Method for detecting parameters indicating activation of the sympathetic nervous system and the parasympathetic nervous system

Abstract

A computer-implemented method for detecting parameters indicative of fluctuations in activation of the sympathetic nervous system and the parasympathetic nervous system of a subject as they transition from a basal state to a perturbed state, the method comprising calculating a power ratio between the power in the LF and HF bands of the power spectra of systolic and diastolic time intervals.

Description

Technical Field

[0001] The present invention relates to a computer-implemented method for detecting parameters indicating fluctuations in sympathetic nervous system activation and fluctuations in parasympathetic nervous system activation in a subject transitioning from a basic state (hereinafter also referred to as a basal state) to a perturbed state, and it is also possible to evaluate fluctuations in the balance between sympathetic nervous system activation and parasympathetic nervous system activation therefrom. Further, thereby, this method provides an index for identifying whether the balance between sympathetic nervous system activation and parasympathetic nervous system activation of a subject transitioning from a basal state to a perturbed state is appropriate. This computer-implemented method can show the influence on the interaction between the sympathetic nervous system and the parasympathetic nervous system when the subject himself / herself transitions from a basal state to a perturbed state, for example, the influence by the application of a drug and / or the change in the posture of the subject himself / herself, in a simple, general-purpose, efficient, and highly reliable manner.

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

[0003] The method according to the present invention is a computer-implemented method, where the term "computer" means any processing device (in particular, at least one microprocessor), and when executed by the apparatus according to the present invention, this processing device executes a set of one or more computer programs including instructions for causing the same apparatus to execute a computer-implemented method for detecting activation of the vagus nerve system. Further, this set of one or more computer programs can be stored in a set of one or more computer-readable media.

Background Art

[0004] It is known that the heart rate can be defined as the average heart rate per minute. This value, for example, 70 beats per minute (b / m), is an average value because the time between one heartbeat and the next is actually not constant but continuously changing. Heart rate variability (HRV), also known as such, is a parameter useful for evaluating the health status of a subject. In fact, the measurement and analysis of HRV are becoming increasingly important, and it is possible to infer a lot of information from this measurement, thereby enabling, for example, the assessment of the risk of arrhythmia and heart attack, or the determination of whether the balance between the activities of the sympathetic nervous system (known as the orthosympathetic nervous system) and the parasympathetic nervous system is appropriate. In this regard, the evaluation of HRV has been limited to the cardiovascular area, but recent numerous scientific studies have shown its importance as a reliable indicator in many other application areas.

[0005] HRV is known to be the natural variation of the heart rate in response to factors such as respiratory rhythm, emotions such as anxiety, stress, anger, and relaxation. In a healthy heart, the heart rate responds quickly to all these factors, changes according to the situation, and can adapt well to various situations the body encounters. Generally, healthy subjects have high heart rate variability, specifically showing appropriate psychophysiological adaptability to various situations.

[0006] HRV is related to the interaction between the sympathetic and parasympathetic nervous systems, and as a result, it affects the functions of the body's organs and systems such as the cardiovascular and respiratory systems.

[0007] When the sympathetic nervous system is activated, a series of effects occur, such as an acceleration of the heart rate, dilation of the bronchi, an increase in blood pressure, constriction of the peripheral blood vessels, dilation of the pupils, and an increase in sweating. The chemical mediators of these autonomic responses are norepinephrine, adrenaline, corticotropin, and some adrenal cortical hormones. The sympathetic nervous system is the normal response of the body to situations of alertness, struggle, physical and / or emotional stress (also known as the "fight or flight" response).

[0008] Conversely, when the parasympathetic nervous system (vagal tone, i.e., also expressed through vagal activity or vagal nerve activity) is activated, bradycardia, increased bronchial muscle tone, vasodilation, decreased pressure, slowed breathing, increased muscle relaxation, calming and deepening of breathing, warming of the genitals and extremities, etc. are said to occur. This acts through acetylcholine, a typical chemical mediator. The parasympathetic nervous system represents the normal reaction of the body to a state of calm, rest, quiet, and absence of danger or (physical and mental) stress.

[0009] The organs of the subject are always in a situation determined by the balance or dominance of either one of these two nervous systems (i.e., the sympathetic nervous system and the parasympathetic nervous system). The ability to change one's own balance by activating either one of the nervous systems is very important and is a basic mechanism for adjusting the dynamic balance of the organs from physiological and psychological perspectives.

[0010] By evaluating HRV, the relative balance state between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system can be evaluated. This is of great significance in evaluating when and how these two systems reach an optimal balance in specific situations and / or specific types of patients (both healthy and pathological patients).

[0011] Generally, HRV is evaluated by measuring it using an electrocardiogram device, also called an ECG or EKG, equipped with conventional surface electrodes worn at the level of the heart to detect the electrical activity of the heart (see, for example, "Naming of the Waves in the ECG, With a Brief Account of Their Genesis" by J.W. Hurst in Circulation, vol. 98, no 18, 3 November 1998, pp. 1937 - 42), in which very complex dedicated software related thereto analyzes the data by identifying individual heartbeats and thus their variations. By way of example, but not limited to, examples of such software are available from Elemaya of Italy (see www.elemaya.it) and Kubios Oy of Finland (www.kubios.com). In particular, after digitization, the data are analyzed by software in a computer - implemented manner. This software calculates the time distance (usually expressed in milliseconds) between each heartbeat and the next by measuring the time distance between the R - peaks of the ECG signal, and then constructs a diagram called a tachogram that represents the trend of the RR distance (vertical axis), usually expressed in milliseconds, as a function of the number of heartbeats elapsed (horizontal axis). Tachograms are typically created at intervals of 4 - 5 minutes (i.e., for a total of approximately about 300 heartbeats).

[0012] Thereafter, the software performs resampling of the tachogram and then performs a Fourier transform to obtain a power spectrum, i.e., to obtain the power spectral density, also shown as the PSD of the tachogram resulting from the resampling operation (see, for example, in "Heart Rate Variability Spectrum: Physiologic Aliasing and Nonstationarity Considerations" by J. Pucik et al., Trends in Biomedical Engineering Conference paper, Bratislava, September 16 - 18, 2009).

