WO2013060322A1

WO2013060322A1 - Method and system for monitoring and for determining the intensity of pain and the depth of anaesthesia

Info

Publication number: WO2013060322A1
Application number: PCT/DE2012/001070
Authority: WO
Inventors: Axel Heller; Hagen Malberg; Niels Wessel
Original assignee: Technische Universität Dresden; Humboldt Universität Zu Berlin
Priority date: 2011-10-28
Filing date: 2012-10-26
Publication date: 2013-05-02
Also published as: DE102011117573A1

Abstract

The invention relates to a method and to a system (13) for non-invasive monitoring and for determining the intensity of pain P and the depth of anaesthesia D, wherein the system (13) comprises an arrangement (2) for detecting/measuring heartbeat signals, a converter (9) connected downstream for converting the detected heartbeat signals into electrically digitised biosignals, a functional unit (4) for signal pre-processing in order to convert the electrical biosignals, taking account of a determined heart rate variability, for processing both into parameters 2B for the intensity of pain P and into parameters SD for the depth of anaesthesia D from the determined heart rate variability, an evaluation unit (8) that has at least two signal channels (18, 19), is connected downstream to the functional unit (4) for signal pre-processing, and receives signals of the time domain parameter ZB from the first signal channel (18) and the signals of the symbolic dynamics parameters SD from the second signal channel (19), wherein the evaluation unit (8) has a functional unit (10) for determining the intensity of pain P and a functional unit (11) for determining the depth of anaesthesia D including program resources stored therein and has a functional unit (6) for a decision system, wherein said functional unit is conductively connected to the functional unit (10) for determining the intensity of pain P and to the functional unit (11) for determining the depth of anaesthesia D and carries out comparisons of determined/calculated values with detected output/desired values, and a display unit (12) on which a display the depth of anaesthesia D and the associated intensity of pain P is provided for monitoring.

Description

Method and device for noninvasive monitoring and determination of pain severity and depth of anesthesia

description

The invention relates to a method and a device for the non-invasive monitoring and determination of pain intensity and depth of anesthesia during medical interventions. Monitoring the depth of anesthesia - the state of anesthesia - during an operation is one of the prior art of medical treatment.

The technical means for determining the depth of anesthesia are the measurement of blood pressure and heart rate; in addition, EEG signals from the brain are now also being used.

There are the following problems:

- Inadequate pain elimination,

- insufficient stress shielding,

- an intraoperative alertness and

- one to "deep narcosis" with hemodynamic impairment, which occur during the conduct of anesthesia during medical operations.

The resulting negative effects can cause delayed postoperative awakening, prolonged monitoring times, and cardiovascular instability.

It is therefore appropriate to have an individual "anesthesia guide and monitoring" during the medical surgical procedure.

The field of application of the invention is thus an anesthesia guide during medical operations on the patient, in order to avoid incorrect loading due to overdoses or underdoses of necessary medicines.

There are known methods for determining the depth of anesthesia using the heart rate data: The document US2005 / 0143668 A1 describes characteristic parameters in the time domain, in the frequency domain and in the nonlinear dynamics. For this purpose, the parallel analysis of the EEG, the pulse and the associated sound signal takes place in defined time windows. In the documents WO 2008131294 A1 and DE 10 2008 016 298 A1, the diagnosis of the pain intensity sensation from biosignals takes place as an example of the physiological condition as the clinical condition of persons. The statement is a qualitatively evaluated diagnostic index for the clinical condition. It is only possible to monitor the state of pain severity.

The document US2011 / 0137134 A1 describes a method with complex algorithmic processing of arterial pressure and heart rate data for monitoring the intraoperative pain intensity sensation for fuzzy logic-based control of infusion administration. Dominant are EEG data in combination with other relevant heart rate data to determine the depth of anesthesia. In the document US Pat. No. 5,871,450 A, only anesthesia depth measurement with frequency parameters of the heart rate variability HRV is possible. New frequency ranges and new monitoring parameters are planned.

In the document US 6,315,736 B1 a stimulation is provided. Additional signals are needed. Only one frequency range measurement is performed.

