heart rate control system, at constant load we strive to keep the heart rate in the center of the selected sub-domain at the value “intensity %”. 
     The HR target  heart rate to be achieved during training is dependent on the user&#39;s fitness level, and therefore needs to be checked from time to time and modified if necessary. 
       FIG. 4  illustrates a preferred implementation of the method of the invention as a flowchart. 
     ESZ Preparatory Section 
     If available, history data is entered in step  31 , and the customized training protocol is used in step  32  to set the phases of resting, i.e. status assessment, load and regeneration; and the warm up, load and reduction protocols, etc. At the load protocol it also has the option of setting impulse loads. The implementation of this will be ensured by the regulation outlined below. 
     After performing the above once, we will move to the actual phases in step  33 . 
     NYSZ Idle Phase 
     In step  34 , we perform resting measurements, data collection and evaluation, the duration of which is defined as an input parameter within the training protocol. During this, we performed an arrhythmic examination per minute for the determination of atrial fibrillation and frequent (&gt;15/min) ventricular extra beats. The atrial fibrillation test is based on the Poincare diagram of the distances between the RR(i) and RR(i-1) consecutive beats as x and y coordinates according to the method described in the article of Tuboly és mtsi: IME, XVIévf. 6.sz. 46-49 o. [Tuboly et al: IME, Vol. 16, No. 6, Pp. 46-49]. At the end of the one-minute period, the averaged cycle with the relevant key ECG wave parameters (PQ, QRS, QT) is determined and displayed, and the relative change of the median HR 0  resting heart rate and the time domain value of CV of the heart rate variability (HRV) is calculated according to this formula: 
         CV=SD/M× 100% 
     where SD is the standard deviation, M is the mean value. 
     The medical judgment of the physiological degree of heart rate variability (HRV) fluctuation is based on the results of Baron and Ewing, see Baron and Ewing In: Recommendation for the Practice of Clinical Neurophysiology, Ch: 7, 1999, Elsevier Science B.V. 
     If the HRV data is significantly lower than the age-appropriate value, according to the statistical F-test, a medical/sports doctor&#39;s check is recommended by means of a message on the smartphone  13 , for example. 
     Then, we estimate the VO2 max  parameter, i.e. the maximum oxygen absorption capacity of the lung, according to, for example, the method of Schneider J: Lung. 2013 October; 191(5): 449-58, using the following regression equations without actual spirometry measurement. 
         VO 2 max : Men=−28×age(in years)+4,000(ml/min);
 
       Women=−20×age(in years)+2,700(ml/min);
 
     or by weight unit: 
         VO 2 max /kg: Men=−0.42×age(in years)+58ml/min/kg;
 
       Women=−0.35×age(in years)+46(ml/min/kg)
 
     The load capacity, that is, the feasibility of the training is determined on the basis of the above data in step  35  for which a “yes” or “no” answer is possible. In case of “yes”, the TSZ load phase is started in step  36 . In case of “no” decision, the process is interrupted and the factor preventing the load is either corrected in step  37 , or a message is displayed on smartphone  13  to the user in step  38 , to let them know about it. Data obtained or determined in the NYSZ idle phase will be included later in a summary when communicating the result of the training session. 
     TSZ Load Phase 
     The load phase is automatically triggered in this example after the end of the NYSZ idle phase if no protection/ban condition, e.g. an alert on the display of smartphone  13 , were generated there. If so, human decision is needed, this is done in step  37 . 
     If the examination of the data collected during the execution of the load, i.e. during the training session, determines in step  39  that the employed ECG amplifier remains in the linear range, i.e. there is no overload, and the noise level does not exceed the predetermined rate either, in step  40  we perform the substantive processing of the data recorded during training. Otherwise, we do not execute the processing, but in step  41  we give an alert, perform the detection and elimination of the cause of the overload or noise, and resume data collection. 
     In the load section, in this example, a sliding average evaluation is performed. The operations are carried out directly on the signals obtained in the case of a single-lead unipolar electrode arrangement, and in the case of the Dower&#39;s electrode arrangement with the three bipolar leads, we also carry out on one lead by means of the Frank&#39;s X-lead signal derived by the regression formula previously described. 
     An explanation of this is that if the subject undergoes ischemia due to the load, changes in the ECG ST section appear in 90% of the cases in the X lead, and 10% in the Y lead, such as known from Chou T, Knilans T. K: Electrocardiography in Clinical Practice, 4th Ed. Ch.10. Saunders Comp., Philadelphia, 1996. 
     During data processing, the signal-to-noise ratio of the signals is corrected by the linear baseline correction of the ECG QRS complex fiducial (reference point), i.e. the linear baseline correction based on the points determined by the steepest gradient point of the QRS, see  FIG. 5 . The figure shows the ECG signal  50  and the linear base line  51  generated therefrom. Baseline noise is random in nature, much of which can be eliminated by so-called synchronized averaging, which can be done with respect to the “fiducial” i.e. reference point. Following baseline correction, the diagnostically important QT sections of consecutive cardiac cycles are standardized, in this case with the Bazett formula, with respect to RR distances: 
         QT   c   =QT   m /√( RR ),
 
