Method of detecting parameters indicative of activation of the sympathetic and parasympathetic nervous systems

Abstract

A computer-implemented method for detecting parameters indicative of a change in activation of a sympathetic nervous system and a change in activation of a parasympathetic nervous system in a subject in a transition from a basal state to a perturbed state comprises calculating a power ratio between the powers of a power spectrum of a systolic time interval and a diastolic time interval in LF and HF frequency bands.

Description

Technical Field

[0001] The present invention relates to a computer-implemented method for detecting parameters indicative of changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system, whereby it is also possible to assess changes in the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system in a subject's transition from a basic state (hereinafter also referred to as a basal state) to a perturbed state, whereby this method provides for distinguishing between a sufficient balance and an imbalance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system in a subject's transition from a basic state to a perturbed state. The computer-implemented method is able to indicate in a simple, universal, effective and reliable manner the influence of the transition of the subject itself from the basic state to the perturbed state on the interaction between the sympathetic and parasympathetic nervous systems, for example to determine the influence of this interaction on the application of a drug and / or a change in posture of the subject itself.

[0002] The invention also relates to an apparatus configured to perform such a method.

[0003] The method according to the invention is a computer-implemented method, wherein the term "computer" refers to any processing device (in particular at least one microprocessor) executing a set of one or more computer programs, the computer programs comprising instructions which, when executed by a device according to the invention, cause the same device to perform the computer-implemented method for detecting activation of the vagus nervous system. Furthermore, the one or more computer programs may be stored on a set of one or more computer-readable media. Background Art

[0004] It is well known that heart rate can be defined as the average number of heartbeats per minute. This number, for example 70 beats / minute (b / m), is an average value, because the time between one heartbeat and the next is not actually constant and varies constantly. Heart rate variation, also known as HRV, is a useful parameter for assessing the health of a subject. In fact, the measurement and analysis of HRV is becoming increasingly important, because a lot of information can be inferred from this measurement, allowing, for example, to assess the risk of arrhythmias and heart attacks, and whether the balance between the activity of the orthosympathetic nervous system (also known as the sympathetic nervous system) and the activity of the parasympathetic nervous system is correct. In this regard, although the evaluation of HRV is limited to the field of cardiology, many recent scientific studies have shown its importance as a reliable indicator in many other application areas as well.

[0005] As is known, HRV is the natural variation of heart rate in response to factors such as breathing rhythm, emotional states such as anxiety, stress, anger, relaxation, etc. In a healthy heart, the heart rate responds quickly to all these factors, thus varying according to the situation in order to better adapt the body to the different states it experiences. Typically, healthy subjects show a good degree of heart rate variation to different situations, i.e. an appropriate degree of psychophysical adaptability.

[0006] HRV is related to the interaction between the sympathetic and parasympathetic nervous systems, which in turn affects the function of organs and systems of the body, such as cardiovascular and respiratory interactions.

[0007] The sympathetic nervous system produces a range of effects when activated, such as: increased heart rate, bronchial dilation, increased blood pressure, peripheral vasoconstriction, pupil dilation, and increased sweating. The chemical mediators of these vegetative responses are norepinephrine, epinephrine, adrenocorticotropic hormone, and several corticosteroids. The sympathetic nervous system is the body's normal response to alarm, struggle, physical, and / or emotional stress (also known as the "fight or flight" response).

[0008] In contrast, the parasympathetic nervous system (also expressed by vagal tone, i.e., activity of the vagus nerve, or vagal activity) when activated produces a slower heart rate, increased bronchial muscle tone, vasodilation, decreased pressure, slower breathing, increased muscle relaxation, calmer and deeper breathing, and warmer genitals, hands, and feet. It works through the typical chemical intermediary, acetylcholine. The parasympathetic nervous system represents the body's normal response to calm, rest, tranquility, and a situation free from danger and (physical and emotional) stress.

[0009] The subject's organism is in a situation at any time determined by the balance or dominance of these two nervous systems, the sympathetic and the parasympathetic. The ability of the organism to change its own balance through greater activation of one or the other nervous system is very important and is a fundamental mechanism that tends to the body's dynamic balance from a physiological and psychological point of view.

[0010] The assessment of HRV allows the evaluation of the relative state of balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system. This is very important for evaluating when and how these two systems are optimally balanced in a specific situation and / or a specific type of patient (which can be both healthy and pathological subjects).

[0011] Typically, HRV is assessed by measurement using an electrocardiogram machine (also called ECG or EKG) equipped with conventional surface electrodes applied at the level of the heart to detect the heart's electrical activity (see, e.g., J. W. Hurst, et al., 2001). 心电图中各波段的命名及其产生机制简述Issued, Vol. 98, No. 18, November 3, 1998, pp. 1937-42), where the associated very complex special software performs data analysis by identifying individual beats and their variations. As an example and not a limitation, examples of such software are those available from the Italian company Elemaya (see www.elemaya.it) and those available from the Finnish company Kubios Oy (www.kubios.com). In particular, after being digitized, the data is analyzed by a computer execution method, and the software calculates the time distance between each heartbeat and the next heartbeat by measuring the time distance between the R peaks of the ECG signal (usually expressed in milliseconds), and then establishes a graph, called a blood flow velocity graph, which represents the trend of the RR distance between one heartbeat and the next heartbeat (ordinate axis), usually expressed in milliseconds, as a function of the number of heartbeats (abscissa axis). The blood flow velocity graph is usually made at a time interval of 4-5 minutes (i.e., a total of about 300 heartbeats).