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

[0014] Recent research and investigations (for example, in "Heart rate variability in athletes" by A.E. Aubert et al., Sports Medicine 33 (12): 889 - 919, 2003) have distinguished what are next shown as three sub - frequency bands respectively. - VLF (Very Low Frequency) band, at frequencies from 0.01 Hz to 0.04 Hz, depends on changes in thermoregulation, is psychologically affected by states of worry and obsessive thoughts (worry and rumination), and is only slightly caused by sympathetic nervous system activity. - LF (Low Frequency) band, at frequencies from 0.04 Hz to 0.15 Hz, is considered to be mainly caused by sympathetic nervous system activity and baroreceptor regulation. - HF (High Frequency) band, at frequencies from 0.15 Hz to 0.4 Hz, for parasympathetic nervous system activity 、 Therefore, it is considered to be an expression of the basic component constituted by vagus nerve activity. In particular, the HF band is strongly affected by the rhythm and depth of breathing. Thus, when the rhythm and / or depth of breathing changes, the contribution of the HF band to the power spectrum PSD of the tachogram increases. 、 The relationship between sympathetic nervous system activation and parasympathetic nervous system activation is evaluated by the LF / HF ratio of the power of the tachogram in the LF band and the power of the tachogram in the HF band (which may also be normalized by their sum). In particular, in the literature, power values are often expressed logarithmically.

[0015]

[0016] ​Finally, the software can also calculate the standard deviation SD and / or the total power (which may be in logarithmic form) of the tachogram, and the total power is generally set equal to the square of the standard deviation of the tachogram (for example, by A.E. Aubert et al. cited above). All of these parameters represent the overall degree of HRV, and thus represent the overall activation of the sympathetic and parasympathetic nervous systems.

[0017] In this field, further research on the analysis of the variation of systolic and diastolic time distances based on ECG and phonocardiogram signals (PCG), and its correlation with HRV for the evaluation of cardiovascular nonlinear dynamics has been conducted by Chengyu Liu et al. in the following literature: "Systolic and Diastolic Time Interval Variability Analysis and Their Relations with Heart Rate Variability", BIOINFORMATICS AND BIOMEDICAL ENGINEERING, 2009, ICBBE2009. 3RD INTERNATIONAL CONFERENCE ON, IEEE, PISCATAWAY, NJ, USA, 11 June 2009 (2009-06-11), pages 1-4, XP031489349, ISBN: 978-1-4244-2901-1. Also, research on the comparability between the respiratory variation of systolic and diastolic time intervals within the radial artery waveform and dynamic indices has been conducted by Park Ji Hyun et al. in the following literature: "Respiratory variation of systolic and diastolic time intervals within radial arterial waveform: a comparison with dynamic preload index", JOURNAL OF CLINICAL ANESTHESIA, BUTTERWORTH PUBLISHERS, STONEHAM, GB, vol.32, 24 March 2016 (2016-03-24), pages 75-81, XP029596121, ISSN: 0952-8180, DOI: 10.1016 / J.JCLINANE.2015.12.022.

[0018] Based on recent clinical experience, it is also possible to define a reference range for the values of the above parameters, namely, the heart rate, the standard deviation SD of the tachogram, the total power of the tachogram, the power of the tachogram in the VLF band, the power of the tachogram in the LF band, and the power of the tachogram in the HF band. The definition of the reference range is not exactly the same among different authors or between the standards in the United States and Europe. However, in the context of prior art software, the reference range obtained based on experiments related to the population under consideration (for example, in the case of research and surveys conducted on Italian subjects, those of the Italian population) is adopted.

[0019] Furthermore, different reference ranges are introduced for the elderly (50 - 70 years old) and the young (20 - 50 years old).

[0020] However, the prior art methods for evaluating the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system based on the HRV still have the annoying problem that the interpretation of the results obtained from the analysis of the measured values performed is not unified. For example, in the literature, there are greatly different, if not conflicting, indicators regarding the time interval for which the analysis must be performed (i.e., the data collection for constructing the tachogram to be analyzed) and the indicators regarding the pathological conditions of the subjects referring to the results obtained from the analysis of the measured values performed on a single subject.

[0021] The object of the present invention is, therefore, to enable 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 to be evaluated in a simple, highly versatile, efficient, and reliable manner. Thereby, it is possible to show the influence on the interaction between the sympathetic and parasympathetic nervous systems of the subject himself / herself during the transition from the basal state to the perturbed state. For example, it is possible to judge the influence of the application of drugs or the change in the posture of the subject himself / herself on this interaction.

Summary of the Invention

Means for Solving the Problems

[0022] A particular object of the present invention is to provide a computer-implemented method for detecting parameters indicative of variations in sympathetic and parasympathetic nervous system activation in a subject during a transition from a basal state to a perturbed state, the computer-implemented method comprising: A. Discrete pressure signal p(t i ) and B. Discrete pressure signal p(t i ) and within each beat, identify the systolic phase p sys (t i ) and diastolic phase p dia (t i ) and C. Diagram of the duration of the systolic phase as a function of heart rate. sys and diagram D of the duration of the diastolic phase as a function of heart rate. dia and D. Diagram of the duration of the systolic phase sys and generate a resampled diagram of the systolic phase duration D sys (r) Obtain the diagram of the duration of the diastolic phase D dia and generate a resampled diagram of the diastolic phase duration D dia (r) and E. Resampled diagram of the duration of the systolic phase D sys (r) Power spectrum PSD of sys and the lower limit frequency f lower_limit and the lower limit frequency f lower_limit Higher upper frequency f upper_limit Resampled diagram of diastolic phase duration at frequencies between dia (r) Power spectrum PSD of dia Calculating F. LF band power spectrum PSD sys Power of P LF (PSDsys) , HF band power spectrum PSD sys Power of PHF (PSDsys) and the power spectrum PSD in the LF band dia of power P LF (PSDdia) and the power spectrum PSD in the HF band dia of power P HF (PSDdia) are calculated, wherein the frequency f in the LF band LF is greater than or equal to the first intermediate frequency f intermediate_1 and less than the second intermediate frequency f intermediate_2 and is represented by the following formula f intermediate_1 ≦f LF <f intermediate_2 wherein the lower limit frequency f lower_limit is less than the first intermediate frequency f intermediate_1 the first intermediate frequency f intermediate_1 is less than the second intermediate frequency f intermediate_2 the second intermediate frequency f intermediate_2 is less than the upper limit frequency f upper_limit and is represented by the following formula f lower_limit <f intermediate_1 <f intermediate_2 <f upper_limit wherein the frequency f in the HF band HF is greater than or equal to the second intermediate frequency f intermediate_2 and less than the upper limit frequency f upper_limit and is represented by the following formula f intermediate_2 ≦f HF <f upper_limit G. The ratio LHR between the powers of the LF band and the HF band of the power spectrum PSD sys and the value of the ratio LHR between the powers of the LF band and the HF band of the power spectrum PSD sys i.e., dia the ratio LHR between the powers of the LF band and the HF band of the power spectrum PSD dia i.e., LHR sys =P LF (PSDsys) / P HF (PSDsys) LHR dia =PLF (PSDdia) / P HF (PSDdia) calculating and outputting what is indicated by; Steps A through G of the computer-implemented method are first executed on the subject in a baseline state and then in a perturbed state.

