METHOD OF DETECTING PARAMETERS INDICATIVE OF ACTIVATION OF SYMPATHETIC AND PARASYMPATHETIC NERVOUS SYSTEMS

Abstract

The present invention relates to an antidepressant composition containing king oyster mushroom extract as an active ingredient, and more specifically, to a food composition and a pharmaceutical composition containing an extract or fraction of king oyster mushroom as an active ingredient for preventing, improving or treating depression. The king oyster mushroom extract of the present invention can act on serotonin receptors and inhibit the binding between serotonin receptors and selective serotonin reuptake inhibitors and act on serotonin receptors to activate serotonin receptor-mediated signaling. Also, as the king oyster mushroom extract can reduce immobility time in animal model experiments of forced swimming tests, the effect of being useful as functional foods and medicines to prevent, improve, or treat depression can be provided.

Claims

1. A method implemented in a computing apparatus for detecting physiological parameters indicative of variations in the activation of the sympathetic and parasympathetic nervous systems of a human subject during transition from a basal to a perturbed condition, the method comprising: A. receiving, from a pressure sensor device, a discrete time-domain pressure signal representative of cardiac cycles; B. identifying, via a processor, in each cardiac cycle, a systolic phase and a diastolic phase; C. generating, via the processor, a first signal trend diagram for systolic phase durations and a second signal trend diagram for diastolic phase durations; D. resampling, via the processor, both diagrams; E. performing, via the processor, a spectral analysis to compute a power spectrum for each resampled diagram; F. segmenting, via the processor, each spectrum into low frequency (LF) and high frequency (HF) bands according to predefined physiological thresholds; G. calculating, via the processor, a LF/HF power ratio for each spectrum; and H. outputting, via the processor, the LF/HF power ratios to a storage module or display system for downstream processing, wherein the method is executed by a processor integrated in a medical monitoring device, and wherein the LF/HF ratio variations are indicative of autonomic nervous system balance adjustments.

2. The method of claim 1, wherein the pressure signal is acquired via a non-invasive photoplethysmographic sensor attached to a peripheral vascular location.

3. The method of claim 1, wherein, in step B, the processor identifies the systolic phase and the diastolic phase in each cardiac cycle based on dicrotic notch detection.

4. The method of claim 1, wherein, in step E, the processor performs the spectral analysis using a Fourier Transform or autoregressive modelling or wavelet transformation.

5. The method of claim 1, further comprising generating and outputting, via the processor, a heart rate variability (HRV) index based on the pressure signal prior to resampling.

6. The method of claim 1, wherein the processor is further configured to calculate and output a standard deviation of the resampled signal and total power of each power spectrum.

7. The method of claim 1 wherein the perturbed condition comprises subject posture elevation during a tilt-table test protocol.

8. A system for detecting physiological parameters associated with autonomic nervous system regulation, the system comprising: a pressure sensor for capturing arterial or venous pressure signals of a subject; a processing unit configured to: A. receive, from the pressure sensor, a discrete time-domain pressure signal representative of cardiac cycles, B. identify, in each cardiac cycle, a systolic phase and a diastolic phase, C. generate a first signal trend diagram for systolic phase durations and a second signal trend diagram for diastolic phase durations, D. resample both diagrams, E. perform a spectral analysis to compute a power spectrum for each resampled diagram, F. segment each spectrum into low frequency (LF) and high frequency (HF) bands according to predefined physiological thresholds, and G. calculate a LF/HF power ratio for each spectrum; a memory device configured to store intermediate and final analysis results; a display configured to visualize data; wherein the processing unit is configured to output the LF/HF power ratios to the memory device and/or to visualize the LF/HF power ratios on the display of the system.

9. The system of claim 8, wherein the pressure sensor is acquired a non-invasive photoplethysmographic sensor.

10. The system of claim 8, wherein the processor is configured to identify the systolic phase and the diastolic phase in each cardiac cycle based on dicrotic notch detection.

11. The system of claim 8, wherein the processor is configured to perform the spectral analysis using a Fourier Transform or autoregressive modelling or wavelet transformation.