[0012] The software then resamples the tachogram and then performs a Fourier transform to obtain the power spectrum, i.e., power spectral density, also denoted as PSD, of the tachogram resulting from the resampling operation (see, e.g., J. Pucik et al., 心率变异性频谱:生理混叠与非平稳性 注意事项 , Trends in Biomedical Engineering Conference paper, Bratislava, September 16-18, 2009).

[0013] The power spectrum PSD represents the frequency components of the blood flow velocity diagram and contains essential information for evaluating the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system. In particular, the power spectrum PSD of the blood flow velocity diagram represents the power of the blood flow velocity diagram (in the frequency domain) at frequencies between 0.01 Hz and 0.4 Hz. The power is usually expressed in milliseconds squared.

[0014] Recent studies and research (see, for example, AE Aubert et al., 运动员的心率变异性 运动员 ”, Sports Medicine 33 (12):889-919, 2003) allows us to distinguish three sub-bands of frequency, called:

[0015] - VLF (very low frequency) band, for frequencies between 0.01 Hz and 0.04 Hz, depending on changes in thermoregulation and, in psychological situations, affected by states of worry and obsessive thoughts (worry and rumination) and which are only slightly due to the activity of the sympathetic nervous system;

[0016] - LF (low frequency) band, for frequencies between 0.04 Hz and 0.15 Hz, believed to be mainly due to activity of the sympathetic nervous system and modulation of baroreceptors; and

[0017] - The HF (high frequency) band, for frequencies between 0.15 Hz and 0.4 Hz, is considered to be an expression of the activity of the parasympathetic nervous system (and therefore of the fundamental component constituted by the activity of the vagus nerve; in particular, the HF band is strongly influenced by the rhythm and depth of respiration, whereby a changed rhythm and / or depth increases the contribution of the HF band to the power spectrum PSD of the tachogram.

[0018] The relationship between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system is assessed by the LF / HF ratio between the power of the blood flow velocity diagram in the LF frequency band and the power of the blood flow velocity diagram in the HF frequency band (possibly normalized to their sum). In particular, in the literature, power values ​​are often also expressed in their logarithmic form.

[0019] Finally, the software can also calculate the standard deviation SD of the tachogram and / or the total power (possibly in logarithmic form), where the total power is usually set equal to the square of the standard deviation of the tachogram (e.g., see AE Aubert et al., cited above). Both parameters express the overall degree of HRV and thus the overall activity of the sympathetic and parasympathetic nervous systems.

[0020] In this context, Chengyu Liu et al. conducted a study on the correlation between changes in systolic and diastolic time intervals based on ECG and phonocardiogram signals (PCG-phonocardiogram) and HRV for evaluating cardiovascular nonlinear dynamics ( 收缩期 与舒张期时间间期变异性分析及其与 心率变异性 ,BIOINFORMATICS AND BIOMEDICAL ENGINEERING, 2009, ICBBE2009. 3rd International Conference, IEEE, PISCATAWAY, NJ, USA, June 11, 2009, pp. 1-4, XP031489349, ISBN: 978-1-4244-2901-1) for further research. In addition, Park Ji Hyun et al. studied the possible comparison of respiratory changes in the systolic and diastolic time intervals in the radial artery waveform with dynamic indices ( 呼吸 桡动脉波形中收缩期和舒张期时间间期的变化:与动态前负荷指数的比较 桡动脉波形中收缩期和舒张期时间间期的变化:与动态前负荷指数的比较, JOURNAL OF CLINICAL ALANESTHESIA, BUTTERWORTH PUBLISHERS, Stoneham, GB, Vol. 32, 24 March 2016, pp. 75-81, XP029596121, ISSN: 0952-8180, DOI: 10.1016 / J.JCLINANE.2015.12.022).

[0021] Clinical experience in recent years has also allowed us to define reference ranges for the values ​​of the above parameters (i.e. heart rate, tachogram, standard deviation SD, tachogram total power, tachogram power in the VLF band, tachogram power in the LF band and tachogram power in the HF band). Although the definition of reference ranges is not completely identical between different authors and between American and European standards, in the context of state-of-the-art software, reference ranges derived from an experimental basis relevant to the population considered (e.g. the Italian population in the case of studies and research conducted on Italian subjects) have been adopted.

[0022] Furthermore, different reference ranges have been introduced for the older population (50 to 70 years) or the younger population (20 to 50 years).

[0023] However, the prior art methods for assessing the state of balance between the activity of the sympathetic and parasympathetic nervous systems based on the assessment of HRV still lack consistency in the interpretation of the results that can be obtained from the analysis of the measurements performed. For example, in the literature there are widely different (if not conflicting) indications regarding the time intervals within which the analysis must be performed (i.e. the collection of data to establish the blood flow velocity map to be analyzed) and regarding the pathology of the examined subject to which the results obtained from the analysis of the measurements performed on a single subject must be referred. Summary of the invention

[0024] Therefore, the purpose of the present invention is to achieve the evaluation of the activation of the sympathetic nervous system and the parasympathetic nervous system, as well as the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system in a simple, universal, effective and reliable manner, so as to indicate the influence of the interaction between such sympathetic and parasympathetic nervous systems in the transition of the subject itself from a basal state to a perturbed state, for example to determine the influence of such interaction on the application of drugs and / or posture changes of the subject itself.