[0023] According to another aspect of the present invention, the lower frequency f lower_limit may be equal to 0.01 Hz, and the upper frequency f upper_limit may be in the range of 0.4 Hz to 1.2 Hz, the first intermediate frequency f intermediate_1 may be in the range of 0.04 Hz to 0.12 Hz, the second intermediate frequency f intermediate_2 may be in the range of 0.15 Hz to 0.45 Hz, the upper frequency f upper_limit may be in the range of 0.8 Hz to 1.2 Hz, the first intermediate frequency f intermediate_1 may be in the range of 0.08 Hz to 0.12 Hz, the second intermediate frequency f intermediate_2 may be in the range of 0.30 Hz to 0.45 Hz, and further, the upper frequency f upper_limit may be equal to 1.2 Hz, the first intermediate frequency f intermediate_1 may be equal to 0.12 Hz, and the second intermediate frequency f intermediate_2 may be equal to 0.45 Hz.

[0024] According to a further aspect of the present invention, in step E, the power spectra PSD sys and PSD dia can be calculated respectively through the Fourier transform of the resampled diagram D sys (r) of the duration of the systolic phase and the resampled diagram D dia (r) of the duration of the diastolic phase, and may be calculated through a fast Fourier transform (FFT).

[0025] According to an additional aspect of the present invention, the discrete pressure signal p(t received in step A i) has a duration of at least 3 minutes, may have a duration of 4 minutes, and may have a duration of at least 5 minutes.

[0026] According to another aspect of the present invention, in step B, based on the identified overlapping upstroke times, the systolic and diastolic phases of each heartbeat can be identified.

[0027] According to a further aspect of the present invention, the computer-implemented method is - In step B, further, the value of the overlapping upstroke pressure P dic in each heartbeat is identified, - In step C, further, a diagram D dic of the overlapping upstroke pressure as a function of the number of heartbeats is constructed, - In step D, further, resampling of the diagram D dic of the overlapping upstroke pressure is performed to obtain a resampled diagram D dic (r) of the overlapping upstroke pressure, - In step E, further, the power spectrum PSD lower_limit of the resampled diagram D upper_limit of the overlapping upstroke pressure at frequencies between the lower frequency f dic (r) and the upper frequency f dic is calculated, - In step F, further, the power P dic of the power spectrum PSD LF (PSDdic) in the LF band and the power P dic of the power spectrum PSD HF (PSDdic) in the HF band are further calculated, - In step G, the ratio LHR dic between the powers in the LF and HF bands of the power spectrum PSD dic is determined, that is, LHR dic = P LF (PSDdic) / P HF (PSDdic) It is possible to calculate and output what is shown by

[0028] According to an additional aspect of the present invention, in step C, a diagram D of the duration of the systolic phase sys and a diagram D of the duration of the diastolic phase dia can be constructed by expressing the durations of the systolic and diastolic phases of each heartbeat as values normalized to the overall period of the heartbeat being analyzed.

[0029] 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.

[0030] According to a further aspect of the present invention, the computer-implemented method may further include the standard deviation SD of the resampled diagram D of the duration of the systolic phase sys (r) of (sys) and the standard deviation SD of the resampled diagram D of the duration of the diastolic phase dia (r) of (dia) which can be calculated and the values of those for the subject in the basal state first and then in the perturbed state can be output in step G.

[0031] According to an additional aspect of the present invention, the computer-implemented method may further include the total power TP of the power spectrum PSD sys (r) of the resampled diagram D of the duration of the systolic phase sys of (sys) and the total power TP of the power spectrum PSD dia (r) of the resampled diagram D of the duration of the diastolic phase dia of (dia) which can be calculated and the values of those for the subject in the basal state first and then in the perturbed state can be output in step G.

[0032] Another specific object of the present invention is, as described above, a processing apparatus configured to execute a computer-implemented method for detecting parameters indicating fluctuations in sympathetic nervous system activation and fluctuations in parasympathetic nervous system activation in a subject during the transition from a basal state to a perturbed state.

[0033] A further specific object of the present invention is one or more computer program sets including instructions that, when executed by one or more processing units, cause the one or more processing units to execute a computer-implemented method for detecting parameters indicating fluctuations in sympathetic nervous system activation and fluctuations in parasympathetic nervous system activation in a subject during the transition from a basal state to a perturbed state, as described above.

[0034] A further specific object of the present invention is a set of one or more computer-readable media having stored thereon the above-described one or more computer program sets.

[0035] The computer-implemented method and related apparatus of the present invention can provide a reliable index for discriminating fluctuations in sympathetic nervous system activation and fluctuations in parasympathetic nervous system activation by separately analyzing the systolic and diastolic phases of the cardiac pressure cycle (e.g., arterial pressure, pulmonary venous pressure, central venous pressure, etc.) in a subject transitioning from a basal state to a perturbed state, and can also make it possible to discriminate whether the balance between sympathetic nervous system activation and parasympathetic nervous system activation is appropriate. Thereby, for example, the effects of drug application or changes in the subject's own posture on the sympathetic and parasympathetic nervous systems can be specified.

Best Mode for Carrying Out the Invention

[0036] Next, the present invention will be described, for illustrative but not limiting purposes, with particular reference to the accompanying FIG. 1 showing a flowchart of a preferred embodiment of the computer-implemented method according to the present invention, according to its preferred embodiments.

[0037] The inventor has surprisingly found that it is possible to utilize the coupling between the heart and the arterial system in order to obtain more information not only about the activation of the sympathetic nervous system and the parasympathetic nervous system of a subject, but also about their balance, based on the fluctuations of the heartbeat. For this reason, unlike the detection techniques based on ECG, the computer-implemented method according to the present invention is based on the cardiac pressure cycle. The computer-implemented method according to the present invention utilizes the "mechanical" characteristic that the heartbeat is composed of two main phases, the systolic phase and the diastolic phase.