In the publication US 2002/0095092 A1, a pulse oximeter sensor is provided for signal generation.

The registration and analysis of cardiovascular biosignals is one of the most current topics in biomedical engineering research. In particular, extracorporeal derived biosignals (e.g., ECG, blood pressure) are used to identify cardiovascular risks and diagnoses using mathematical, computerized analysis.

General anesthesia is a medication-induced controlled and reversible loss of consciousness with parallel pain elimination. like a induced muscle relaxation. The brain is not completely turned off, so the depth of anesthesia is constantly monitored during a medical operation. As standard for the monitoring of the depth of anesthesia measurements are made, based on

repetitive blood pressure or continuous blood pressure,

- heart rate,

- Tear-foot observation,

- sweat secretion,

- Spontaneous movements and / or

- pupil play.

Conventional hemodynamics, autonomic signs, and the anesthesiologist's experience are available for "clinical" anesthesia control, and these signs are not reliable because individual anesthetic needs vary considerably.

Optionally, without compelling necessity, additional measurement data of the partial electroencephalogram (pEEP) of the brain has recently been taken into account.

These monitors are used to measure the frequencies that appear in the cerebral current curves: the lower the anesthesia, the more the low frequencies dominate, while the higher frequencies disappear.

In other systems, the anaesthetized patient wears a headset with a continuous click. Each click triggers a response in the patient's brain, and the reaction is reflected in the cerebral flow curves. Quantifying the reaction is entirely possible with computer technology. The way the reaction works depends on the depth of anesthesia, which the system can measure in this way, as in the publication Wiedemann: Neuärige "Wachheitsmonitore" (Anesthesia depth with acoustic stimuli), URL: http: //www.innovations-report. de / html / reports / medicine_health / report- 17726.html. Clinically, the criteria for "too shallow or too deep anesthesia" so far difficult to judge patient-specific.

A device for monitoring anesthesia and depth of consciousness is described in document WO 2011/017778 A1. The invention also includes a method wherein the apparatus and methods are based on the execution of at least one non-linear dynamics (NLD) analysis for monitoring continuous or evoked signals at the patient.

With such a device, the following process steps can be carried out:

a) a combination of a biosignal which has been triggered as a result of patient stimulation displayed on a patient, with a nonlinear analysis method capable of excite / excite time variations or uniformities in a signal sequence; b) a combination of triggered (evoked) or continuous central nervous or peripheral physiological mechanism,

c) use of an agent to generate a measurement tailored to the level of patient anesthesia and depth of consciousness (A & CD) for sedation or sleep / wake states.

Although monitoring of pain intensity is indicated, its role in medical procedures is not apparent.

The invention is based on a non-linear dynamics (NLD) analyzer to improve the difference between different signal origins.

One problem is that at least two sensors are needed to estimate the depth of anesthesia. In addition, there is a very complex, functional units complex measuring and analyzing device for the collection of data that are routinely not measured during a medical procedure. The focus of the invention is directed to AEP (triggered test signals) and the associated data analysis with nonlinear dynamics (NLD) methods from EEG recordings. There is no explicit HRV analysis and no information on a procedure regarding the evaluation of the HRV analysis. An estimate of the depth of anesthesia based on the nonlinear parameter Symbolic Dynamics SD from an EEG is found in Tupaika et al .: Assessment of the Depth of Anesthesia based on Symbolic Dynamics of the EEG, in: 32nd Annual International Conference of the IEEE EMBS, Buenos Aires, Argentina, August 21 - September 4, 2010. It demonstrates how the parameter symbolic dynamics represents the non-linear behavior of biological signals. The parameter of the symbolic dynamics is supported by the EEG to describe the level of anesthesia depth. The results are transferred into symbolic numbers and finally words. From the words and the sequence of different words and the same words, the depth of anesthesia is easily reproduced in readable histograms. The document Albrecht: Narkosemonitoring - vital parameters and depth of anesthesia, University Hospital Erlangen, anaesthesiological clinic, a monitoring of the depth of anesthesia with the computer-assisted EEG monitor NARCOTREND is described. The subject matter is the possibilities of obtaining statements about the contents of the anesthesia monitoring and the procedural limits of the EEG monitoring. Relevant results show that a closed-loop technique, ie regulation of the drug applicator, can not be achieved by the anesthetic monitor.