12. The system of claim 8, wherein the processor is further configured to generate a heart rate variability (HRV) index based on the pressure signal prior to resampling and to output the heart rate variability (HRV) index to the memory device and/or to visualize the heart rate variability (HRV) index on the display of the system.

13. The system of claim 8, wherein the processor is further configured to calculate a standard deviation of the resampled signal and total power of each power spectrum and to output the standard deviation of the resampled signal and total power of each power spectrum to the memory device and/or to visualize the standard deviation of the resampled signal and total power of each power spectrum on the display of the system.

14. A method implemented in a non-generic computing apparatus for detecting physiological parameters indicative of variations in the activation of the sympathetic and parasympathetic nervous systems of a human subject during transition from a basal to a perturbed condition, the method comprising: A. receiving, from a pressure sensor device, a discrete time-domain pressure signal representative of cardiac cycles; B. identifying, in each cardiac cycle, a systolic phase and a diastolic phase based on dicrotic notch detection; C. generating, via a processor, a first signal trend diagram for systolic phase durations and a second signal trend diagram for diastolic phase durations; D. resampling, via the processor, both diagrams using a time-domain regularization algorithm; E. performing, via the processor, a spectral analysis using a Fourier Transform or wavelet transformation to compute a power spectrum for each resampled diagram; F. segmenting, via the processor, each spectrum into low frequency (LF) and high frequency (HF) bands according to predefined physiological thresholds; G. calculating, via the processor, a LF/HF power ratio for each spectrum; and H. outputting, via the processor, the LF/HF power ratios to a storage module or display system for downstream processing, wherein the method is executed by a processor integrated in a medical monitoring device, and wherein the LF/HF ratio variations are indicative of autonomic nervous system balance adjustments.

Description

[0052] FIG. 1 shows a flow chart of the preferred embodiment of the computer-implemented method according to the invention.

[0053] In a first step 1000, the method receives a discrete pressure signal p(t.sub.i) (such as for example an arterial pressure or a pulmonary venous pressure or a central venous pressure) of a subject or patient comprising a plurality of heartbeats. In particular, the discrete pressure signal p(t.sub.i) can derive from a continuous pressure signal p(t) that is detected through pressure sensors and that is digitised to obtain the discrete signal p(t.sub.i) (wherein the index i indicates the succession of discrete samples), or a discrete signal (i.e. already digitised) stored in a memory medium; in particular, the detection of the continuous pressure signal p(t) can take place either invasively or non-invasively, e.g. through a photoplethysmographic sensor. The received discrete pressure signal p(t.sub.i) has a time duration optionally of at least 3 minutes, more optionally of at least 4 minutes, even more optionally of at least 5 minutes.

[0054] In a second step 1050, the method identifies each heartbeat of the discrete pressure signal p(t.sub.i) and, within each heartbeat, identifies the systolic phase p.sub.sys(t.sub.i) and the diastolic phase p.sub.dia(t.sub.i). Optionally, the method performs the identification of each heartbeat through the automated method of discrimination of the heartbeat described in the International application no. WO 2004/084088 A1, and/or the identification of the systolic phase and diastolic phase of each heartbeat on the basis of the identification of the dicrotic notch time (corresponding to the time of closure of the aortic valve for arterial pressure signals or to the time of closure of the tricuspid valve for pulmonary pressure signals).

[0055] In a third step 1100, the method builds a diagram D.sub.sys of the duration of the systolic phase (ordinate axis) as a function of the progressive number of the heartbeats (abscissa axis) and a diagram D.sub.dia of the duration of the diastolic phase (ordinate axis) as a function of the progressive number of the heartbeats (abscissa axis). The duration of the systolic phase and diastolic phase is optionally expressed in milliseconds.

[0056] In a fourth step 1150, the method performs a resampling of the diagram D.sub.sys of the duration of the systolic phase and of the diagram D.sub.dia of the duration of the diastolic phase (built in the third step 1100), obtaining a resampled diagram

[00024]$D_{sys}^{\left(r\right)}$

of the duration of the systolic phase and a resampled diagram

[00025]$D_{dia}^{\left(r\right)}$

of the duration of the diastolic phase.