[0038] In contrast to this method, the prior art methods and devices using ECG signal detection are based on the cardiac cycle of electrical signals. Since the electrical signals of the cardiac cycle only correspond to the electrical elements of the electromechanical cardiac activity for circulating blood inside the human body, they are insufficient to provide all the available information regarding the balance between the sympathetic nervous system and the parasympathetic nervous system. This is because much of this information is actually related to the mechanical elements of the cardiac activity that circulates the blood. In fact, the electrical signals sent to the heart do not immediately cause the mechanical reaction of the heart itself, which also depends on the inertia of the heart and the circulatory system, that is, the specific state of the rigidity and adaptation of the various systems forming the circulatory system. This means that the prior art methods and devices that employ the detection of ECG signals to evaluate HRV are subject to the influence of errors and approximations that greatly limit their reliability. For example, without being limited to this example, if the aortic valve does not open correctly and there are problems with the electromechanical coupling between the heart and the cardiovascular and respiratory systems, only the electrical component of the cardiac activity will show that the mechanical function of the heart is severely impaired, and as a result, while the sympathetic nervous system and the parasympathetic nervous system are activated in an unbalanced manner with respect to each other, an ECG signal may be provided that indicates an appropriate heart rate through the detection of the electrical activity of the heart; this applies to all cases where there is a qualitative separation between the electrical and mechanical elements of the cardiac activity.

[0039] The computer-implemented method according to the present invention can obtain the detection of parameters indicating the variations in the activation of the sympathetic and parasympathetic nervous systems by separately analyzing the variations in the duration of the systolic and diastolic phases of the cardiac cycle of pressure. Further, by this method, it is possible to evaluate the change in the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system, and to make a reliable evaluation of the degree of activation and the balance thereof of the sympathetic and parasympathetic nervous systems. In fact, since the cardiac cycle of pressure has a typical pressure pattern in which the systolic and diastolic phases are clearly defined, not only the contribution to the entire cardiac cycle as in the evaluation of HRV through the analysis of the tachogram based on the R-R interval of the ECG signal by the prior art method, but also the contribution to the same systolic and diastolic phases can be identified and quantified. Hereinafter, the variability of the duration of the systolic phase of the pressure signal will be denoted as SYS-V, and the variability of the duration of the diastolic phase of the pressure signal will be denoted as DIA-V.

[0040] In particular, with respect to the balance evaluated by detecting the HRV of the entire cardiac cycle based on the ECG signal by the prior art method, the individual analysis of SYS-V and DIA-V implemented by the computer-implemented method according to the present invention shows that in one or both of the systolic and diastolic phases, it is possible to detect parameters indicating that the variations in 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 are different.

[0041] For example, without limitation, for each of three subjects, namely an athlete, a heart disease patient, and a normal subject, the same HRV may correspond to different pairs of SYS-V and DIA-V. In fact, generally, even when there is no change in the R-R interval of the ECG signal over a plurality of cardiac cycles, a change with opposite signs may occur in the duration of the systolic phase and the duration of the diastolic phase over the same plurality of cardiac cycles by the organ adapting to the specific conditions it is experiencing. Therefore, these two fluctuations in the systolic and diastolic phases can represent the contributions of different activations of the sympathetic nervous system and the parasympathetic nervous system, and thus, the analysis of SYS-V and DIA-V can provide more specific information about such contributions. Similarly, when the heart rate of a subject is constant before and after an event, the two mechanical phases that form it, namely the systolic phase and the diastolic phase, may change. In this way, by the computer-implemented method according to the present invention, for example, by intervening in the component of the activation of the parasympathetic nervous system that affects and changes the component of the activation of the sympathetic nervous system, such as the administration of a vasoconstrictor or a vasodilator or a cardiotonic agent, it becomes possible to pre-identify whether it is necessary to cause a change in the contribution of the activation of the sympathetic nervous system to the contribution of the activation of the parasympathetic nervous system.

[0042] As a result, the degree of the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system due to some pathological reactions such as stress caused by drugs and surgery could not be correctly identified by the prior art techniques based on the detection of the ECG signal for HRV measurement, but will be reliably evaluated by the analysis of SYS-V and DIA-V performed by the computer-implemented technique according to the present invention. In particular, through the analysis of SYS-V and DIA-V, the computer-implemented method according to the present invention can make it possible to identify at an early stage some pathological conditions that have not yet been clarified, while the prior art methods can only identify them after their modification.

[0043] FIG. 1 shows a flowchart of a preferred embodiment of the computer-implemented method according to the present invention.

[0044] In a first step 1000, the method receives a discrete pressure signal p(t i )(e.g., arterial pressure or pulmonary venous pressure or central venous pressure, etc.) of a subject or patient including a plurality of heartbeats. In particular, the discrete pressure signal p(t i ) is a signal detected via a pressure sensor and is derived from a continuous pressure signal p(t) that has been digitized to obtain the discrete pressure signal p(t i )(where the index i indicates successive values of discrete samples), or may be derived from a discrete signal stored in a storage medium (i.e., already digitized). In particular, the detection of the continuous pressure signal p(t) can be performed invasively or non-invasively via, for example, a photoelectric sensor. The received discrete pressure signal p(t i ) has a duration of at least optionally 3 minutes, more optionally at least 4 minutes, and further optionally at least 5 minutes.

[0045] In a second step 1050, the method identifies each heartbeat of the discrete pressure signal p(t i ) and, within each heartbeat, identifies the systolic phase p sys (t i ) and the diastolic phase p dia (t i ). Optionally, the method performs the identification of each heartbeat via the automatic heartbeat identification method described in WO2004 / 084088Al and / or the identification of the systolic and diastolic phases of each heartbeat based on the identification of the overlapping upstroke time (corresponding to the aortic valve closure time for the arterial pressure signal or the tricuspid valve closure time for the pulmonary pressure signal).

[0046] In a third step 1100, the method constructs a diagram D sys of the duration of the systolic phase (vertical axis) as a function of the number of heartbeats progressed (horizontal axis) and a diagram D dia of the duration of the diastolic phase (vertical axis) as a function of the number of heartbeats progressed (horizontal axis). The durations of the systolic and diastolic phases may be expressed in milliseconds.

[0047] In a fourth step 1150, the method is the diagram D of the duration of the systolic phase sysand the diagram D of the duration of the diastolic phase dia Execute resampling of (which were constructed in the third step 1100), and the resampled diagram D of the duration of the systolic phase sys (r) and the resampled diagram D of the duration of the diastolic phase dia (r) to obtain.

