WO2012119665A1

WO2012119665A1 - Method and device for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals

Info

Publication number: WO2012119665A1
Application number: PCT/EP2011/059905
Authority: WO
Inventors: Kalju Meigas; Mart-Rein ROSMANN; Jaanus Lass; Jüri KAIK; Kristjan PILT; Denis KARAI; Indrek RAIG; Avo TÖLPT
Original assignee: Tensiotrace Oü; Tallinn University Of Technology
Priority date: 2011-03-09
Filing date: 2011-06-15
Publication date: 2012-09-13
Also published as: EE05619B1; EE201100016A

Abstract

Method and device for long-term variability monitoring of cardiovascular parameters based on registered electrocardiogram (ECG) and pulse wave signals provide digitalization of a patient's ECG and pulse wave signal, followed by registration of R-peaks of ECG signal and basing on these also formation of NN series, pulse wave raising front detection with delay time calculation and basing thereupon also formation of delay time NN series, QT interval calculation and basing thereupon also formation of QT interval NN series which are followed by time and frequency variability analysis of all the formed NN series and in pairs by time and frequency variability correlation analysis.

Description

Method and device for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals

Technical Field

Present invention relates to the field of medical technology and concerns a method and a device for implementing long-term (from a couple of hours to some days) ambulatory monitoring of a patient's cardiovascular parameters while performing his everyday activities. The survey is based on registered electrocardiogram (ECG) and on peripheral pulse wave signals, followed by variability analysis of the cardiovascular parameters.

Background Art

From prior art a method for long-term ambulatory ECG registering and a method for subsequent variability analysis and equipment for implementing the same - Holter™ ECG monitoring equipment is known. This method is limited to the analysis of cardiac rhythms based on cardiac electrical signals registered on the body surface. In those devices signal registering and signal analysis are typically separated. Registration of signals takes place in a portable device, which stores signals onto the memory card, and those records are later analysed on a computer using suitable software. This method is limited to the variability analysis of ECG signals and does not allow broader analysis of the cardiovascular parameters to take into account the condition of the circulatory system. The disadvantage of these devices being that in most cases recording and analysis of signals are carried out in different devices, which does not allow operational analysis of the results obtained, at the same time, however, solutions are known in which either ECG or pulse wave measurement and analysis are physically realized in the same device.

For example, a device and a method for measuring variability of cardiovascular parameters (US5862805) is known. This device registers pulse wave signals at two certain measuring points, analyzes the period variability and frequency specters and performs correlation analysis of the results of the analyses carried out at both measuring points. Disadvantage of the device and method is that measurement and analysis of ECG signal do not include parameters calculated on the ECG signal characterizing functioning of the heart, therefore in this solution the analysis does not allow to comprise the whole cardiovascular system and therefore the heart rhythm analysis is inaccurate.

A fairly similar solution to the one described above is disclosed in patent US7001337, which enables on the basis of the registered pulse wave to analyze the variability of heart rhythms and of the blood flow. But in this solution ECG signals are not used either, which would allow more accurate registration of the variability of heart rhythms.

In the published United States patent application US2006/0287605A1, ECG recording and analysis is integrated into a single unit and analytical processes are realized in a digital signal processing module. The device includes time and frequency analyses of the cardiac rhythm variability. The disadvantage of the device is that it lacks the pulse wave signal sensor, therefore non-use of pulse wave signals does not allow to obtain complex cardiovascular analysis.

Method and device (WO2010/037056A1) enabling to derive the blood pressure values on the basis of the pulse wave time delays in relation to the R-peaks of the ECG signal and pulse frequency. Metrologically it is difficult to prove the accuracy of rapid changes in blood pressure values (for comparison a calibrated pressure transducer would have to be introduced into the blood vessel, which is practically impossible in case patient is on the move). In this solution the blood pressure values are obtained in a manner, where the results might not be reliable enough for diagnostic purposes.

Device (EE00720U1), where a pulse wave sensor is added to the ECG monitoring device from Holter™ is also known. The analog output of the pulse wave sensor is connected to the free input of the ECG signal recorder. This allows synchronous registering of ECG and peripheral pulse wave signals for further processing and analysis and both of those signals are stored on a memory card in the Holter monitoring device. The disadvantage of that device is that it is limited only to the synchronous registering of the digital signals, and does not allow co-analysis (jointly analyses) of the ECG and pulse wave signals, which would give substantially more information about the condition of the patient's cardiovascular system.

None of the known methods and devices makes it possible to use one device for ambulatory registering of ECG and peripheral pulse wave signals and at the same time on the basis of these signals to simultaneously analyse the time and frequency variability of the cardiovascular system (heart and blood circulation) parameters and correlation between them, to evaluate dynamic changes in the blood pressure on the basis of the pulse wave time delay and if necessary, to promptly forward the results of the analysis. The realtime co-analysis of the ECG and peripheral pulse wave signals would give better chances for to developing new diagnostic methods of cardiovascular disorders.