[0025] A specific object of the present invention is a computer-implemented method for detecting parameters indicative of changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system of a subject during a transition of the subject from a basal state to a perturbed state, comprising the steps of:

[0026] A. Receive a discrete pressure signal including multiple heartbeats of the subject ;

[0027] B. Identifying discrete pressure signals each heartbeat and identifies the systolic phase within each heartbeat and diastolic ;

[0028] C. Create a graph of systolic duration as a function of the number of incremental heartbeats and a plot of diastolic duration as a function of the number of incremental heartbeats ;

[0029] D. Implementation of the systolic duration graph The resampling of the systolic duration is obtained. , and the diastolic duration graph is implemented The resampling of diastolic duration is obtained ;

[0030] E. Calculate at the lower frequency limit f 下限 and above the lower frequency limit f 下限 Upper frequency limit f 上限 Resampled plot of systolic duration at frequencies between The power spectrum and resampled plots of diastolic duration The power spectrum ;

[0031] F. Calculate the power spectrum in the LF band Power , HF band mid-power spectrum Power , power spectrum in LF band Power And the power spectrum in the HF band Power , where the frequency in the LF band is f LF Higher than or equal to the first intermediate frequency f 中间_1 and below the second intermediate frequency f 中间_2 ,thus

[0032] f 中间_1 ≤ f LF ＜ f 中间_2 ,

[0033] Among them, the lower limit frequency f 下限 Below the first intermediate frequency f 中间_1 , which is lower than the second intermediate frequency f 中间_2 , which is lower than the upper frequency limit f 上限 ,thus

[0034] f 下限 ＜ f 中间_1 ＜ f 中间_2 ＜ f 上限 ,

[0035] And among them, the frequency in the HF band f HF Higher than or equal to the second intermediate frequency f 中间_2 And below the upper frequency limit f 下限 ,thus

[0036] f 中间_2 ≤ f HF ＜ f 上限 ;and

[0037] G. Calculate and output the power spectrum in LF and HF bands The ratio between the power The values ​​of and the power spectra in the LF and HF bands The ratio between the power The value of

[0038]

[0039] Therein, steps AG of the computer-implemented method are first carried out on the object in a base state and then on the object in a disturbed state.

[0040] According to another aspect of the present invention, the lower limit frequency f 下限 Can be equal to 0.01Hz, upper limit frequency f 上限 The first intermediate frequency can be in the range of 0.4Hz to 1.2Hz. f 中间_1 The second intermediate frequency can be in the range of 0.04Hz to 0.12Hz f 中间_2can be in the range of 0.15 Hz to 0.45 Hz, where the upper frequency limit is optionally f 上限 The first intermediate frequency can be in the range of 0.8Hz to 1.2Hz. f 中间_1 The second intermediate frequency can be in the range of 0.08Hz to 0.12Hz f 中间_2 can be in the range of 0.30 Hz to 0.45 Hz, where more preferably, the upper frequency f 上限 Can be equal to 1.2Hz, the first intermediate frequency f 中间_1 Can be equal to 0.12Hz, the second intermediate frequency f 中间_2 It can be equal to 0.45Hz.

[0041] According to another aspect of the present invention, in step E, the resampled map of the systolic duration The power spectrum and resampled plots of diastolic duration The power spectrum The χ2 can be calculated by a Fourier transform, optionally by a fast Fourier transform (FFT), respectively.

[0042] According to an additional aspect of the present invention, the discrete pressure signal received in step A It may have a duration of at least 3 minutes, optionally at least 4 minutes, more optionally at least 5 minutes.

[0043] According to another aspect of the present invention, in step B, the systolic period and the diastolic period of each heartbeat can be identified based on the identification of the dicrotic notch time.

[0044] According to yet another aspect of the present invention, a computer-implemented method may:

[0045] - In step B, further identify the dicrotic notch pressure in each heartbeat The value of

[0046] - In step C, a graph of the dicrotic notch pressure as a function of the number of progressive heartbeats is further created ;

[0047] - In step D, further plotting of the dicrotic notch pressure is performed The resampling of the dicrotic notch pressure is obtained ;

[0048] - In step E, further calculation is performed at the lower frequency limit f 下限 and upper frequencyf 上限 Resampled plot of dicrotic notch pressure at frequencies between The power spectrum ;

[0049] - In step F, the power spectrum in the LF band is further calculated Power and the power spectrum in the HF band Power ;and

[0050] - In step G, the power spectra in the LF and HF bands are further calculated and output The ratio between the power The value of , thus:

[0051] .

[0052] According to an additional aspect of the invention, in step C, a map of systolic duration can be created by expressing the systolic duration and diastolic duration of each heartbeat as values ​​normalized to the overall duration of the heartbeat under consideration. and diastolic duration .

[0053] According to another aspect of the present invention, the computer-implemented method may further include determining and outputting the HRV (heart rate variability) of the subject first in a basal state and then in a perturbed state.

[0054] According to yet another aspect of the invention, the computer-implemented method may further calculate a resampled map of systolic duration of a subject first in a basal state and then in a perturbation state. Standard Deviation and resampled plots of diastolic duration Standard Deviation , and output them in step G.

[0055] According to an additional aspect of the invention, the computer-implemented method may further calculate a resampled map of systolic duration of a subject first in a basal state and then in a perturbation state. The power spectrum Total power and resampled plots of diastolic duration The power spectrum Total power , and they can be output in step G.

[0056] Another specific object of the present invention is a device comprising a processing unit, which is configured to execute a computer-implemented method as described above for detecting parameters indicating changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system in the subject's transition from a basal state to a disturbed state.