[0048] In the fifth step 1200, the method is the resampled diagram D of the duration of the systolic phase sys (r) of the power spectrum PSD sys , and the resampled D of the duration of the diastolic phase dia (r) of the power spectrum PSD dia to be calculated between a lower frequency f which may be equal to 0.01 Hz lower_limit and an upper frequency f which may be 0.4 Hz to 1.2 Hz, further may be in the range of 0.8 Hz to 1.2 Hz, and further may be equal to 1.2 Hz upper_limit (greater than the lower frequency f lower_limit ). In particular, the lower frequency f lower_limit , and the upper frequency f upper_limit depend on the type of the subject being examined. Optionally, the method is the resampled diagram D of the duration of the systolic phase sys (r) , and the resampled diagram D of the duration of the diastolic phase dia (r) of the Fourier transform, more optionally, through the fast Fourier transform (FFT), to calculate the power spectrum PSD sys and PSD dia respectively. Instead of the Fourier transform, other embodiments of the computer-implemented method according to the present invention can calculate the power spectrum PSD sys and PSD dia through autoregressive modeling or through wavelet transform.

[0049] In the sixth step 1250, the method is the power spectrum PSD sys and PSD dia each of which is subdivided into three frequency bands: VLF (very low frequency), LF (low frequency), and HF (high frequency). In the LF band, the frequency f LF is in the range from the first intermediate frequency f intermediate_1 to the second intermediate frequency f intermediate_2 and is represented by the following formula, f intermediate_1 ≦f LF <f intermediate_2 The lower frequency f lower_limit is smaller than the first intermediate frequency f intermediate_1 and the first intermediate frequency f intermediate_1 is smaller than the second intermediate frequency f intermediate_2 and the second intermediate frequency f intermediate_2 is smaller than the upper frequency f upper_limit and is represented by the following formula. f lower_limit <f intermediate_1 <f intermediate_2 <f upper_limit

[0050] The frequency f HF in the HF band is in the range from the second intermediate frequency f intermediate_2 to the upper frequency f upper_limit and is represented by the following formula. f intermediate_2 ≦f HF <f upper_limit

[0051] The frequency f VLF in the VLF band is in the range from the lower frequency f lower_limit to the first intermediate frequency f intermediate_1 and is represented by the following formula. f lower_limit ≦f VLF <f intermediate_1

[0052] The first intermediate frequency f intermediate_1 and the second intermediate frequency f intermediate_2 also depend on the type of the subject under examination. Optionally, the first intermediate frequency fintermediate_1 is in the range of 0.04 Hz to 0.12 Hz, more optionally in the range of 0.08 Hz to 0.12 Hz, and even more optionally equal to 0.12 Hz, the second intermediate frequency f intermediate_2 is in the range of 0.15 Hz to 0.45 Hz, more optionally in the range of 0.30 Hz to 0.45 Hz, and even more optionally equal to 0.45 Hz.

[0053] Further, in the sixth step 1250, the method calculates the power spectrum PSD sys and PSD dia for each of the powers, that is, - the power P in the LF band of the power spectrum PSD sys (given by the integral value in the LF band, that is, the sum in the discretized domain of the frequencies of the power spectrum PSD LF (PSDsys) ) sys ) - the power P in the HF band of the power spectrum PSD sys (given by the integral value in the HF band, that is, the sum in the discretized domain of the frequencies of the power spectrum PSD HF (PSDsys) ) sys ) - the power P in the LF band of the power spectrum PSD dia (given by the integral value in the LF band, that is, the sum in the discretized domain of the frequencies of the power spectrum PSD LF (PSDdia) ) dia ) - the power P in the HF band of the power spectrum PSD dia (given by the integral value in the HF band, that is, the sum in the discretized domain of the frequencies of the power spectrum PSD HF (PSDdia) ) dia ) and calculates.

[0054] In the seventh step 1300, the method calculates the power spectrum PSD sys and PSDdia The ratio LHR between the powers in the LF and HF bands of sys and LHR dia values, i.e., LHR sys = P LF (PSDsys) / P HF (PSDsys) LHR dia = P LF (PSDdia) / P HF (PSDdia) are each calculated (and output) as indicated.

[0055] Based on the ratio LHR sys and LHR dia values output in the seventh step 1300, considering the type of group to which the subject belongs, the doctor can evaluate the fluctuations in the activation of the sympathetic nervous system and the fluctuations in the activation of the parasympathetic nervous system, and from this, it is also possible to evaluate the fluctuations in the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system of the subject himself / herself (i.e., the possibility that the activation of the sympathetic nervous system or the activation of the parasympathetic nervous system becomes dominant over the other). In particular, the ratio LHR sys and LHR dia values depend on what age group and disease state group the subject being examined belongs to.

[0056] That is, the computer-implemented method according to the present invention analyzes the systolic phase and diastolic phase within each cardiac cycle and utilizes the characteristics of the mechanical response of the cardiovascular system to electrical stimulation of the heart. Thereby, the dynamic components of the activation of the sympathetic nervous system and the parasympathetic nervous system and the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system give different indices of dynamic balance between the two systolic phases and diastolic phases, providing more detailed information about stress and vagus nerve activation, so that a more reliable evaluation than the prior art methods becomes possible.

[0057] The inventor applied the computer-implemented method according to the present invention to obtain results, and conducted several evaluations by comparing the results with those obtained by the prior art methods in the evaluation of HRV. In particular, an experiment was conducted on subjects who shifted from the basal state to a perturbed state in which the cardiovascular system changed due to an event.

[0058] The experiment shows that the characteristics of the variation of HRV may either match or not match the characteristics of the resampled diagram D of the diastolic phase duration (however, the absolute values are not equal), and the characteristics of the variation of the resampled diagram D of the systolic phase duration dia (r) are, in many cases, significantly different from the characteristics of HRV. sys (r) Regarding the results obtained for subjects in whom a perturbed state was induced by the administration of a potent anesthetic with a sympathetic nerve inhibitory effect (i.e., propofol (registered trademark)), several evaluations were conducted. In conventional physiology, it was supposed that the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system changes because vagal activity is activated and thereby the activity of the sympathetic nervous system is inhibited, so the ratio between the LF component and the HF component should decrease. However, there is variation in the characteristics of HRV, and contradictory results were obtained in that the ratio between the LF component and the HF component of the power spectrum PSD of the tachogram decreased in some subjects and increased in some subjects, indicating that the power spectrum PSD of the tachogram cannot correctly distinguish the activation of the vagus nerve and the inhibition of the sympathetic nervous system. In contrast, the ratio LHR

[0059] obtained from the resampled diagram D of the systolic phase duration decreased in all patients and was able to reliably distinguish the predominance of the activation of the parasympathetic nervous system with respect to the basal state (i.e., the state not changed by the administration of the anesthetic). sys (r) from sys was

[0060] Generally, to evaluate which of the sympathetic nervous system and the parasympathetic nervous system is predominantly activated from the results obtained by applying the computer-implemented method according to the present invention, the ratio LHR sys and LHR dia It has been clarified that the fluctuations of should be compared according to the type of subject examined. For example, depending on the type of subject, if the fluctuations are inconsistent, the activation of the parasympathetic nervous system prevails over the activation of the sympathetic nervous system, and if the fluctuations are consistent (for example, both increase), the activation of the sympathetic nervous system prevails over the activation of the parasympathetic nervous system.