Summary of invention

Consequently the first object of the invention is to provide a method and a device enabling long-term (from a few hours to some days) synchronous registering of ECG and peripheral pulse wave signals derived from the patient by not taking him away from everyday activities and enabling to use those signals in the same device for performing variability and correlation analysis of the cardiovascular parameters.

The second aim of the invention is to enable in the device to evaluate and to display the dynamics of the blood pressure changes based on the correlation between the changes of the pulse wave delay in relation to the ECG signal.

Set aims are achieved by a method for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals, comprising the following steps:

registering and recording of electrocardiogram (ECG) and the pulse wave signals;
registering R-wave peaks of ECG signal and the moments of the raising fronts of the pulse wave signals;
calculating RR-intervals from the moments of the R-wave peaks of ECG signals;
forming a sequence of NN-intervals of the ECG signal from the RR-intervals of the ECG-signal;
performing variability analysis of the length of heartbeat periods from the sequence of NN intervals of the ECG signal;
performing a variability analysis of the frequency of heart beats from the sequence of NN intervals of the ECG signal.

The calculation of the time delays of the pulse wave on the basis of the registered R-wave peaks of the ECG signal and moments of the raising fronts of the pulse wave signal is supplemented by the following steps:

forming a sequence of the NN-interval time delays on the basis of the sequence of NN-intervals of the ECG-signal and time delays of the pulse wave;
performing frequency and period variability analysis of the pulse wave time delays on the basis of the sequence of NN intervals of the time delays of the pulse wave;
calculating QT intervals on the basis of the recorded ECG-signals and registered R-wave peaks thereof;
forming a NN sequence of the QT intervals on the basis of the calculated QT intervals and a sequence of the NN intervals of the ECG-signal;
performing frequency and period variability analyses of the QT intervals on the basis of the NN sequence of the QT intervals;
subjecting the results of the heartbeat period variability analysis and the results of the pulse wave time variability analysis to correlation analysis;
subjecting the results of the heartbeat frequency variability analysis and the results of the pulse wave time delay frequency analysis to correlation analysis;
subjecting the results of the heartbeat period variability analysis and the results of the QT intervals period variability analysis to correlation analysis;
subjecting the results of the heartbeat frequency variability analysis and the results of frequency variability analysis of the QT intervals to correlation analysis.

ECG and pulse wave signals are recorded continuously throughout the whole monitoring cycle.

The analyses are performed repeatedly and periodically throughout the monitoring cycle on the basis of the continuously recorded ECG and pulse wave signals.

Periodical analyses are performed on the basis of all the all ECG and pulse wave signals recorded by the time of the analysis.

The method is implemented by the device for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals, whereas said device comprises a set of ECG electrodes, a ECG signal amplifier and an analog-to-digital converter, a memory device for recording signals derived from the patient, a module for registering of the moments of the R-peaks, a module for calculating RR intervals, a module for forming a sequence of the NN intervals, a module for heartbeat period variability analysis, a module for heartbeat frequency variability analysis and a control module.

As a novelty said device comprises a pulse wave sensor, a pulse wave signal amplifier and an analog-to-digital converter, a module for registering Q and T time moments, and for calculating QT intervals and for forming a NN sequence, a module for period variability analysis of the QT intervals, a module for frequency variability analysis of the QT intervals, a module for registering moments of the raising fronts of the pulse wave, a module for calculating a time delay of the pulse wave, a module for forming a NN sequence of the pulse wave time delays, a module for time delay period variability analysis on the basis of the NN interval sequence of the pulse wave, a module for frequency variability analysis on the basis of the NN interval sequence of the pulse wave and a module for correlation analysis.

The output of the set of ECG electrodes is connected to the input of the amplifier and analog-to-digital converter of the ECG signals, the output of the latter is connected to one of the inputs of the memory device for the signals recorded from the patient, where one output of the latter is connected to the input of the module for registering the moments of the R-peaks and the second output thereof is connected bi-directionally to the control module.

One output of the module for registering the moments of the R-peaks is connected to the input of the module for calculating RR intervals, the output of the latter is connected to the input of the module for forming a sequence of the NN intervals, the output of the latter is connected to the inputs of the module for heartbeat period variability analysis and to the module for heartbeat frequency variability analysis and the outputs of said modules are connected bi-directionally to the control module.

The output of the pulse wave sensor is connected to the input of the amplifier and the analog-to-digital converter of the pulse wave signals, the output of the latter is connected to the second input of the memory device for the signals recorded from the patient.

The third output of said memory device is connected to the input of the module for registering the moments of the raising fronts of the pulse wave, the output of that module is connected to the module for calculating a time delay of the pulse wave, and the second input of said module is connected to a third output of the module for registering the moments of the R-peaks.

The output of the module for calculating the time delay of the pulse wave is connected to an input of the module for forming a NN sequence of the pulse wave time delays.

The second input of the module for forming a NN sequence of the pulse wave time delays is connected to the output of the module for forming a sequence of the NN intervals, the output of the module for forming of NN sequence of the pulse wave time delays is connected to the input of the module for period variability analysis of the pulse wave time delays and to the input of the module for frequency variability analysis of the pulse wave time delays, and outputs of those modules are connected bi-directionally to the control module and the control module is connected bi-directionally to the correlation analysis module.