A general problem of the aforementioned prior art is thus that a pain strength measurement and assessment during anesthesia so far is not possible. The known monitoring systems are not suitable for detecting the occurrence of lack of anesthetic depth or intraoperative alertness early and reliably. The metrological quantification of pain intensity is missing. In critical situations, it is objectively impossible to distinguish between the need to administer a sleep aid or tranquilizer. The result is that hypnotics and sedatives are administered for safety and thus the overdose is made with all the negative consequences. As heart rate variability or heart rate variability (HRV) is in the article: heart rate variability, Wikipedia http://de.wikipedia.org/wiki/Herzfrequenzva- riabil% C3% A4t, the ability of an organism (human, mammal) called the frequency to change the heart rhythm. Even at rest spontaneous changes in the time interval between two heartbeats occur.

Through autonomous physiological regulatory pathways, a healthy organism consistently adjusts the heart rate to current needs. As a rule, physical stress or mental stress usually results in an increase in the heart rate, which usually returns when relief and relaxation are achieved. This shows a higher adaptability to stress in a greater variability of the heart rate. On the other hand, under chronic stress, both are more or less restricted and, as a result, reduced because of the constant high level of tension typical of them.

The distance between two heart beats is usually defined as the time between the beginning of two contractions of the ventricles. This beginning of the chamber contraction appears in the electrocardiogram (ECG) as a so-called R-wave. The distance between two R waves is therefore referred to as the RR interval (to avoid confusion with the blood pressure indication RR (according to Riva-Rocci), the name NN is sometimes used). The RR interval can be converted into the heart rate as a reciprocal (60 BPM ~ 1000 ms: 60 beats per minute ~ 1000 milliseconds RR distance). The RR intervals are usually not the same length, but are subject to fluctuations. The quantification of these fluctuations is referred to as heart rate or heart rate variability (HRV).

In the healthy individual, a heartbeat is triggered by an impulse of the sinus node as the central impulse generator of the autonomic excitation system of the heart. This, in turn, is under the influence of the superior vegetative nervous system, with an activating influence on the sympathetic nervous system. flow which, inter alia, results in an increase in the heart rate. Physical and mental stress is associated with an increase in the activity of the sympathetic, to be reduced in parallel to the parasympathetic regulated body functions, such as digestion. External influences (stimuli), mental processes (thoughts) or mechanical processes (breathing) interact complexly with each other, but may also have different effects on the heartbeat depending on their own weight.

The ECG of a heart rate monitor is still a central diagnostic procedure in cardiology. From the ECG, a so-called time series of the RR intervals can be determined. The variation of this time series can be quantified by means of different methods with regard to their strength, time scale or internal patterns. A simple statistical quantity for determining the variance is the standard deviation of the RR intervals. There are three areas (domains) that are used to analyze heart rate variability: · Time range ZB (eg standard deviation of RR intervals)

• frequency range FB (eg spectrum of heart rate variability)

• non-linear area NLD (eg Poincare plots)

With regard to their time scale, the fluctuations of the heart rate can be further characterized by spectral analysis. More recently, complex empirical parameters such. B. the fractal dimension used.

Spectral analysis is a very accurate method for determining the frequency components that make up heart rate variability. For example, it provides information about the coupling of respiration and heartbeat (ie their coherence) in the relaxed state. When respiration and heartbeat are well coupled, the spectral analysis gives a clear peak (peak). The relevant measurement spectrum is divided into frequency bands in HRV research, low-frequency band LF (low frequency), high-frequency band HF (high frequency), partially plus another frequency band: VLF (Very-low frequency) band and ULF (ultra low frequency) band. Furthermore, a parameter of the frequency range FB is the heart rate (HR).