[0061] In a patient under examination (for example, a patient with orthostatic intolerance causing fainting or a patient with liver cirrhosis), when data regarding the basal state is not available, the evaluation of the fluctuation of the activation of the sympathetic nervous system, the fluctuation of the activation of the parasympathetic nervous system, and the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system is performed by executing the computer-implemented method according to the present invention with the patient lying on the examination table, using this as the basal state, performing a so-called tilt test (that is, tilting the examination table by 60 degrees) on the patient, using this as the perturbed state, and executing the computer-implemented method according to the present invention again. For a patient suffering from liver cirrhosis, it is sufficient to use the movement from the supine position to the standing position as the perturbed state.

[0062] The computer-implemented method according to the present invention is not a diagnostic method per se, but a method for detecting parameters such as the fluctuation of the activation of the sympathetic nervous system, the fluctuation of the activation of the parasympathetic nervous system, and the ratio LHR sys and LHR dia indicating the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system of a subject transitioning from the basal state to the perturbed state, and a substantial interpretation by a doctor is required for diagnosis.

[0063] The following other embodiments of the computer-implemented method according to the present invention are - In the second step 1050, specifying the value of the overlapping bulge pressure P dic at each heartbeat, - In the third step 1100, construct a diagram D of the overlapping bulge pressure (vertical axis) as a function of the heart rate progression number (horizontal axis). dic - In the fourth step 1150, perform resampling of the diagram D of the overlapping bulge pressure dic to obtain a resampled diagram D of the overlapping bulge pressure dic (r) - In the fifth step 1200, calculate the power spectrum PSD lower_limit of the resampled diagram D of the overlapping bulge pressure at frequencies between a lower frequency (optionally equal to 0.01 Hz) and an upper frequency (greater than the lower frequency f dic (r) and optionally in the range of 0.4 Hz to 1.2 Hz, more optionally in the range of 0.8 Hz to 1.2 Hz, and even more optionally equal to 1.2 Hz), where the frequency depends on the type of subject being examined as described above dic (optionally through a Fourier transform, more optionally through an FFT, an autoregressive model, or a wavelet transform), - In the sixth step 1250, divide the power spectrum PSD dic (r) of the resampled diagram D of the overlapping bulge pressure dic into three frequency bands: the VLF band (where the frequency f VLF is in the range from the lower frequency f lower_limit to the first intermediate frequency f intermediate_1 ), the LF band (where the frequency f LF is in the range from the first intermediate frequency f intermediate_1 to the second intermediate frequency f intermediate_2 ), and the HF band (where the frequency f HF is in the range from the second intermediate frequency f intermediate_2 to the upper frequency f upper_limit ), and in each of the LF band and the HF band, calculate the power of the power spectrum PSD dic , that is, the power P sys of the power spectrum PSD LF (PSDdic) ​​(Integration in the LF band, i.e., the sum in the discretized domain of the frequencies of the power spectrum PSD dic ), and the power spectrum PSD sys of the power P HF (PSDdic) (Integration in the HF band, i.e., the sum in the discretized domain of the frequencies of the power spectrum PSD dic ), are calculated, provided that, as described above, the first intermediate frequency f intermediate_1 and the second intermediate frequency f intermediate_2 depend on the type of subject. Optionally, the first intermediate frequency f intermediate_1 is in the range of 0.04 Hz to 0.12 Hz, more optionally in the range of 0.08 Hz to 0.12 Hz, further optionally equal to 0.12 Hz, and optionally, the second intermediate frequency f intermediate_2 is in the range of 0.15 Hz to 0.45 Hz, more optionally in the range of 0.30 Hz to 0.45 Hz, further optionally equal to 0.45 Hz, - In the seventh step 1300, the ratio LHR dic between the powers of the LF band and the HF band of the power spectrum PSD dic is calculated (output), i.e., LHR dic = P LF (PSDdic) / P HF (PSDdic) shown by, and this enables the physician to consider the fluctuations in the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system of the subject, as well as the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system, based on the type of population to which the subject belongs, and evaluate based on the value of the ratio LHR is also executable, and thereby, the physician can also evaluate based on the value of the ratio LHR dic considering the type of population to which the subject belongs.

[0064] A further embodiment of the computer-implemented method according to the present invention can also determine HRV by the prior art, i.e., - In the third step 1100, the tachogram D i of the discrete pressure signal p(tbeat constructing - In a fourth step 1150, the tachogram D of the discrete pressure signal p(t i ) beat is resampled to obtain a resampled tachogram D of the discrete pressure signal p(t i ) beat (r) - In a fifth step 1200, the power spectrum PSD of the resampled tachogram D of the discrete pressure signal p(t i ) beat (r) is calculated (optionally, through Fourier transform, more optionally, through FFT, through autoregressive modeling, or through wavelet transform) beat - In a sixth step 1250, the power spectrum PSD of the resampled tachogram of the discrete pressure signal p(t i ) beat is subdivided into three frequency bands, namely, the VLF_HRV band (where the frequency f VLF_HRV is in the range of 0.01 Hz to 0.04 Hz), the LF_HRV band (where the frequency f LF_HRV is in the range of 0.04 Hz to 0.15 Hz), and the HF_HRV band (where the frequency f HF_HRV is in the range of 0.15 Hz to 0.4 Hz), and in each of one of LF_HRV and HF_HRV, the power of the power spectrum PSD beat , that is, the power P of the power spectrum PSD in the LF_HRV band beat LF_HRV (PSDbeat) (given by the integral in the LF_HRV band, that is, the sum in the discretized domain of the frequencies of the power spectrum PSD beat ), and the power P of the power spectrum PSD in the HF_HRV band beat HF_HRV (PSDbeat) (given by the integral in the HF_HRV band, that is, the sum in the discretized domain of the frequencies of the power spectrum PSD beat ​​​​calculating (given by the sum in the discretized domain of the frequency), and - In the seventh step 1300, the power spectrum PSD beat the ratio LHR between the peak frequencies of the LF_HRV band and the HF_HRV band of dic the value, that is, LHR beat =P LF_HRV (PSDbeat) / P HF_HRV (PSDbeat) shown by can be calculated and output, whereby a doctor can also evaluate the fluctuations in the activation of the sympathetic nervous system and the fluctuations in the activation of the parasympathetic nervous system of the subject, and the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system, considering the type of the group to which the subject belongs, based on the value of the ratio LHR beat of.