The output of the memory device for storing the signals recorded from the patient is connected to the input of the module for registering Q and T time moments, for calculating QT intervals and for forming a NN sequence and the second input of said module is connected to the output of the module for registering time moments of the R-peaks.

The output of the module for calculating QT intervals and for forming a NN sequence is connected to the inputs of the modules for period variability analysis of the QT intervals and for frequency variability analysis of the QT intervals, and outputs of those two modules are connected bi-directionally to the control module.

Brief description of drawings

For better understanding of the subject of the invention the specification includes the following drawings, where:
Figure 1 shows a flow chart of the method according to the present invention;
Figure 2 shows ECG and pulse wave diagrams and measured parameters;
Figure 3 shows a block diagram of the device according to the invention;
Figure 4 shows a block diagram according to Figure 3, including additional modules, which enable presentation of the dynamics of the blood pressure in correlation with the time delay of the pulse wave in relation to the ECG signal.

Description of embodiments

The method according to the present invention, represented by the block diagram on Figure 1, is carried out as follows.

Using electrodes fixed to the patient, the ECG signals are registered and amplified using analogue technology to the suitable level for digitalization. Pulse wave signals are registered by the sensor and these signals are amplified using analogue technology to the suitable level for digitalization. Thereafter the ECG and pulse wave signals are transformed to digital and recorded for further processing.

Hereinafter the data processing is explained with references to Figure 2 showing both the ECG and pulse wave signals. On the ECG time diagram there is indicated a QRS complex comprising the Q-wave in the beginning, R-peak in the middle and S-wave in the end, as well as T-wave, P-wave, RR interval and QT interval.

In practice the moments of the R-peaks are registered according to the raising front of said peaks on the level slightly below the peak apex (for example on the level of 90% of the height of the peak apex).

RR interval is a period from the measuring point on the raising front of the R-peak to the next similar point on the next R-peak.

QT interval is a period from the beginning of the Q wave to the end of the T wave. In practice the beginning of the Q wave and the end of the T wave are registered at the lower lever of the heights of those waves (for example at the level of 10%).

On the time diagram of the pulse wave there is shown the moment for registering the raising front of the wave, required for subsequent analysis. Due to a sharp rise of the raising front, it is convenient to register the moment, which corresponds approximately to 1/2 of the amplitude of the pulse wave, but other spots can also be used for registering.

The time delay of the pulse wave (PWTD) is a period from the moment of the R-wave peak of the ECG signal to the subsequent moment of the raising front of the pulse wave.

The processing and analyzing of the recorded signals takes place as follows.

As described above, the moments of the R-peaks are registered in the ECG signal. As described above, the moments of the raising fronts are registered in the pulse wave signal. The time values of the duration of the RR intervals are calculated in accordance with the R-peaks. Regular intervals (related to the sine rhythm) are maintained from the registered RR intervals and irregular intervals are eliminated. The so-called normal intervals between packages retained are indicated as NN intervals – the sequence of the NN intervals of the ECG signal is formed.

On the basis of the sequence of the NN intervals of the ECG signal variability analysis of the heartbeat periods (Time Domain HRV) is performed, as a result of which the main parameters are obtained:

The standard deviation of NN intervals (SDNN). It is usually calculated over the period of 24 hours.
The square root of the mean squared difference of the successive NN intervals (RMSSD).
The histogram of the NN intervals (TINN – NN interval histogram).
The number of pairs of successive NN intervals is determined that differ by more than 50 ms (NN50).

On the basis of the sequence of the NN intervals of the ECG signal frequency variability analysis of the heartbeats is performed (Frequency Domain HRV). The spectral power density is derived from the analysis, reflecting the distribution of signal power on the scale of frequencies. For the derivation of the power spectral density mainly discrete Fourier transformation is used. The main parameters of the heartbeat frequency variability analysis are:

Total power (TP).
High-frequency power 0.15 – 0.4 Hz (HFP).
Low-frequency power 0.04 – 0.15 Hz (LFP).
Very low-frequency power below 0.04 Hz (VLF).

The above described registering of the ECG signals and heartbeat analysis based on those signals are known and widely used. However in the present invention the following additional analyses are performed.

On the basis of the moments of R-peaks and moments of the raising fronts of the pulse wave the time delays of the pulse wave (PWTD) are calculated. Then for each NN interval of the ECG signal pulse wave time delays are selected. It means that from the calculated PWTD-s for each R-peak the PWTD-s corresponding to the NN sequence of the ECG signal are maintained. The rest of the PWTD-s are eliminated.

On the basis of the obtained NN sequence of the pulse wave time delays, pulse wave time delay variability analysis is performed similarly to the analysis of the sequence of the NN intervals of the ECG signal. The following parameters are obtained:

The standard deviation (SDNN - the standard deviation of NN time delays). It is calculated on the basis of the whole recorded signal.
The square root of the mean squared difference of successive time delays (RMSSD - the square root of the mean squared difference of successive NN time delays).
Time delay histogram (TINN - NN (time delay) interval histogram).
The number of pairs of the successive time delays that differ more than by x ms (NNx – the number of pairs of successive NN(time delay)-s that differ more than by x ms.