[0057] In a fifth step 1200, the method calculates the power spectrum PSD.sub.sys of the resampled diagram

[00026]$D_{sys}^{\left(r\right)}$

of the duration of the systolic phase and the power spectrum PSD.sub.dia of the resampled diagram

[00027]$D_{dia}^{\left(r\right)}$

of the duration of the diastolic phase at frequencies between a lower limit frequency f.sub.lower_limit, optionally equal to 0.01 Hz, and an upper limit frequency f.sub.upper_limit (higher than the lower limit frequency f.sub.lower_limit), optionally variable from 0.4 Hz to 1.2 Hz, more optionally variable from 0.8 Hz to 1.2 Hz, even more optionally equal to 1.2 Hz; in particular, the lower limit frequency f.sub.lower_limit and the upper limit frequency f.sub.upper_limit depend on the type of the subjects under examination. Optionally, the method calculates the power spectra PSD.sub.sys and PSD.sub.dia through a Fourier transform, more optionally a Fast Fourier Transform (FFT), of the resampled diagram

[00028]$D_{sys}^{\left(r\right)}$

of the duration of the systolic phase and of the resampled diagram

[00029]$D_{dia}^{\left(r\right)}$

of the duration of the diastolic phase, respectively. Alternatively to the Fourier transform, other embodiments of the computer-implemented method according to the invention can calculate the power spectra PSD.sub.sys and PSD.sub.dia through an autoregressive modelling or through a wavelet transform.

[0058] In a sixth step 1250, the method subdivides each of the power spectra PSD.sub.sys and PSD.sub.dia into three frequency bands VLF (Very Low Frequency), LF (Low Frequency) and HF (High Frequency). In the LF band the frequency f.sub.LF ranges from a first intermediate frequency f.sub.intermediate_1 to a second intermediate frequency f.sub.intermediate_2, thereby

[00030]$f_{\mathrm{intermediate}\_1}{f}_{\mathrm{LF}}<f_{\mathrm{intermediate}\_2},$

where the lower limit frequency f.sub.lower_limit is lower than the first intermediate frequency f.sub.intermediate_1, that in turn is lower than the second intermediate frequency f.sub.intermediate_2, that in turn is lower than the upper limit frequency f.sub.upper_limit, thereby

[00031]$f_{\mathrm{lower}\_\mathrm{limit}}<f_{\mathrm{intermediate}\_1}<f_{\mathrm{intermediate}\_2}<f_{\mathrm{upper}\_\mathrm{limit}}.$

In the HF band the frequency f.sub.HF ranges from the second intermediate frequency f.sub.intermediate_2 to the upper limit frequency f.sub.upper_limit, thereby

[00032]$f_{\mathrm{intermediate}\_2}{f}_{\mathrm{HF}}<f_{\mathrm{upper}\_\mathrm{limit}}.$

In the VLF band the frequency f.sub.VLF ranges from the lower limit frequency f.sub.lower_limit to the first intermediate frequency f.sub.intermediate_1 thereby

[00033]$f_{\mathrm{lower}\_\mathrm{limit}}{f}_{\mathrm{VLF}}<f_{\mathrm{intermediate}\_1}.$

The first intermediate frequency f.sub.intermediate_1 and the second intermediate frequency f.sub.intermediate_2 also depend on the type of the subjects under examination. Optionally, the first intermediate frequency f.sub.intermediate_1 ranges from 0.04 Hz to 0.12 Hz, more optionally it ranges from 0.08 Hz to 0.12 Hz, still more optionally it is equal to 0.12 Hz; optionally, the second intermediate frequency f.sub.intermediate_2 ranges from 0.15 Hz to 0.45 Hz, more optionally it ranges from 0.30 Hz to 0.45 Hz, still more optionally it is equal to 0.45 Hz.