     prior to the formation of a median or major median cardiac cycle characterizing a one-minute period. “Major cardiac cycles” are then determined by a clustering method based on a known correlation method, followed by the derivation of normalized and “fiducial” i.e. reference point synchronized majority cardiac cycles with time averaging or median formation. It should be noted that the relevant literature suggests more precise methods for normalization than the Bazett formula, any of which can be used in our method. For example, Malik M et al. “Heart”, 2002 March; 87 (3):220-8. 
     The averaged, time-parameterized ECG curves are stored, followed by the determination, based on the amplitude of point J and ST 60  of the ECG, in step  42 —during the load process—whether significant elevation or depression, associated with dangerous ischemia, is detected—see  FIG. 6 —, in which case a stoppage based on the hazard analysis will be determined. As a decision thresh-old, 100 mV is taken in the present example. 
     In step  43 , an alert is issued if, over the analyzed one-minute period, more than 15% of detected cardiac cycles are in a cluster with form characteristics other than the major cardiac cycle, while the resulting minority cluster has a large form similarity with a correlation coefficient of &gt;0.8. This implies to frequent, same-focused ectopic beats. 
     During the hazard analysis, the QT section&#39;s integral of the majority cycles is calculated per minute. If the QT section&#39;s integral&gt;threshold K1, the probability of occurrence of VT/VF is considered to be minimal, which is indicated to the user by the color green in this example. If the K2&lt;QT segment&#39;s integral&lt;K1, the chance of VT/VF has moderately increased, this is indicated to the user by the color yellow, and if the QT segment&#39;s integral&lt;K1, the chance of VT/VF has significantly increased, and that will be signaled to the user by, for example, color red, as a call for stop. Other considerations and details directly related to this can be found in Kozmann Gy és mtsi: “Kardiovaszkuláris rizikótényezők okostelefonos vizsgálata”, IME: 15. évf. 4. sz., 42-46. [Gy. Kozmann et al: “ Smartphone examination of cardiovascular risk factors, ” IME: Vol. 15, No. 4, pp. 42-46.] 
     During the load phase, thanks to real-time monitoring, a signal is shown when the heart rate has reached, in the analyzed one-minute range, the—HR target  target heart rate value set on the basis of the resting measurement. For the pace modification required to achieve a dynamic load protocol, in the case of predetermined too low/too high heart rate, when in step  44  it is determined that, after reaching the −HR target  target heart rate value; at continuous physical load, the heart rate is continuously increasing (drift); therefore, it exceeds the upper limit of the selected range, in step  45  the user is instructed by visual and/or acoustic indications to reduce the intensity of their motion, i.e. a so-called f max  control is performed. Conversely, if the heart rate falls below the lower limit of the selected range, we can initiate an increase in performance. With such control, we can ensure that the user performs their training with optimal stroke volume. Executing the instruction is the user&#39;s responsibility. 
     The load, i.e., the training is completed in step  46  at the end of the predetermined period of time, in accordance with the protocol. 
     RSZ Regeneration Phase 
     Following the TSZ loading phase, the measurements of the RSZ regeneration phase are performed in step  47 . After one and two minutes, the HRR1 and HRR2 heart rate decrease parameters are calculated. With the help of available medical knowledge, based on the summarized results of the training, the value of HRR is evaluated from a medical point of view. In an abnormal case, when the heart rate reduction is slow, the value of the parameter may indicate heart failure. 
     After the third minute, an arrhythmia test is performed in every minute as in the idle phase. At the end of the RSZ regeneration phase, the length of which is also considered as an input parameter, the averaged cycle and the associated waveform parameters are determined for the RSZ regeneration phase, along with the heart rate variability. The result obtained can be compared next time, for example, the next day, to the resting measurement of that time and can be used to signal cardiac fatigue, and, on the basis of this, to ease the training that day or even instruct the user to abandon it. As with the arrhythmic examination, during the averaging and heart rate variability calculation, the first three minutes of the RSZ regeneration phase are ignored. 
     After that, the measurement is aggregated in step  48 . For this, we use the GPS data for positioning, if available, and the result is displayed on the smartphone  13 . 
     To enable a retrospective analysis of the whole heart rate record, i.e. recorded in NYSZ idle phase, TSZ load phase and RSZ regeneration phase, the averaged signal sections and, if breathing sensor  22  is used, their associated cardiac and respiratory frequencies are also stored. 
     In the case of regular exercise, we can edit trend curves from the results that indicate an increase in the stroke volume. The referenced trend curves characterize the improvement of the VO2max value associated with the optimum stroke volume by the following Schneider&#39;s correlations. Using Schneider&#39;s regression correlation, the value of VO2 max /HR corresponding to the target HR accomplished during the training is: 
       Men=−0.10×age(in years)+20.50ml/min/heart rate;
 