The period variability analysis of the pulse wave time delays on the basis of the NN sequence reflects new data about the changes in the bloodstream (stiffness of the blood vessels, blood pressure). Mapping of the data derived from different patients with different functional conditions enables to use the data in future for the diagnosis of the cardiovascular system.

Further comparison of the period variability parameters obtained on the basis of the NN sequence of the ECG signal with the synchronous pulse wave time delay variability parameters pairwise enables registration of the whole functioning of the cardiovascular (heart and circulatory) system of different patients in different situations. The correlation analysis of the pairs of those parameters enables to elicit the corresponding numerical indicators. Mapping of those parameters derived from the patients having different disorders and also mapping of said parameters derived from healthy persons having different functional conditions enables further to use these numerical indicators for diagnostic purposes.

On the basis of obtained NN sequence of the pulse wave time delays also the frequency variability analysis of the pulse wave time delays performed similarly to the frequency variability analysis of the sequence of the NN intervals of the ECG signal, resulting in the following main parameters:

Total power (TP).
High-frequency power (HFP).
Low-frequency power (LFP).
Very low-frequency power (VLF).

The frequency variability analysis based on the time delays NN sequence of the pulse wave reflects new data concerning the changes taking place in the blood circulation (stiffness of the blood vessels, blood pressure). Mapping of the data derived from the patients having different functional conditions enables to use the data for diagnosis of the cardiovascular system.

Further comparison of the parameters obtained from the heartbeat frequency variability analysis on the basis of the NN sequence of the ECG signal with the similar parameters of the synchronous pulse wave time delay variability pairwise enables registration of the whole functioning of the cardiovascular (heart and circulatory) system of different patients in different situations. The correlation analysis of the pairs of those parameters enables to elicit the corresponding numerical indicators. Mapping of those parameters derived from the patients having different disorders and also mapping of said parameters derived from healthy persons having different functional conditions enables the use of those numerical indicators for diagnostic purposes.

The Q and T moments are registered according to the R-peaks of the ECG signal in the close vicinity of the R-peaks and time periods - the QT intervals - between the Q and T are calculated. From the calculated QT intervals irregular QT intervals are eliminated, from the retained QT intervals for subsequent analysis only those intervals are maintained, which are synchronous with the NN intervals of the whole ECG signal. This selection gives the NN sequence of the QT intervals.

On the basis of the NN sequence of the QT intervals period variability analysis of the QT intervals is performed similarly to the analysis of the NN sequence of the ECG and pulse wave signal, resulting in the following main parameters:

Standard deviation (SDNN - the standard deviation of NN time delays). It is calculated on the basis of the whole recorded signal.
The square root of the mean squared values (RMSSD – the square root of the mean squared difference of successive NN time delays).
Deviation histogram (TINN – NN(time delay) interval histogram).
The number of pairs of successive intervals that differ more than y ms (NNy – the number of pairs of successive NN(time delay)-s that differ more than y ms).

The period variability analysis of the QT intervals gives new data concerning heart functioning of the patients having different functional conditions in the course of their taking different exercises. Mapping of the data enables to seek new approaches to the diagnosis of the cardiovascular diseases.

Further comparison of the parameters obtained by the period variability analysis of the sequence of the NN intervals of the ECG signal with the similar synchronous parameters of the period variability analysis of the QT NN intervals pairwise enables more deep registering of heartbeat functioning in comparison with the analysis based only on the sequence of the NN intervals of the ECG signal and therefore additional information of the heart functioning is derived from different patients under different circumstances. The correlation analysis between pairs of those parameters enables to elicit the corresponding numerical indicators. Mapping of those parameters derived from patients having different disorders and also mapping of said parameters derived from healthy persons having different functional conditions enables further to use these numerical indicators for diagnostic purposes.

On the basis of the NN sequence of the QT intervals frequency variability analysis of the QT NN intervals is also performed similarly to the NN sequence of the ECG and pulse wave signals, resulting in the following main parameters:

Total power TP).
High-frequency power (HFP).
Low-frequency power (LFP).
Very low-frequency power (VLF).

The frequency variability analysis of the NN sequence of the QT intervals gives new data concerning heart functioning of the patients having different functional conditions while taking different exercises. Mapping of the data enables to seek new approaches to the diagnosis of the cardiovascular diseases.

Further comparison of the parameters obtained by the frequency variability analysis of the sequence of the NN intervals of the ECG signal with the similar synchronous parameters of the frequency variability analysis of the QT NN intervals pairways enables more deep registering of heartbeat functioning in comparison with the analysis based only on the NN interval sequence of the ECG signal and therefore additional information of heart functioning of different patients under different circumstances is derived. The correlation analysis of the pairs of those parameters enables to elicit the corresponding numerical indicators. Mapping of those parameters derived from the patients having different disorders and also mapping of said parameters derived from healthy persons having different functional conditions enables to use of those numerical indicators for diagnostic purposes.