[0057] Another specific object of the present invention is a set of one or more computer programs comprising instructions, which, when executed by one or more processing units, cause the one or more processing units to perform a computer-implemented method as described above for detecting parameters indicating changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system in the transition of an object from a basal state to a disturbed state.

[0058] A further specific object of the invention is a set of one or more computer-readable media on which is stored a set of one or more computer programs just described.

[0059] The computer-implemented method and the related apparatus according to the present invention, due to the separate analysis of the systolic and diastolic phases of the cardiac pressure cycle (e.g. arterial pressure or pulmonary venous pressure or central venous pressure), allow to provide reliable indications for identifying changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system in the transition of the subject from a basal state to a perturbed state, as well as for distinguishing between a sufficient balance and an imbalance between activation of the sympathetic nervous system and activation of the parasympathetic nervous system. This allows, for example, to determine the effects of applied drugs and / or changes in the subject's own posture on the sympathetic and parasympathetic nervous systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] For illustrative purposes and not limiting purposes, the following description will be given according to its preferred embodiments and with particular reference to the accompanying drawings. Figure 1 To describe the present invention, Figure 1 A flow chart of a preferred embodiment of a computer-implemented method according to the present invention is shown. DETAILED DESCRIPTION

[0061] The inventors unexpectedly discovered that in order to obtain more information about the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system and the balance between them, the coupling of the heart with the arterial system can be exploited based on the variability of the cardiac rhythm in the subject. To this end, unlike ECG-based detection techniques, the computer-implemented method according to the invention is based on the cardiac pressure cycle. The computer-implemented method according to the invention exploits the "mechanical" nature of the heartbeat, which consists of two main periods, namely the systolic period and the diastolic period.

[0062] Differently, the prior art methods and devices using ECG signal detection are based on the cardiac cycle of electrical signals. Since the electrical signal of the cardiac cycle corresponds only to the electrical component of the electromechanical cardiac activity used to circulate blood in the human body, it is not sufficient to provide all the available information about the balance of the sympathetic and parasympathetic nervous systems, because most of this information is related to the mechanical component of the cardiac activity that actually circulates the blood. In fact, the electrical signal sent to the heart does not immediately produce a mechanical response of the heart itself, because this also depends on the inertia of the heart and the cardiovascular system, that is, on the specific state of rigidity and compliance of the various systems that form the cardiovascular system. This shows that the prior art methods and devices for evaluating HRV using the detection of ECG signals are subject to errors and approximations, which greatly limit their reliability. As an example and not a limitation, in the case of problems with the electromechanical coupling of the heart with the cardiovascular and respiratory systems caused by the aortic valve not opening correctly, only the electrical component of the cardiac activity can provide an ECG signal that sends a sufficient heartbeat signal by detecting the electrical activity of the heart, while the mechanical function of the heart is severely impaired, and the sympathetic and parasympathetic nervous systems are activated in an unbalanced manner relative to each other; this applies to all cases where the electrical component of the cardiac activity is qualitatively separated from the mechanical component.

[0063] According to the computer-implemented method of the invention, due to the separate analysis of the variability of the duration of the systolic and diastolic phases of the cardiac pressure cycle, it is possible to obtain the detection of parameters indicating changes in the activation of the sympathetic and parasympathetic nervous systems, whereby it is also possible to evaluate changes in the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system, which allows a reliable evaluation of the activation of the sympathetic and parasympathetic nervous systems and their degree of balance. In fact, since the cardiac pressure cycle has a typical pressure morphology in which the systolic and diastolic phases are clearly defined, it is possible to distinguish and therefore weigh the contributions to the HRV of the same systolic and diastolic phases and not just the entire cardiac cycle, as this occurs for the evaluation of HRV not by analyzing the blood flow velocity diagram based on the RR distance of the ECG signal according to the prior art methods. In the following, the variability of the duration of the systolic phase of the pressure signal will be denoted by SYS-V, while the variability of the duration of the diastolic phase of the pressure signal will be denoted by DIA-V.

[0064] In particular, by separate analysis of SYS-V and DIA-V performed according to the computer-implemented method of the present invention, it is possible to detect parameters indicating changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system, as well as parameters indicating a balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system, the balance in one or both of systole and diastole being different from the balance evaluated by detecting HRV throughout the cardiac cycle relative to ECG signals based on prior art methods.

[0065] As an example and not a limitation, the same HRV may correspond to three different pairs of SYS-V and DIA-V for three respective subjects, namely, for an athlete, a cardiac patient and a normal subject. In fact, in general, even in the case where the RR distance of the ECG signal does not change in multiple cardiac cycles, there may be changes of opposite signs in the duration of systole and the duration of systole in the same multiple cardiac cycles due to the adaptation of the body to the specific conditions it experiences. Therefore, the variability of the systolic and diastolic periods may represent contributions of the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system that are different from each other, whereby the analysis of SYS-V and DIA-V provides more specific information about such contributions. Similarly, in the case where the heart rate of the subject is constant before and after the event, the two mechanical periods that form it, namely the systolic and diastolic periods, may vary. In this way, the computer-implemented method according to the present invention allows to identify in advance whether it is necessary to cause a change in the contribution of the activation of the sympathetic nervous system relative to the contribution of the activation of the parasympathetic nervous system, for example, by intervening to affect and change the activation component of the parasympathetic nervous system that is the activation component of the sympathetic nervous system, such as the administration of vasoconstrictors or vasodilators or positive inotropic drugs.