[0065] Another embodiment of the computer-implemented method according to the present invention is - (Optionally, performed at any one step between the fifth step 1200 and the seventh step 1300, and output at the seventh step 1300), the standard deviation SD of the resampled diagram D of the systolic phase duration sys (r) of, and the standard deviation SD of the resampled diagram D of the diastolic phase duration (sys) and, (and, optionally, the standard deviation SD of the resampled tachogram D of the discrete pressure signal p(t dia (r) ), the standard deviation SD of the resampled diagram D of the systolic phase duration (dia) ), optionally, the total power TP of the power spectrum PSD of the resampled diagram D of the systolic phase duration i ) of, and the standard deviation SD of the resampled diagram D of the diastolic phase duration beat (r) of, (and, optionally, the standard deviation SD of the resampled tachogram D of the discrete pressure signal p(t (beat) ), optionally, the total power TP of the power spectrum PSD of the resampled diagram D of the systolic phase duration sys (r) of, and the total power TP of the power spectrum PSD of the resampled diagram D of the diastolic phase duration sys of (sys) and, and the total power TP of the power spectrum PSD of the resampled diagram D of the diastolic phase duration dia (r) of diaTotal power TP (dia) (and, optionally, the discrete pressure signal p(t i ) resampled tachogram D beat (r) power spectrum PSD beat total power TP (beat) ) are calculated, and thereby, the physician, taking into account the type of population to which the subject belongs, the standard deviation SD (sys) and SD (dia) (optionally, the standard deviation SD (beat) ), optionally, based also on the values of the total power TP (sys) and TP (dia) (optionally, the total power TP (beat) ), can evaluate the variations in the activation of the subject's own sympathetic nervous system and the activation of the parasympathetic nervous system, as well as the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system.

[0066] A further embodiment of the computer-implemented method according to the present invention is, in the third step 1100, a diagram D of the duration of the systolic phase and the duration of the diastolic phase of each heartbeat, expressed not as an absolute value in milliseconds but as a normalized value (e.g., a percentage value) with respect to the total heartbeat duration sys and a diagram D of the duration of the diastolic phase dia can be constructed.

[0067] The preferred embodiments have been described above and numerous variations of the present invention have been proposed. It is to be understood that those skilled in the art can make other variations and modifications without departing from the scope of protection defined by the appended claims.

Claims

1. A method executed by a computer, which is a method for detecting parameters indicating fluctuations in sympathetic nervous system activation and fluctuations in parasympathetic nervous system activation of a subject transitioning from a basal state to a perturbed state, comprising: A. Receiving a discrete pressure signal p(t ｉ ) indicating a plurality of heartbeats of the subject (1000), B. Identifying each heartbeat of the discrete pressure signal p(t ｉ ), and within each heartbeat, identifying the systolic phase p ｓｙｓ (t ｉ ) and the diastolic phase p ｄｉａ (t ｉ ) (1050), C. Diagram D of the duration of the systolic phase as a function of the heart rate ｓｙｓ and diagram D of the duration of the diastolic phase as a function of the heart rate ｄｉａ constructing them (1100), D. The diagram D of the duration of the systolic phase ｓｙｓ perform resampling of, and obtain the resampled diagram D of the duration of the systolic phase ｓｙｓ （ｒ） of the diagram D of the duration of the diastolic phase, perform resampling of, and obtain the resampled diagram D of the duration of the diastolic phase ｄｉａ of the diagram D of the duration of the diastolic phase, perform resampling of, and obtain the resampled diagram D of the duration of the diastolic phase ｄｉａ （ｒ） and (1150), E. the resampled diagram D of the duration of the systolic phase ｓｙｓ （ｒ） of the power spectrum PSD ｓｙｓ and, the lower frequency f ｌｏｗｅｒ＿ｌｉｍｉｔ and the lower frequency f ｌｏｗｅｒ＿ｌｉｍｉｔ higher upper frequency f ｕｐｐｅｒ＿ｌｉｍｉｔ and the resampled diagram D of the duration of the diastolic phase at a frequency between ｄｉａ （ｒ） of the power spectrum PSD ｄｉａ calculating (1200); The power P of the power spectrum PSD in the F. LF band ｓｙｓ of the power P ＬＦ （ＰＳＤｓｙｓ） and the power P of the power spectrum PSD in the HF band ｓｙｓ of the power P ＨＦ （ＰＳＤｓｙｓ） and the power P of the power spectrum PSD in the LF band ｄｉａ of the power P ＬＦ （ＰＳＤｄｉａ） and the power P of the power spectrum PSD in the HF band ｄｉａ of the power P ＨＦ （ＰＳＤｄｉａ） calculate (1250), However, the frequency f of the LF band ＬＦ is equal to or higher than the first intermediate frequency f ｉｎｔｅｒｍｅｄｉａｔｅ＿１ and is smaller than the second intermediate frequency f ｉｎｔｅｒｍｅｄｉａｔｅ＿２ and is represented by the following formula f ｉｎｔｅｒｍｅｄｉａｔｅ＿１ ≤ f ＬＦ < f ｉｎｔｅｒｍｅｄｉａｔｅ＿２ The lower limit frequency f ｌｏｗｅｒ＿ｌｉｍｉｔ is smaller than the first intermediate frequency f ｉｎｔｅｒｍｅｄｉａｔｅ＿１ and the first intermediate frequency f ｉｎｔｅｒｍｅｄｉａｔｅ＿１ is smaller than the second intermediate frequency f ｉｎｔｅｒｍｅｄｉａｔｅ＿２ and the second intermediate frequency f ｉｎｔｅｒｍｅｄｉａｔｅ＿２ is smaller than the upper limit frequency f ｕｐｐｅｒ＿ｌｉｍｉｔ and is represented by the following formula: f ｌｏｗｅｒ＿ｌｉｍｉｔ <f ｉｎｔｅｒｍｅｄｉａｔｅ＿１ <f ｉｎｔｅｒｍｅｄｉａｔｅ＿２ <f ｕｐｐｅｒ＿ｌｉｍｉｔ Furthermore, provided that the frequency f of the HF band ＨＦ is equal to or higher than the second intermediate frequency f ｉｎｔｅｒｍｅｄｉａｔｅ＿２ and is smaller than the upper limit frequency f ｕｐｐｅｒ＿ｌｉｍｉｔ and is represented by the following equation f ｉｎｔｅｒｍｅｄｉａｔｅ＿２ ≤ f ＨＦ < f ｕｐｐｅｒ＿ｌｉｍｉｔ G. The power spectrum PSD ｓｙｓ The ratio LHR between the power of the LF band and the power of the HF band of ｓｙｓ the value of, and the power spectrum PSD ｄｉａ the ratio LHR between the power of the LF band and the power of the HF band of ｄｉａ the value of, that is, LHR ｓｙｓ = P ＬＦ （ＰＳＤｓｙｓ） / P ＨＦ （ＰＳＤｓｙｓ） LHR ｄｉａ = P ＬＦ （ＰＳＤｄｉａ） / P ＨＦ （ＰＳＤｄｉａ） calculating and outputting what is shown by (1300); The method according to which steps A to G of the above method are executed on the subject first in the basal state and then in the perturbed state.