To sum up the above it can be stated, that the known method of the period and frequency variability analysis on the basis of the ECG signal is amended by:

Registering pulse wave signals (synchronously with ECG signals).
Calculating pulse wave time delays in relation to the R-peaks of the ECG signal.
Performing period and frequency variability analysis of the pulse wave time delays.
Calculating QT intervals of the ECG signal.
Performing period and frequency variability analysis of the QT intervals.
Correlation analysis by pairs of parameters is carried out between the period variability parameters of heartbeats, the period variability parameters of the pulse wave time delays and the period variability parameters of the QT intervals.
Correlation analysis by pairs of parameters is carried out between the frequency variability parameters of the heartbeats, the frequency variability parameters of the pulse wave time delays and the frequency variability parameters of the QT intervals.

Consequently the presented method enables through the analysis of the parameters and through the correlation analysis between said parameters to reflect functioning of the whole cardiovascular system. Mapping of those output indicators and associating them with different symptoms enables to create new and specify known methods of the diagnostics of the cardiovascular disorders.

The method according to the present invention is carried out by means of the device, the block diagram of which is shown on Figure 3. The device comprises a set of ECG electrodes 1 having their output connected to the input of the amplifier and an analog-to-digital converter 3 of the ECG signals, also a pulse wave sensor 2 having its output connected to the input of the amplifier and an analog-to-digital converter 4 of the pulse wave signals, the outputs of the analog-to-digital converters are correspondingly connected to the first and second input of a memory device 5 for recording signals derived from a patient, one output of the memory device 5 is bi-directionally connected to the input of the control module 17 and the second output is connected to an input of the module 6 for registering the Q and T moments, for calculating QT intervals and for forming a NN sequence, and to the input of module 7 for registering the moments of the R-peaks of the ECG signal, the third output is connected to an input of module 14 for registering moments of the raising fronts of the pulse wave signals. The output of module 14 is connected to an input of module 15 for calculating time delays of the pulse wave (PWTD), the second input of module 15 is connected to an output of module 7 for registering the moments of the R- peaks of the ECG signal and the output of module 15 is connected to an input of module 16 for forming a NN sequence of the pulse wave time delays.

An output of module 7 for registering moments of the R-peaks of the ECG signal is connected to a second input of module 6 for registering Q and T moments, for calculating QT intervals and for forming a NN sequence and the other output of 7 is connected to the input of module 8 for calculating RR intervals of an ECG signal and the output of module 8 is connected to the input of module 9 for forming a NN interval sequence of the ECG signal. The output of module 9 is connected to the second input of module 16 for forming a NN sequence of the time delays of the pulse wave, and it is also connected to the input of module 12 for the period variability analysis of the heartbeat periods and to the input of module 13 for frequency variability analysis of the heartbeats and the outputs of said

modules

12 and 13 are connected bi-directionally to control module 17. The output of module 6 for registering Q and T moments, for calculating QT intervals and for forming a NN sequence is connected accordingly to the input of module 10 for period variability analysis of the QT intervals and to the input of module 11 for frequency variability analysis of the QT intervals, and the outputs of

modules

10 and 11 are connected bi-directionally to control module 17.

The output of module 16 for forming a NN sequence of the time delays of the pulse wave is connected to the input of module 18 for period variability analysis of the time delays of pulse wave on the basis of NN intervals sequence and to the input of the module 19 for frequency variability analysis of the time delays of pulse wave on the basis of NN intervals sequence and the outputs of said modules are connected bi-directionally to control module 17, which is also connected bi-directionally to correlation analysis module 20. A control program (algorithm) is saved in control module 17 for autonomous operation of the device, when the ECG signal and pulse wave sensors are fixed to a patient, control module 17 comprises also a memory for recording intermediate results of the analyses, for example the results of the heartbeat frequency variability analysis, the results of the frequency variability analysis of the QT intervals, etc., for recording the data for the correlation analyses and for recording the final results of the correlation analyses of correlation analysis module 20.

Control module 17 is connectable to peripheral devices, for example to external control device 21 (such as keyboard) for data inquiries from the memory of control module 17, but also for adjusting the operation of the autonomous operation program of control module 17 when necessary, for example for changing time periods for executing the correlation analyses in correlation analysis unit 20. A display 22 can also be connected to control module 17, and when necessary, also external (storage) memory 23 can be connected to control module 17 for archiving and processing data stored in the memory of control module 17, but also for entering data in control module 17 or for transferring it to some other device.