[0066] Thus, by means of the SYS-V and DIA-V analysis performed by the computer-implemented method according to the invention, it is possible to reliably assess the degree of balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system in response to some pathological conditions of drug and surgical stress, which the prior art methods for HRV measurement based on ECG signal detection cannot correctly identify. In particular, by means of the analysis of SYS-V and DIA-V, the computer-implemented method according to the invention is able to allow early identification of some pathological conditions when they are not yet apparent, whereas the prior art methods identify these conditions only after they have worsened.

[0067] Figure 1 A flow chart of a preferred embodiment of a computer-implemented method according to the present invention is shown.

[0068] In a first step 1000, the method receives a discrete pressure signal comprising a plurality of heart beats of a subject or patient. (e.g. arterial pressure or pulmonary venous pressure or central venous pressure). In particular, the discrete pressure signal Can be detected by pressure sensor and digitized to obtain discrete signal (where index i represents the continuum of discrete samples) or a discrete signal stored in a storage medium (i.e. already digitized); in particular, a continuous pressure signal The detection can be performed invasively or non-invasively, for example, by a photoplethysmographic sensor. The discrete pressure signal received Having a duration of optionally at least 3 minutes, more optionally at least 4 minutes, even more optionally at least 5 minutes.

[0069] In a second step 1050, the method identifies discrete pressure signals each heartbeat and identifies the systolic phase within each heartbeat and diastolic Optionally, the method identifies each heartbeat by an automatic method for distinguishing heartbeats described in International Application No. WO2004 / 084088A1, and / or identifies the systole and diastole of each heartbeat based on the identification of the dicrotic notch time (corresponding to the aortic valve closure time of the arterial pressure signal or the tricuspid valve closure time of the pulmonary pressure signal).

[0070] In a third step 1100, the method creates a graph of systolic duration (ordinate) as a function of the number of incremental heartbeats (abscissa axis). and the duration of diastole (ordinate) as a function of the number of incremental heartbeats (abscissa axis) The systolic duration and diastolic duration are optionally expressed in milliseconds.

[0071] In a fourth step 1150, the method performs a graph of the systolic duration. and diastolic duration (established in the third step 1100) resampling is performed to obtain a resampled graph of the systolic duration and resampled plots of diastolic duration .

[0072] In a fifth step 1200, the method calculates the lower frequency f 下限 , optionally equal to 0.01Hz and upper frequency f 上限 (Above the lower frequency limit f 下限 ), optionally from 0.4 Hz to 1.2 Hz, more optionally from 0.8 Hz to 1.2 Hz, and even more optionally equal to 1.2 Hz. The power spectrum and resampled plots of diastolic duration The power spectrum ; In particular, the lower frequency f 下限 and upper frequency f 上限 Depending on the type of object under examination, the method optionally calculates a resampled map of the systolic duration by means of a Fourier transform, more optionally a fast Fourier transform (FFT). The power spectrum and resampled plots of diastolic duration The power spectrum As an alternative to Fourier transformation, other embodiments of the computer-implemented method according to the present invention may calculate the power spectrum by autoregressive modeling or by wavelet transformation and .

[0073] In a sixth step 1250, the method converts the power spectrum and Each of the three frequency bands is subdivided into VLF (very low frequency), LF (low frequency) and HF (high frequency). In the LF band, the frequency f LF At the first intermediate frequency f 中间_1 To the second intermediate frequency f 中间_2 range, thus

[0074] f 中间_1 ≤ f LF ＜f 中间_2 ,

[0075] The lower frequency f 下限 Below the first intermediate frequency f 中间_1 , which is lower than the second intermediate frequency f 中间_2 , which is lower than the upper frequency limit f 上限 ,thus

[0076] f 下限 ＜f 中间_1 ＜ f 中间_2 ＜ f 上限 .

[0077] In the HF band, the frequency f HF At the second intermediate frequency f 中间_2 To upper frequency f 上限 range, thus

[0078] f 中间_2 ≤ f HF ＜ f上限 .

[0079] In the VLF band, the frequency f VLF At the lower frequency f 下限 To the first intermediate frequency f 中间_1 range, thus

[0080] f 下限 ≤ f VLF ＜f 中间_1 .

[0081] First intermediate frequency f 中间_1 and the second intermediate frequency f 中间_2 It also depends on the type of object under examination. Optionally, the first intermediate frequency f 中间_1 In the range from 0.04 Hz to 0.12 Hz, more optionally in the range from 0.08 Hz to 0.12 Hz, still more optionally equal to 0.12 Hz; optionally, the second intermediate frequency f 中间_2 In the range from 0.15 Hz to 0.45 Hz, more optionally in the range from 0.30 Hz to 0.45 Hz, still more optionally equal to 0.45 Hz.

[0082] Still in step 1250, the method calculates the power spectrum of each medium in the LF and HF bands and The power of each of ; that is:

[0083] - Power spectrum in LF band Power (given as an integral in the LF band, i.e., the power spectrum sum in the discrete frequency domain);

[0084] - Power spectrum in the HF band Power (given as an integral in the HF band, i.e. the power spectrum sum in the discrete frequency domain);

[0085] - Power spectrum in LF band Power (given as an integral in the LF band, i.e., the power spectrum sum in the discrete frequency domain);

[0086] - Power spectrum in the HF band Power (given as an integral in the HF band, i.e. the power spectrum sum in the discrete frequency domain).