       Women=−0.05×age(in years)+13(ml/min/heart rate).
 
     The above results are included in the measurement summary. 
     After the aggregation, we display the measurement
     protocol graphically,   the HR 0  characteristic of the resting state, the HR max  and HR target  values calculated from the age and the HR 0 , the HRV, i.e., heart rate variability parameters in time and frequency domains, estimated resting state VO2max parameters in binary, good/non-good categories,   the representative load signal sections of the current measurement, such as the HR (t) time function and the change in the ECG (t) waveforms as a function of time, the evaluation of the results obtained in binary, good/non-good categories,   the HRR1 and HRR2 heart rate parameters of the RSZ regeneration section, and HRV, i.e. heart rate variability parameters, after the third minute of resting time, in the time and frequency domains, the VO2max estimate after load and the evaluation of the results obtained in binary, good/non-good categories,   if the exercise included running, the identification of the track based on GPS data service, if available,   trends and conclusions based on previous measurements characterizing health and fitness status, if available.   

     Data can be sent in conveniently compressed and securely encrypted form to the database of a cloud storage service  20  to document the health status, which can contribute to reviewing long-term results. 
     LIST OF REFERENCE SYMBOLS 
       1  chest strap
 
 2  strap
 
D_I, D_E, D_A, D_S electrode
 
 3  connecting strip
 
 4  band
 
 5  connector
 
 6  strap
 
 7 _ 1 ,  7 _ 2 ,  7 _ 3 ,  7 _ 4  electrode
 
 8 ,  9 ,  10 ,  11  section
 
 12  data processing unit
 
 13  smartphone
 
 14 ,  15  amplifier stage
 
 16  multiplexer
 
 17  analog-to-digital converter
 
 18  processor
 
 19  Bluetooth stage
 
 20  cloud service
 
 21  power supply
 
 22  breathing sensor
 
 23 ,  24 ,  25 ,  26  amplifier stage
 
R 1 , R 2 , R 3 , R 4  resistor
 
 31 - 48  step
 
CT central terminal
 
ESZ preparatory section
 
NYSZ idle phase
 
TSZ load phase
 
RSZ regeneration phase
 
RR distance
 
 50  ECG signal
 
 51  linear baseline
 
EA healthy state
 
KA abnormal state
 
PQ section
 
QRS section
 
QT section
 
ST section
 
J point
 
ST 60  point