Figure 4 shows an embodiment of the device comprising additionally module 24 for recording blood pressure readings, module 25 for calculating reciprocal value of the pulse wave time delays (PWTD) and module 26 for transforming reciprocal values of the pulse wave delays (PWTD) into blood pressure units. The input of module 25 for calculating reciprocal values of the pulse wave time delays (PWTD) is connected to the second output of module 15 for calculating the pulse wave time delays (PWTD), the output of module 25 for calculating reciprocal values of the pulse wave delays (PWTD) is connected to one of the inputs of module 26 for transforming reciprocal values of the pulse wave time delays (PWTD) into blood pressure units, the other input of module 26 is connected to a output of module 24 for recording blood pressure readings. Both the input of module 24 for recording blood pressure readings and the third input of module 26 for transforming reciprocal values of the pulse wave time delays (PWTD) into blood pressure units are connected bi-directionally to control module 17. Whereas for the time being there are no devices which can measure ambulatory blood pressure in an online mode (beat to beat), adding of these modules enables in addition to the parameters measured and the correlation analyses performed by the device to produce the relative changes of the blood pressure in an online mode, which can be of significant importance to the physician at a later stage of the diagnostics either independently or in correlation with other measured parameters.

The device showed on Figures 3 and 4 also includes a power unit, but because it is not essential for understanding functioning of the device, the power unit is not shown in drawings.

The device according to the invention operates as follows.

Signals from set 1 of ECG electrodes and pulse wave sensor 2 attached to the patient are digitized in the amplifier and analog-to-digital converter 3 of the ECG signals and in the amplifier and analog-to-digital converter 4 of the pulse wave signals accordingly and these signals are stored in memory device 5 for recording signals derived from the patient. All the signals registered throughout a long-term monitoring cycle are stored in memory device 5 and after the analyses have been performed during the cycle and at the end of the cycle, transferred through control unit 17 into peripheral memory device 23, should later use of those signals be needed. When signals have been stored in peripheral memory device 23, they can be transferred back into memory device 5 when needed and the analyses already performed can be repeated, memory device 23 can also be used for collecting a long-term archive, which in some diagnostic cases could be of significant interest for the physician. When memory device 5 has been emptied, a next long-term monitoring cycle of the patient can be started and said memory device can be used for recording the data of the new cycle.

The digital ECG signals stored in memory device 5 are led into module 7 for registering the moments of the R-peaks, which thereafter are led into module 8 for calculating RR intervals (Figure 2). The intervals calculated in module 8 are led into module 9 for forming a sequence of the NN intervals, where the intervals of irregular length are eliminated from among the registered RR intervals and only the intervals of regular length are maintained. These intervals are indicated as NN intervals, thus in module 9 a sequence of the NN intervals of the ECG signal is formed. This sequence is transferred into module 12 for period variability analysis of the heartbeats and into module 13 for frequency variability analysis of the heartbeats, where the period and frequency analyses of the heartbeats are performed on the basis of the NN intervals of the ECG signal. The results of the analyses are stored in the memory of control unit 17.

The stored digital ECG signals are transferred into module 6 for registering Q and T moments, for calculating QT intervals and for forming a NN sequence, for which purpose the moments of the R-peaks of the ECG signal registered in module 7 are also transferred through a second input. In module 6 the following processes take place: Q and T moments are registered and periods between them - QT intervals – calculated on the basis of and close to the R-wave peaks of the ECG signal (Figure 2). From the calculated QT intervals first the irregular ones are eliminated and only the ones which are synchronous with the NN intervals of the whole ECG signal are maintained for the analysis purposes. This kind of selection forms a NN sequence of the QT intervals in the output of module 6.

The NN sequence of the QT intervals is led into module 10 for period variability analysis of QT intervals and into module 11 for frequency variability analysis of QT intervals, where on the basis of the NN sequence of the QT intervals period variability and frequency variability analyses of the QT intervals are performed. The results of those analyses are stored in the memory of control module 17.

The digital pulse wave signals stored in memory device 5 are led into module 14 for registration of the moments of the raising fronts of the pulse wave. Because the rise of the raising front of the pulse wave is sharp, the moment registered corresponds to almost 1/2 of the amplitude of the pulse wave (Figure 2). The moments of the raising fronts of the pulse wave registered in module 14 and the R-peaks of the ECG signals registered in module 7 are led into module 15 for calculating time delays of the pulse wave (PWTD), as a time interval between the moments of the R-peaks and the subsequent moments of the raising fronts of the pulse wave. Calculated pulse wave time delays and through another input also a sequence of the NN intervals of the ECG signal formed in module 9 are both led into module 16 to form a NN sequence of the pulse wave time delays. Selection of the pulse wave time delays for each NN interval of the ECG signal is performed in module 16. It means that from all of the calculated pulse wave time delays only those are maintained which correspond to the NN sequence of the ECG signal. The rest of the time delays are eliminated.

The NN sequence of the pulse wave time delays formed in module 16 is led into module 18 for period variability analysis and into module 19 for frequency variability analysis, where the period variability and the frequency variability analyses of the time delays of the pulse wave are performed. The results of the analyses are stored in the memory of control module 17.

Correlation analysis module 20 connected bi-directionally to control device 17 performs four correlation analyses comparing previously obtained parameters of the heartbeat and the parameters of the pulse wave in pairs.

For correlation of the variability analysis of the heartbeat periods and pulse wave time delays, the results of the period variability analysis of the heartbeat periods and the results of the period variability analysis of the pulse wave time delays stored in the memory of control module 17 are led into correlation analysis module 20 and the results of the correlation analyses are stored back into the memory of control module 17.