[0087] In a seventh step 1300, the method calculates (and outputs) the power spectra in the LF and HF bands, respectively. and The ratio between the power and The value of , thus:

[0088] .

[0089] Based on the ratio outputted by step 1300 and The value of , taking into account the type of population to which the subject belongs, allows the physician to assess changes in the activation of the sympathetic nervous system and changes in the activation of the parasympathetic nervous system, and thereby also changes in the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system of the subject itself (i.e., the activity of the sympathetic nervous system or the activity of the parasympathetic nervous system may be dominant). In particular, the ratio and The value of depends on the type of population described by the examined subject (due to age and pathology).

[0090] In other words, the computer-implemented method according to the invention exploits the characteristics of the mechanical response of the cardiovascular system to electrical stimulation of the heart, analyzing the systolic and diastolic phases within each cardiac cycle. This allows a more reliable assessment than prior art methods, since the dynamic components of the activation of the sympathetic and parasympathetic nervous systems and the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system give different indications of the dynamic balance during these two systolic and diastolic phases, thus providing more detailed information on pressure and vagal activation.

[0091] The inventors have performed some evaluations of the results obtained by applying the computer-implemented method according to the invention and compared the results with those obtained by prior art methods in evaluating HRV. In particular, experiments were performed on subjects passing through a basal state to a perturbation state in which an event causes a change in the cardiovascular system.

[0092] Experiments have shown that the changing characteristics of HRV can be compared with the resampled diastolic duration. The change characteristics of systolic duration are consistent or inconsistent (although the absolute values ​​are not equal), while the resampled graphs of systolic duration The changing characteristics of are usually substantially different from the changing characteristics of HRV.

[0093] For patients who have been treated with a strong anesthetic agent with sympathetic effects (i.e., propofol ®Some evaluations were made of the results obtained for subjects in a perturbation condition caused by vagus nerve. According to conventional physiology, since the vagus nerve activity is activated, the ratio between the LF and HF components must decrease and, therefore, change the balance between the activity of the sympathetic nervous system and that of the parasympathetic nervous system by inhibiting the activity of the sympathetic nervous system. However, the characteristics of HRV have variations that lead to conflicting results in the ratio between the LF and HF components of the power spectrum PSD of the tachogram, resulting in a decrease in some subjects and an increase in others, indicating that the power spectrum PSD of the tachogram does not correctly identify the activation of the vagus nerve and the inhibition of the sympathetic nervous system. Differently, from the resampled graphs of the systolic duration The resulting ratio It was reduced in all patients, thus reliably identifying the prevalence of activation of the parasympathetic nervous system relative to the basal state (i.e., a state not altered by the administration of anesthetics).

[0094] In general, the results obtained by applying the computer-implemented method according to the present invention show that in order to assess which of the sympathetic and parasympathetic nervous systems is activated in a prevalent manner, the proportion of and A comparison of the changes that occur with the type of subject being examined is sufficient. For example, for some types of subjects, if the changes are not consistent, activation of the parasympathetic nervous system is predominant over activation of the sympathetic nervous system, whereas if the changes are consistent (e.g., both increase), activation of the sympathetic nervous system is predominant over activation of the parasympathetic nervous system.

[0095] In the case of patients being examined (e.g. patients with orthostatic problems leading to syncope or patients with cirrhosis of the liver) and for whom no data relating to a basal state are available, the evaluation of changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system, as well as the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system, is performed by carrying out the computer-implemented method according to the invention when the patient is lying on an examination table (assuming this is the basal state) and again when the patient is subjected to a so-called tilt test (i.e. the examination table is raised by 60°) (assuming this is a perturbation condition). For patients with cirrhosis of the liver, moving from a supine position to an upright position is sufficient as a perturbation state.

[0096] It should be emphasized that the computer-implemented method according to the present invention is not a diagnostic method per se, but rather a method for detecting a parameter, i.e. a ratio, indicating changes in activation of the sympathetic nervous system, changes in activation of the parasympathetic nervous system, and the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system during the transition of the subject from a basal state to a perturbation. and method, which requires subsequent interpretation by a physician to formulate a diagnosis.

[0097] Other embodiments of the computer-implemented method according to the present invention may also:

[0098] - In the second step 1050, the dicrotic notch pressure is identified in each heartbeat The value of

[0099] - In a third step 1100, a graph of the dicrotic notch pressure (ordinate) as a function of the number of progressive heart beats (abscissa) is created ;

[0100] - In step 4 1150, a graph of the dicrotic notch pressure Resampling is performed to obtain the resampled graph of the dicrotic notch pressure. ;

[0101] - In the fifth step 1200, the lower frequency is calculated f 下限 (optionally equal to 0.01Hz) to the upper frequency limit f 上限 (Above the lower frequency limit f 下限 , and optionally a resampled map of the dicrotic notch pressure at a frequency in the range of from 0.4 Hz to 1.2 Hz, more optionally in the range of from 0.8 Hz to 1.2 Hz, still more optionally equal to 1.2 Hz) The power spectrum (optionally by Fourier transformation, more optionally FFT, or by autoregressive modeling or by wavelet transformation), as previously mentioned, depending on the type of object under examination;