[0059] Still in the sixth step 1250, the method calculates the power of each of the power spectra PSD.sub.sys and PSD.sub.dia in each one of the LF and HF bands; namely: [0060] the power

[00034]$P_{\mathrm{LF}}^{\left({\mathrm{PSD}}_{\mathrm{sys}}\right)}$

in the LF band of the power spectrum PSD.sub.sys (given by the integral in the LF band, i.e. the summation in the discretised domain of frequencies of the power spectrum PSD.sub.sys); [0061] the power

[00035]$P_{\mathrm{HF}}^{\left({\mathrm{PSD}}_{\mathrm{sys}}\right)}$

in the HF band of the power spectrum PSD.sub.sys (given by the integral in the HF band, i.e. the summation in the discretised domain of frequencies of the power spectrum PSD.sub.sys); [0062] the power

[00036]$P_{\mathrm{LF}}^{\left({\mathrm{PSD}}_{\mathrm{dia}}\right)}$

in the LF band of the power spectrum PSD.sub.dia (given by the integral in the LF band, i.e. the summation in the discretised domain of frequencies of the power spectrum PSD.sub.dia); [0063] the power

[00037]$P_{\mathrm{HF}}^{\left({\mathrm{PSD}}_{\mathrm{dia}}\right)}$

in the HF band of the power spectrum PSD.sub.dia (given by the integral in the HF band, i.e. the summation in the discretised domain of frequencies of the power spectrum PSD.sub.dia).

[0064] In a seventh step 1300, the method calculates (and outputs) the values of the ratios LHR.sub.sys and LHR.sub.dia between the powers in the LF and HF bands of the power spectra PSD.sub.sys and PSD.sub.dia, respectively, thereby:

[00038]${\mathrm{LHR}}_{\mathrm{sys}}=\frac{P_{\mathrm{LF}}^{\left({\mathrm{PSD}}_{\mathrm{sys}}\right)}}{P_{\mathrm{HF}}^{\left({\mathrm{PSD}}_{\mathrm{sys}}\right)}}$${\mathrm{LHR}}_{\mathrm{dia}}=\frac{P_{\mathrm{LF}}^{\left({\mathrm{PSD}}_{\mathrm{dia}}\right)}}{P_{\mathrm{HF}}^{\left({\mathrm{PSD}}_{\mathrm{dia}}\right)}}$

[0065] On the basis of the values of the ratios LHR.sub.sys and LHR.sub.dia output by the seventh step 1300, taking account of the type of population to which the subject belongs, a doctor is able to evaluate the variation of activation of the sympathetic nervous system and the variation of the activation of the parasympathetic nervous system, from which it is also possible to evaluate a variation in the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system (i.e., the possible predominance of the activity of the sympathetic nervous system or of the activity of the parasympathetic nervous system on the other) of the subject himself/herself. In particular, the values of the LHR.sub.sys and LHR.sub.dia ratios depend on the type of population, by age and pathology, to which the examined subjects belong.

[0066] In other words, the computer-implemented method according to the invention uses the characteristics of the mechanical response of the cardiovascular system to the electrical stimulus of the heart, analysing the systolic and diastolic phases within each cardiac cycle. This allows for a more reliable evaluation than prior art methods, since the dynamic components of the activations of the sympathetic and parasympathetic nervous system and the balance between the activation of the sympathetic nervous system and the activation of the parasympathetic nervous system give different indications of dynamic equilibrium during the two systolic and diastolic phases, providing more detailed information on stress and vagal activation.

[0067] The inventor made some evaluations on the results obtained by applying the computer-implemented method according to the invention and comparing the results with those obtained by the prior art methods in the evaluation of the HRV. In particular, the experiments were conducted on subjects who passed from a basal condition to a perturbed condition in which an event causes a change in the cardiovascular system.

[0068] The experiments show that the characteristics of variation of the HRV can be either in agreement or in disagreement with those of the resampled diagram

[00039]$D_{\mathrm{dia}}^{\left(r\right)}$

of the duration of the diastolic phase (albeit with non-equal absolute values), and that the characteristics of variation of the resampled diagram

[00040]$D_{\mathrm{sys}}^{\left(r\right)}$

of the duration of the systolic phase are often substantially different from those of the HRV.