The results of the frequency variability analysis of the pulse wave and the results of the frequency variability analysis of the heartbeats, which are all stored in the memory of control module 17, are led for the correlation analysis of the frequency variability of the heartbeats and pulse wave time delays into correlation analysis module 20 and the results of said correlation analyses are stored back into the memory of control device 17.

For correlation analysis of the period variability of the heartbeats and QT intervals, the results of the period variability analysis of the heartbeats and period variability analysis of the QT intervals stored in the memory of control module 17 are led into correlation analysis module 20, and the results of said analyses are stored back into the memory of control device 17.

For correlation analysis of the frequency variability correlation of the heartbeats and QT intervals, the results of the frequency variability analysis of the heartbeats and frequency variability analysis of the QT intervals stored in the memory of control device 17 are led into correlation analysis module 20, and the results of said analyses are stored back into the memory of control device 17.

The results of the above correlation analyses enables registration of more versatile aspects of the functioning of the cardiovascular (heart and circulatory) system of a patient in different situations. Mapping of the indicators of the correlation analysis derived from the patients having different disorders and also mapping of said indicators derived from healthy persons having different functional conditions enables the use of those numerical indicators for further diagnostic purposes.

All the data stored in the memory of control module 17 can be displayed by using commands of peripheral control device 21 on the display 22 in extent and order selected by the operator (physician). Peripheral control device 21 enables copying of the data stored in the memory of control device 17 into peripheral memory device 23, deletion of the data from the memory of control device 17, deletion of the data from peripheral memory device 23, etc.

Figure 4 shows an embodiment of the device enabling to report the parameters measured by the device and the results of the correlation analyses performed by the device, also relative changes of the blood pressure in an online mode throughout the whole measurement cycle. For that purpose the mean (systolic) value of the blood pressure of the patient in a relaxed state is measured by the calibrated measurement device and said value is entered by peripheral control device 21 through control module 17 into storage module 24 for blood pressure values. Module 25 calculates the reciprocal values 1/PWTD of the pulse wave which are thereafter are led into module 26 for transforming the reciprocal value of the pulse wave delay (PWTD) into blood pressure units, also the blood pressure from module 24 is led into module 26 through the second input. This way the process of the changes of the blood pressure of the patient throughout the long-term monitoring cycle is obtained in module 26. Data obtained is stored through control module 17 in peripheral memory device 23.

It is obvious to the person skilled in the art, that the invention is not limited to the embodiments described above, but also includes other solutions, which are covered by the claims.

Reference signs list

1. ECG electrode set
2. Pulse wave sensor
3. Amplifier and analog-to-digital converter of ECG signals
4. Amplifier and analog-to-digital converter of pulse wave signals
5. Memory device for storing signals derived from the patient
6. Module for registering Q and T moments, for calculating QT intervals and for formation of a NN sequence
7. Module for registering moments of R-peaks
8. Module for calculating RR intervals
9. Module for formation of a sequence of NN intervals
10. Module for period variability analysis of QT intervals
11. Module for frequency variability analysis of QT intervals
12. Module for variability analysis of heartbeat periods (Time Domain HRV)
13. Module for frequency variability analysis of heartbeats (Frequency Domain HRV)
14. Module for registering the moments of raising fronts of pulse wave
15. Module for calculating time delays of pulse wave (PWTD)
16. Module for forming a NN sequence of time delays of pulse wave
17. Control module
18. Module for period variability analysis of time delays on the basis of NN intervals of pulse wave
19. Module for frequency variability analysis of time delays on the basis of NN intervals of pulse wave
20. Module for correlation analysis
21. Peripheral control device
22. Display
23. Peripheral memory device
24. Module for storing blood pressure values
25. Module for calculating reciprocal value of pulse wave delay (PWTD)
26. Module for converting reciprocal values of pulse wave delay (PWTD) into blood pressure units

Claims

Method for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals, comprising the following steps:

registration and recording of ECG and pulse wave signals;

registration of R-peaks of ECG signals and raising fronts of the pulse wave;

calculation of RR intervals of ECG signals from the R-peaks of the ECG signals;

formation of a sequence of the NN intervals of the ECG signal from the RR intervals of the ECG signal;

performing variability analysis of the heartbeat periods on the basis of the sequence of the NN intervals of the ECG signal;

performing variability analysis of the heartbeat frequency on the basis of the sequence of the NN intervals of the ECG signal;

calculation of time delays of the pulse wave on the basis of the registered R-peaks of the ECG signal and raising fronts of the pulse wave;

characterized by

forming a NN sequence of the time delays of the pulse wave calculated on the basis of the sequence of the ECG NN intervals and raising fronts of the pulse wave;

performing both frequency and period variability analysis of the time delays of the pulse wave on the basis of the NN sequence of the pulse wave time delays;

calculating QT intervals on the basis of the stored ECG signals and registered R-peaks of the ECG signal;

forming a NN sequence of QT intervals on the basis of the calculated QT intervals and NN intervals of the ECG signal;