[0102] - In step 1250, the resampled image of the dicrotic notch pressure is The power spectrum It is divided into three frequency bands VLF (where the frequency f VLF At the lower frequency f 下限 To the first intermediate frequency f 中间_1 range), LF (where the frequency f LF At the first intermediate frequency f 中间_1 To the second intermediate frequency f 中间_2 range) and HF (where the frequency f HF At the second intermediate frequency f 中间_2 To upper frequencyf 上限 range), and calculate the power spectrum in each of the LF and HF bands The power, that is, the power spectrum in the LF band Power (given as an integral in the LF band, i.e., the power spectrum sum in the discrete frequency domain) and the power spectrum in the HF band Power (given as an integral in the HF band, i.e., the power spectrum sum in the discrete frequency domain); as mentioned above, the first intermediate frequency f 中间_1 and the second intermediate frequency f 中间_2 Depending on the type of examination object: Optionally, the first intermediate frequency f 中间_1 In the range from 0.04 Hz to 0.12 Hz, more optionally in the range from 0.08 Hz to 0.12 Hz, still more optionally equal to 0.12 Hz; optionally, the second intermediate frequency f 中间_2 In the range from 0.15 Hz to 0.45 Hz, more optionally in the range from 0.30 Hz to 0.45 Hz, more optionally equal to 0.45 Hz;

[0103] - In the seventh step 1300, the power spectra in the LF and HF bands are calculated (and output) The ratio between the power The value of , thus:

[0104]

[0105] Therefore, based on the ratio and taking into account the type of population to which the subject belongs, the physician can assess changes in activation of the subject's sympathetic nervous system and changes in activation of the parasympathetic nervous system and the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system.

[0106] Other embodiments of the computer-implemented method according to the present invention may also determine HRV according to conventional techniques, whereby:

[0107] - In the third step 1100, a discrete pressure signal is established Blood flow velocity diagram ;

[0108] - In a fourth step 1150, the discrete pressure signal Blood flow velocity diagram Resampling is performed to obtain a discrete pressure signal Resampled blood flow velocity map ;

[0109] - In a fifth step 1200, the discrete pressure signal is calculated at frequencies between 0.01 Hz and 0.4 Hz Resampled blood flow velocity map The power spectrum (optionally by Fourier transform, more optionally FFT, or by autoregressive modelling or by wavelet transform);

[0110] - In the sixth step 1250, the discrete pressure signal Resampled blood flow velocity map The power spectrum It is divided into three frequency bands VLF_HRV (where the frequency f VLF_HRV in the range from 0.01Hz to 0,04Hz), LF_HRV (where the frequency f LF_HRV in the range from 0.04Hz to 0.15Hz) and HF_HRV (where the frequency f HF_HRV in the range from 0.15 Hz to 0.4 Hz), and calculate the power spectrum in each of the frequency bands LF_HRV and HF_HRV The power, that is, the power spectrum in the LF_HRV band Power (given as an integral in the LF_HR band, i.e., the power spectrum sum in the discrete frequency domain) and the power spectrum in the HF_HRV band Power (given as an integral in the HF_HRV band, i.e., the power spectrum sum in the discrete frequency domain); and

[0111] - In the seventh step 1300, the power spectra in the LF_HRV and HF_HRV bands are calculated (and output) The ratio between the peak frequencies The value of , thus:

[0112]

[0113] Therefore, based on the ratio and taking into account the type of population to which the subject belongs, the physician can assess changes in activation of the subject's sympathetic nervous system and changes in activation of the parasympathetic nervous system and the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system.

[0114] Other embodiments of the computer-implemented method according to the present invention may also:

[0115] - Calculate (optionally in any of the steps from the fifth step 1200 to the seventh step 1300 and output in the seventh step 1300) a resampled map of the systolic duration Standard Deviation and resampled plots of diastolic duration Standard Deviation (and possibly, discrete pressure signals Resampled blood flow velocity Standard Deviation ), and optionally, a resampled map of systolic duration The power spectrum Total power and resampled plots of diastolic duration The power spectrum Total power (and possibly, discrete pressure signals Resampled blood flow velocity map The power spectrum Total power ),

[0116] Therefore, based on the standard deviation and (and possibly the standard deviation ) and optionally also based on the total power and (and total power ) and taking into account the type of population to which the subject belongs, the physician is able to assess changes in activation of the subject's own sympathetic nervous system and changes in activation of the parasympathetic nervous system as well as the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system.

[0117] Other embodiments of the computer-implemented method according to the present invention may create a map of the duration of the systolic phase relative to the duration of the entire heartbeat in the third step 1100. and diastolic duration , expressed as normalized values ​​(e.g., percentage values) of the systolic duration and diastolic duration of each heart beat, rather than absolute values ​​in milliseconds.

[0118] Above, preferred embodiments have been described and various modifications of the present invention have been proposed, but it should be understood that those skilled in the art may make other modifications and changes without departing from the scope of protection as defined in the appended claims.