[0069] Some evaluations were carried out on the results obtained for subjects for whom the perturbed condition was caused by the administration of a powerful anaesthetic that has a sympatholytic effect (namely Propofol). According to traditional physiology, the ratio between the LF and HF components must decrease because the vagal activity is activated and, thus, by inhibiting the activity of the sympathetic nervous system, the balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system changes. However, the characteristics of the HRV had variations that led 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, demonstrating that the power spectrum PSD of the tachogram does not correctly identify the activation of the vagal nerve and the inhibition of the sympathetic nervous system. Differently, the ratio LHR.sub.sys derived from the resampled diagram

[00041]$D_{\mathrm{sys}}^{\left(r\right)}$

of the duration of the systolic phase decreases for all patients, reliably identifying the prevalence of the activation of the parasympathetic nervous system with respect to the basal condition (i.e. to the condition not altered by the administration of the anaesthetic).

[0070] In general, the results obtained from the application of the computer-implemented method according to the invention revealed that, to evaluate which one of the sympathetic nervous system and the parasympathetic nervous system is activated in a prevalent way, it is sufficient to carry out a comparison of the variations of the ratios LHR.sub.sys and LHR.sub.dia in the transition from the basal condition to the perturbed condition in function of the type of subject examined. By way of example, for some types of subjects, if such variations are discordant, the activation of the parasympathetic nervous system has prevailed over the activation of the sympathetic nervous system, while if such variations are in agreement (e.g., both increase), the activation of the sympathetic nervous system has prevailed over the activation of the parasympathetic nervous system.

[0071] In the case of a patient under examination (e.g., a patient who has problems of orthostatism, which can lead to syncope, or a patient suffering from liver cirrhosis) and no data related to a basal condition are available, the evaluation of the variation in activation of the sympathetic nervous system and of the variation of the 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, are carried out by performing the computer-implemented method according to the invention while the patient is lying down on an examination table, assuming this as the basal condition, subjecting the patient to the so-called tilt test (i.e., the examination table is raised by 60 degrees), assuming this as the perturbed condition, and performing again the computer-implemented method according to the invention. For a patient suffering from liver cirrhosis, it is sufficient to move from a supine position to an orthostatic position as perturbed condition.

[0072] It is important to underline that the computer-implemented method according to the invention is not a diagnostic method per se, but it is a method detecting parameters, namely the ratios LHR.sub.sys e LHR.sub.dia, indicative of the variation of activation of the sympathetic nervous system, of the variation of activation of the parasympathetic nervous system, and of a balance between the activity of the sympathetic nervous system and the activity of the parasympathetic nervous system of a subject in the transition from a basal condition to a perturbed condition, which require a subsequent interpretation by a physician for formulating the diagnosis. Other embodiments of the computer-implemented method according to the invention can also: [0073] in the second step 1050, identify the value of the dicrotic notch pressure P.sub.dic in each heartbeat; [0074] in the third step 1100, build a diagram D.sub.dic of the dicrotic notch pressure (ordinate axis) as a function of the progressive number of the heartbeats (abscissa axis); [0075] in the fourth step 1150, perform a resampling the diagram D.sub.dic of the dicrotic notch pressure obtaining a resampled diagram

[00042]$D_{\mathrm{dic}}^{\left(r\right)}$

of the dicrotic notch pressure; [0076] in the fifth step 1200, calculate the power spectrum PSD.sub.dic (optionally through a Fourier transform, more optionally a FFT, or through an autoregressive modelling or through a wavelet transform) of the resampled diagram

[00043]$D_{\mathrm{dic}}^{\left(r\right)}$

of the dicrotic notch pressure at frequencies ranging from the lower limit frequency f.sub.lower_limit (optionally equal to 0.01 Hz), and the upper limit frequency f.sub.upper_limit (higher than the lower limit frequency f.sub.lower_limit and optionally ranging from 0.4 Hz to 1.2 Hz, more optionally ranging from 0.8 Hz to 1.2 Hz, still more optionally equal to 1.2 Hz), that, as mentioned, depend on the type of the subjects examined; [0077] in the sixth step 1250, subdivide the power spectrum PSD.sub.dic of the resampled diagram