performing both frequency and period variability analysis of the QT interval on the basis of the NN sequence of the QT intervals;

performing correlation analysis of the results of the period variability analysis of the heartbeats and of the results of the period variability analysis of the pulse wave time delays;

performing correlation analysis of the results of the frequency variability analysis of the heartbeats and of the results of the frequency variability analysis of the pulse wave time delays;

performing correlation analysis of the results of the period variability analysis of the heartbeats and of the results of the period variability analysis of the QT intervals;

performing correlation analysis of the results of the frequency variability analysis of the heartbeats and of the results of the frequency variability analysis of the QT intervals.
Method for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals according to claim 1, characterized by storing ECG and pulse wave signals throughout the monitoring cycle.
Method for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals according to claims 1 and 2, characterized by repeatedly and periodically performing analyses on the basis of the ECG and pulse wave signals continuously registered during the whole monitoring cycle.
Method for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals according to claims 1, 2 and 3, characterized by that the periodical analyses are performed on the basis of all the ECG and pulse wave signals registered by the time of the analysis.
Device for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals comprising set (1) of ECG electrodes, amplifier of ECG signals and analog-to-digital converter (3), memory device (5) for storing signals derived from a patient, module (7) for registering moments of R-peaks, module (8) for calculating RR intervals, module (9) for forming a sequence of NN intervals, module (12) for period variability analysis of the heartbeats, module (13) for frequency variability analysis of the heartbeats and control module (17),

where the output of the set of ECG electrodes is connected to the input of the amplifier of ECG signals and analog-to-digital converter (3),

the output of which is connected to an input of the memory device (5) for storing signals derived from a patient,

one output of the latter is connected to the input of module (7) for registering moments of R-peaks and the other output is connected bi-directionally to control module (17),

one output of module (7) for registering moments of R-peaks is connected to the input of module (8) for calculating RR intervals and the output of module (8) is connected to the input of module (9) for forming a sequence of NN intervals, the output of module (9) is connected to the input of module (12) for the period variability analysis of the heartbeats and to the input of module (13) for frequency variability analysis of the heartbeats,

at that the outputs of said modules are connected bi-directionally to control module (17),

characterized by that

device additionally comprises pulse wave sensor (2), amplifier and analog-to-digital converter (4) of the pulse wave signals, module (6) for registering Q and T moments, for calculating QT intervals and for forming NN sequence,

module (10) for period variability analysis of QT intervals, module (11) for frequency variability analysis of QT intervals,

module (14) for registering moments of the raising fronts of the pulse wave, module (15) for calculating time delays of the pulse wave, module (16) for forming a NN sequence of the pulse wave time delays, module (18) for period variability analysis of the time delays of the pulse wave on the basis of NN sequence of the pulse wave,

module (19) for frequency variability analysis of the time delays of the pulse wave on the basis of the NN sequence of the pulse wave and module (20) for correlation analysis,

whereby the output of pulse wave sensor (2) is connected to the input of the amplifier and analog-to-digital converter (4) of pulse wave signals,

and the output of the latter is connected to the second input of the memory device (5) for storing signals derived from the patient,

the second output of memory device (5) is connected to the input of module (14) for registering moments of raising fronts of the pulse wave, the output of module (14) is connected to one input of the module (15) for calculating time delays of the pulse wave,

the second input of module (15) is connected to the third output of module (7) for registering moments of the R-peaks,

the output of module (15) is connected to one input of module (16) for forming a NN sequence of the time delays of the pulse wave,

the second input of module (16) is connected to the output of the module (9) for forming a sequence of NN intervals,

the output of module (16) is connected to the input of module (18) for period variability analysis of the time delays of the pulse wave on the basis of the sequence of NN intervals of the pulse wave and to the input of module (19) for frequency variability analysis of the time delays of the pulse wave on the basis of the sequence of NN intervals,

and the outputs of those latter modules (18 and 19) are connected bi-directionally to control module (17) and the correlation analysis module (20) is connected bi-directionally to control module (17).
Device for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals according to claim 5, characterized by that ,

the device comprises a module (24) for storing blood pressure values, a module (25) for calculating reciprocal value of the pulse wave delays

and a module (26) for transforming reciprocal values of the pulse wave time delays into blood pressure units,

where the input of module (25) for calculating reciprocal value of the pulse wave time delays is connected to the output of module (15) for calculating time delays of the pulse wave,

the output of module (25) for calculating reciprocal value of the pulse wave time delays is connected to one input of module (26) for transforming reciprocal values of the pulse wave time delays into blood pressure units,

the second input of module (26) is connected to the output of module (24) for storing blood pressure values,

and the input of module (24) for storing blood pressure values and also the third input of module (26) for transforming reciprocal values of the pulse wave time delays into blood pressure units are connected bi-directionally to control module (17).
Device for long-term variability monitoring of cardiovascular parameters based on ambulatory registration of electrocardiogram and pulse wave signals according to claim 5, characterized by that , control module (17) is connected to peripheral control device (21), to display (22) and to peripheral memory device (23).