2. The lower limit frequency f ｌｏｗｅｒ＿ｌｉｍｉｔ is equal to 0.01 Hz, and the upper limit frequency f ｕｐｐｅｒ＿ｌｉｍｉｔ is in the range of 0.4 Hz to 1.2 Hz, and the first intermediate frequency f ｉｎｔｅｒｍｅｄｉａｔｅ＿１ is in the range of 0.04 Hz to 0.12 Hz, and the second intermediate frequency f ｉｎｔｅｒｍｅｄｉａｔｅ＿２ is in the range of 0.15 Hz to 0.45 Hz. The method according to claim 1.

3. The upper limit frequency f upper_limit is in the range of 0.8 Hz to 1.2 Hz, the first intermediate frequency f intermediate_1 is in the range of 0.08 Hz to 0.12 Hz, and the second intermediate frequency f intermediate_2 is in the range of 0.30 Hz to 0.45 Hz. The method according to claim 2.

4. The upper limit frequency f upper_limit is equal to 1.2 Hz, the first intermediate frequency f intermediate_1 is equal to 0.12 Hz, and the second intermediate frequency f intermediate_2 is equal to 0.45 Hz. The method according to claim 3.

5. In step E, the power spectrum PSD ｓｙｓ and PSD ｄｉａ are respectively calculated through the Fourier transform of the resampled diagram D ｓｙｓ （ｒ） of the duration of the systolic phase and the resampled diagram D ｄｉａ （ｒ） of the duration of the diastolic phase The method according to any one of claims 1 to 4.

6. The Fourier transform is a fast Fourier transform (FFT). The method according to claim 5.

7. The discrete pressure signal p(t ｉ ) received in step A has a duration of at least three minutes. The method according to any one of claims 1 to 6.

8. The discrete pressure signal p(ti) received in step A has a duration of at least 4 minutes. The method according to claim 7.

9. The discrete pressure signal p(ti) received in step A has a duration of at least 5 minutes. The method according to claim 8.

10. In step B, based on the identification of the repetitive upstroke time, the systolic phase and the diastolic phase of each heartbeat are identified. The method according to any one of claims 1 to 9.

11. - In step B, further, the value of the overlapping bulge pressure P at each heartbeat ｄｉｃ is specified, - In step C, further, a diagram D of the overlapping bulge pressure as a function of the heart rate progression number ｄｉｃ is constructed, - In step D, further, the diagram D of the repeated heaving pressure ｄｉｃ is resampled to obtain the resampled diagram D of the repeated heaving pressure ｄｉｃ （ｒ） and - In step E, further, the lower frequency f ｌｏｗｅｒ＿ｌｉｍｉｔ and the upper frequency f ｕｐｐｅｒ＿ｌｉｍｉｔ the power spectrum PSD ｄｉｃ （ｒ） of the resampled diagram D ｄｉｃ at frequencies between and is calculated, - In step F, further, the power P of the power spectrum PSD of the LF band ｄｉｃ and the power P of the power spectrum PSD of the HF band ＬＦ （ＰＳＤｄｉｃ） are calculated, ｄｉｃ and ＨＦ （ＰＳＤｄｉｃ） ​ - In step G, further, the ratio LHR ｄｉｃ between the power of the LF band and the HF band of the power spectrum PSD ｄｉｃ of the value, that is, LHR ｄｉｃ = P ＬＦ （ＰＳＤｄｉｃ） / P ＨＦ （ＰＳＤｄｉｃ） Calculating and outputting what is shown by, the method according to claim 10.

12. In step C, the diagram D of the duration of the systolic phase ｓｙｓ and the diagram D of the duration of the diastolic phase ｄｉａ are constructed by expressing the durations of the systolic phase and the diastolic phase of each heartbeat as values normalized to the overall period of the heartbeat being analyzed. The method according to any one of claims 1 to 11.

13. Furthermore, first in the basal state and then in the perturbed state, the HRV (heart rate variability) of the subject is determined and output. The method according to any one of claims 1 to 12.

14. Furthermore, the standard deviation SD of the resampled diagram D of the duration of the systolic phase ｓｙｓ （ｒ） and the standard deviation SD of the resampled diagram D of the duration of the diastolic phase （ｓｙｓ） are calculated, and in step G, those values of the subject in the initial baseline state and then in the perturbation state are output ｄｉａ （ｒ） （ｄｉａ） ​​ The method according to any one of claims 1 to 13.

15. Furthermore, the resampled diagram D of the duration of the systolic phase ｓｙｓ （ｒ） of the power spectrum PSD ｓｙｓ of the total power TP （ｓｙｓ） , and the resampled diagram D of the duration of the diastolic phase ｄｉａ （ｒ） of the power spectrum PSD ｄｉａ of the total power TP （ｄｉａ） are calculated and, in step G, those values of the subject in the initial basal state and then in the perturbed state are output The method according to any one of claims 1 to 14.

16. An apparatus including a processing device configured to execute the method according to any one of claims 1 to 15, the method for detecting parameters indicating fluctuations in sympathetic nervous system activation and fluctuations in parasympathetic nervous system activation in a subject during a transition from a basal state to a perturbed state.

17. One or more computer program sets including instructions that, when executed by one or more processing units, cause the one or more processing units to execute the method according to any one of claims 1 to 15, the method for detecting parameters indicating fluctuations in sympathetic nervous system activation and fluctuations in parasympathetic nervous system activation in a subject during a transition from a basal state to a perturbed state.

18. A set of one or more computer-readable media having stored thereon the one or more computer program sets according to claim 17.

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