[00044]$D_{\mathrm{dic}}^{\left(r\right)}$

of the dicrotic notch pressure into three frequency bands VLF (in which the frequency f.sub.VLF ranges from the lower limit frequency f.sub.lower_limit to the first intermediate frequency f.sub.intermediate_1), LF (in which the frequency f.sub.LF ranges from the first intermediate frequency f.sub.intermediate_1 to the second intermediate frequency f.sub.intermediate_2) and HF (in which the frequency f.sub.HF ranges from the second intermediate frequency f.sub.intermediate_2 to the upper limit frequency f.sub.upper_limit), and it calculate, in each of the LF and HF bands, the power of the power spectrum PSD.sub.dic, namely the power

[00045]$P_{\mathrm{LF}}^{\left({\mathrm{PSD}}_{\mathrm{dic}}\right)}$

of the power spectrum PSD.sub.dic in the LF band (given by the integral in the LF band, i.e. the summation in the discretised domain of the frequencies, of the power spectrum PSD.sub.dic) and the power of the power

[00046]$P_{\mathrm{HF}}^{\left({\mathrm{PSD}}_{\mathrm{dic}}\right)}$

of the power spectrum PSD.sub.dic in the HF band (given by the integral in the HF band, i.e. the summation in the discretised domain of the frequencies, of the power spectrum PSD.sub.dic); as mentioned, the first intermediate frequency f.sub.intermediate_1 and the second intermediate frequency f.sub.intermediate_2 depend on the type of the subjects examined: optionally, the first intermediate frequency f.sub.intermediate_1 ranges from 0.04 Hz to 0.12 Hz, more optionally it ranges from 0.08 Hz to 0.12 Hz, still more optionally it is equal to 0.12 Hz; optionally, the second intermediate frequency f.sub.intermediate_2 ranges from 0.15 Hz to 0.45 Hz, more optionally it ranges from 0.30 Hz to 0.45 Hz, still more optionally it is equal to 0.45 Hz; [0078] in the seventh step 1300, calculate (and output) the value of the ratio LHR.sub.dic between the powers in the LF and HF bands of the power spectrum PSD.sub.dic, thereby:

[00047]${\mathrm{LHR}}_{\mathrm{dic}}=\frac{P_{\mathrm{LF}}^{\left({\mathrm{PSD}}_{\mathrm{dic}}\right)}}{P_{\mathrm{HF}}^{\left({\mathrm{PSD}}_{\mathrm{dic}}\right)}}$

whereby a doctor is able to evaluate the variation of activation of the sympathetic nervous system and the variation of 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 of a subject also on the basis of the value of the ratio LHR.sub.dic, taking into account the type of population to which the subject belongs.

[0079] Further embodiments of the computer-implemented method according to the invention can also determine the HRV according to conventional techniques, whereby: [0080] in the third step 1100, building a tachogram D.sub.beat of the discrete pressure signal p(t.sub.i); [0081] in the fourth step 1150, performing a resampling of the tachogram D.sub.beat of the discrete pressure signal p(t.sub.i) obtaining a resampled tachogram

[00048]$D_{\mathrm{beat}}^{\left(r\right)}$

of the discrete pressure signal p(t.sub.i); [0082] in the fifth step 1200, calculating the power spectrum PSD.sub.beat (optionally through a Fourier transform, more optionally a FFT, or through an autoregressive modelling or through a wavelet transform) of the resampled tachogram

[00049]$D_{\mathrm{beat}}^{\left(r\right)}$

of the discrete pressure signal p(t.sub.i) at frequencies between 0.01 Hz and 0.4 Hz; [0083] in the sixth step 1250, subdividing the power spectrum PSD.sub.beat of the resampled tachogram

[00050]$D_{\mathrm{beat}}^{\left(r\right)}$

of the discrete pressure signal p(t.sub.i) into three frequency bands VLF_HRV (in which the frequency f.sub.VLF_HRV ranges from 0.01 Hz to 0.04 Hz), LF_HRV (in which the frequency f.sub.LF_HRV ranges from 0.04 Hz to 0.15 Hz) e HF_HRV (in which the frequency f.sub.HF_HRV ranges from 0.15 Hz to 0.4 Hz), and calculating, in each one of the bands LF_HRV e HF_HRV, the power of the power spectrum PSD.sub.beat, namely the power