Claims

1. A computer-implemented method for detecting parameters indicative of changes in activation of a sympathetic nervous system and changes in activation of a parasympathetic nervous system in a subject during a transition from a basal state to a perturbed state, comprising the steps of: A. Receive a discrete pressure signal including multiple heartbeats of the subject ; B. Identifying discrete pressure signals each heartbeat and identifies the systolic phase within each heartbeat and diastolic ; C. Create a graph of systolic duration as a function of the number of incremental heartbeats and a plot of diastolic duration as a function of the number of incremental heartbeats ; D. Implementation of the systolic duration graph The resampling of the systolic duration is obtained. , and the diastolic duration graph The resampling of diastolic duration is obtained ; E. Calculate at the lower frequency limit f 下限 and above the lower frequency limit f 下限 Upper frequency limit f 上限 Resampled plot of systolic duration at frequencies between The power spectrum and resampled plots of diastolic duration The power spectrum ; F. Calculate the power spectrum in the LF band Power , HF band mid-power spectrum Power , power spectrum in LF band Power And the power spectrum in the HF band Power , where the frequency in the LF band is f LF Higher than or equal to the first intermediate frequency f 中间_1 and below the second intermediate frequency f 中间_2 ,thus f 中间_1 ≤ f LF ＜f 中间_2 ， Among them, the lower limit frequency f 下限 Below the first intermediate frequency f 中间_1 , which is lower than the second intermediate frequency f 中间_2 , which is lower than the upper frequency limit f 上限 ,thus f 下限 ＜f 中间_1 ＜ f 中间_2 ＜ f 上限 ， And among them, the frequency in the HF band f HF Higher than or equal to the second intermediate frequency f 中间_2 And below the upper frequency limit f 上限 ,thus f 中间_2 ≤ f HF ＜ f 上限 ;and G. Calculate and output the power spectrum in the LF and HF bands The ratio between the power The values ​​of and the power spectra in the LF and HF bands The ratio between the power The value of ， Therein, steps AG of the computer-implemented method are carried out on the object first in a base state and then in a disturbed state.

2. The computer-implemented method of claim 1, wherein: Lower frequency f 下限 Equal to 0.01Hz, upper limit frequency f 上限 In the range from 0.4 Hz to 1.2 Hz, the first intermediate frequency f 中间_1 In the range from 0.04Hz to 0.12Hz, the second intermediate frequency f 中间_2 In the range from 0.15Hz to 0.45Hz.

3. The computer-implemented method of claim 2, wherein the upper frequency f 上限 In the range from 0.8 Hz to 1.2 Hz, the first intermediate frequency f 中间_1 In the range from 0.08 Hz to 0.12 Hz, the second intermediate frequency f 中间_2 In the range from 0.30Hz to 0.45Hz.

4. The computer-implemented method of claim 2, wherein the upper frequency f 上限 Equal to 1.2Hz, the first intermediate frequency f 中间_1 Equal to 0.12Hz, the second intermediate frequency f 中间_2 Equal to 0.45Hz.

5. The computer-implemented method according to any one of claims 1 to 4, wherein: In step E, the resampled images of the systolic duration are calculated by Fourier transform. The power spectrum and resampled plots of diastolic duration The power spectrum .

6. A computer-implemented method according to any one of claims 1 to 4, wherein: In step E, the resampled images of the systolic duration are calculated by fast Fourier transform. The power spectrum and resampled plots of diastolic duration The power spectrum .

7. A computer-implemented method according to any one of claims 1 to 4, wherein: The discrete pressure signal received in step A Have a duration of at least 3 minutes.

8. The computer-implemented method of claim 7, wherein: The discrete pressure signal received in step A Have a duration of at least 4 minutes.

9. The computer-implemented method of claim 7, wherein: The discrete pressure signal received in step A Have a duration of at least 5 minutes.

10. The computer-implemented method according to any one of claims 1 to 4, wherein: In step B, the systolic and diastolic phases of each heartbeat are identified based on the identification of the dicrotic notch time.

11. The computer-implemented method of claim 10, wherein: - In step B, further identify the dicrotic notch pressure in each heartbeat The value of - In step C, a graph of the dicrotic notch pressure as a function of the number of progressive heartbeats is further created ; - In step D, further analysis of the dicrotic notch pressure Resampling is performed to obtain the resampled graph of the dicrotic notch pressure. ; - In step E, further calculation is performed at the lower frequency limit f 下限 and upper frequency f 上限 Dicrotic notch pressure at frequencies between Resampling diagram of The power spectrum ; - In step F, the power spectrum in the LF band is further calculated Power and the power spectrum in the HF band Power ; and - In step G, the power spectra in the LF and HF bands are further calculated and output The ratio between the power The value of , thus: 。 12. A computer-implemented method according to any one of claims 1 to 4, wherein in step C, a map of systolic duration is created by expressing the systolic duration and the diastolic duration of each heartbeat as normalized values ​​to the overall duration of the considered heartbeat. and diastolic duration .

13. The computer-implemented method of any one of claims 1 to 4, further comprising determining and outputting a subject's heart rate variability first in a basal state and then in a perturbation state.

14. The computer-implemented method according to any one of claims 1 to 4, wherein a resampled map of the systolic duration of the subject first in a basal state and then in a perturbation state is further calculated. Standard Deviation and resampled plots of diastolic duration Standard Deviation , and output them in step G.

15. The computer-implemented method according to any one of claims 1 to 4, wherein a resampled map of the systolic duration of the subject first in a basal state and then in a perturbation state is further calculated. The power spectrum Total power and resampled plots of diastolic duration The power spectrum Total power , and output them in step G.

16. An apparatus comprising a processing unit configured to perform a computer-implemented method according to any one of claims 1 to 15 for detecting parameters indicative of changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system of a subject in a transition from a basal state to a perturbed state.

17. A computer program product comprising instructions which, when executed by one or more processing units, cause the one or more processing units to perform a computer-implemented method for detecting parameters indicating changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system of an object in a transition from a basal state to a disturbed state according to any one of claims 1 to 15.

18. A computer-readable medium having instructions stored thereon which, when executed by one or more processing units, cause the one or more processing units to perform a computer-implemented method for detecting parameters indicating changes in activation of the sympathetic nervous system and changes in activation of the parasympathetic nervous system of an object in a transition from a basal state to a disturbed state according to any one of claims 1 to 15.

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