[00051]$P_{\mathrm{LF\_HRV}}^{\left({\mathrm{PSD}}_{\mathrm{beat}}\right)}$

in the LF_HRV band of the power spectrum PSD.sub.beat, (given by the integral in the LF_HRV band, i.e. the summation in the discretised domain of the frequencies, of the power spectrum PSD.sub.beat) and the power

[00052]$P_{\mathrm{HF\_HRV}}^{\left({\mathrm{PSD}}_{\mathrm{beat}}\right)}$

in the HF_HRV band of the power spectrum PSD.sub.beat (given by the integral in the HF_HRV band, i.e. the summation in the discretised domain of the frequencies, of the power spectrum PSD.sub.beat); and [0084] in the seventh phase 1300, calculating (and outputting) the value of the ratio LHR.sub.beat between the peak frequencies in the LF_HRV and HF_HRV bands of the power spectrum PSD.sub.beat, thereby:

[00053]${\mathrm{LHR}}_{\mathrm{beat}}=\frac{P_{\mathrm{LF\_HRV}}^{\left({\mathrm{PSD}}_{\mathrm{beat}}\right)}}{P_{\mathrm{HF\_HRV}}^{\left({\mathrm{PSD}}_{\mathrm{beat}}\right)}}$

whereby a physician is able to evaluate the variation of activation of the sympathetic nervous system and the variation of 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 of a subject also on the basis of the value of the ratio LHR.sub.beat, taking into account the type of population to which the subject belongs.

[0085] Other embodiments of the computer-implemented method according to the invention can also: [0086] calculate (optionally in any one of the steps from the fifth step 1200 to the seventh step 1300, and outputting in the seventh step 1300) the standard deviation SD.sup.(sys) of the resampled diagram

[00054]$D_{\mathrm{sys}}^{\left(r\right)}$

of the duration of the systolic phase and the standard deviation SD.sup.(dia) of the resampled diagram

[00055]$D_{\mathrm{dia}}^{\left(r\right)}$

of the duration of the diastolic phase (and possibly the standard deviation SD.sup.(beat) of the resampled tachogram

[00056]$D_{\mathrm{beat}}^{\left(r\right)}$

of the discrete pressure signal p(t.sub.i)), and optionally the total power TP.sup.(sys) of the power spectrum PSD.sub.sys of the resampled diagram

[00057]$D_{\mathrm{sys}}^{\left(r\right)}$

of the duration of the systolic phase and the total power TP.sup.(dia) of the power spectrum PSD.sub.dia of the resampled diagram

[00058]$D_{\mathrm{dia}}^{\left(r\right)}$

of the duration of the diastolic phase (and possibly the total power TP.sup.(beat) of the power spectrum PSD.sub.beat of the resampled tachogram

[00059]$D_{\mathrm{beat}}^{\left(r\right)}$

of the discrete pressure signal p(t.sub.i)),
whereby a physician, taking into account the type of population to which a subject belongs, is able to evaluate the variation of activation of the sympathetic nervous system and the variation of 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 of the subject himself/herself also on the basis of the value of the standard deviations SD.sup.(sys) and SD.sup.(dia) (and possibly of the standard deviation SD.sup.(beat)), and optionally also on the basis of the total powers TP.sup.(sys) and TP.sup.(dia) (as well as of the total power TP.sup.(beat)).

[0087] Further embodiments of the computer-implemented method according to the invention can build, in the third step 1100, the diagram D.sub.sys of the duration of the systolic phase and the diagram D.sub.dia of the duration of the diastolic phase expressing the duration of the systolic phase and of the diastolic phase of each heartbeat as a normalised value (e.g., as a percentage value) with respect to the overall heartbeat duration, rather than as an absolute value in milliseconds.

[0088] In the above, the preferred embodiments have been described and a number of variations of the present invention have been suggested, but it is to be understood that those skilled in the art can make other variations and changes without departing from the scope of protection thereof, as defined by the appended claims.