Another form of representation of heart rate variability HRV is the histogram. A progress graph of a biofeedback measurement counts how many heartbeats fall into a particular class. With larger HRV, the heartbeats distribute more evenly over as many classes. Under heavy load, the vegetative balance shifts and the HRV is limited to a few classes.

Since heart rate variability has its origin in the function of the autonomic nervous system, in principle it is possible to detect diseases which have an effect on the heartbeat. Diseases that directly affect the autonomic nervous system and illnesses that have an effect on the autonomic nervous system, for example, through permanently increased metabolic stress, must be distinguished.

The invention is therefore based on the object of specifying a method and a device for non-invasive monitoring and determination of pain intensity and depth of anesthesia, which are designed so that the measurement of heartbeat signals and the common display of anesthetics and pain intensity during medical Interventions can be reliably and promptly given to improve the quality of the anesthesia depth profile. In addition, an individualized anesthesia guide should also be sought for economic reasons, wherein

- Facility costs are to be reduced,

- An increase in information for the surgical staff should take place and

- short anesthesia discharge times should be achieved.

The object is solved by the features of claims 1 and 9.

The method for noninvasive monitoring and determination of pain severity and depth of anesthesia during medical procedures is described in patent claim 1

with at least the following steps: Signal acquisition of heartbeats by means of a heartbeat signal measurement arrangement,

Signal processing taking into account a heart rate variability determined from the heartbeat signals and evaluation of processed signals to biosignals,

Biosignalanalyse at least with the determination of time-domain based parameters ZB for the pain intensity P and with determination of nonlinear-based symbolic dynamics parameters SD for the depth of anesthesia D, wherein information about

o Anesthetic depth D and

o pain intensity P

the results are,

the determination of the narcosis depth D by means of the determined symbolic dynamics parameters SD via a predetermined functional dependency D = D (SD) and the determination of the pain intensity by means of the determined tare range based parameters ZB via a predetermined functional dependency P = P (ZB) P performed and the determined depth of anesthesia D and the determined pain intensity P are monitored by display. The function dependence between the parameter of the time range ZB and the pain intensity P with P = P (ZB) as well as the function dependence between the parameter of the symbolic dynamics SD and the depth of anesthesia D with D = D (SD) can each be determined proportionally, in particular linearly. The following steps can be completed:

Detection of heartbeat signals by means of a single heartbeat measurement device, the heartbeat signals indicating the change in heart rate and heart rate variability being calculated,

Calculation of various parameters from heart rate variability in an evaluation unit having functional units to which the parameters are assigned, Comparison of the calculated parameters with specific target values for corresponding decisions in at least one comparison unit or functional unit for decisions as well as

- Display of pain intensity P from the calculated parameters Time range ZB and

Display of the depth of anesthesia D from the calculated symbolic dynamics parameters SD

for monitoring on a connected monitor / anesthesia pain monitor.

Heart rate variability is hereby considered to be the change in heartbeat duration for each heartbeat, i. is defined as a change in heartbeat-to-heartbeat interval. In addition to the parameter symbolic dynamics SD, the parameter frequency range FB can be used to display the depth of anesthesia D.

An associated device for the non-invasive monitoring and determination of pain intensity and depth of anesthesia according to the aforementioned method comprises according to the characterizing part of claim 9

at least

a single arrangement for acquiring / measuring heartbeat signals,

a downstream converter for the conversion of the detected heartbeat signals into electrically digitized biosignals,

a function unit for signal preprocessing, in order to provide the electrical biosignals, taking account of a determined heart rate variability, on the one hand for processing into parameter time range ZB for the pain intensity P and on the other hand for processing into parameter symbolic dynamics SD for the depth of anesthesia D respectively

an evaluation unit having at least two signal channels, which is connected downstream of the functional unit for signal preprocessing, and the signals of the parameter time domain ZB are arranged in a first signal channel and the parameters of the symbolic dynamics signal SD in a second signal channel,

wherein the evaluation unit has a functional unit for calculating the pain intensity P and a functional unit for calculating the anesthetic dose D including program-technical means stored therein, and

- has a decision-system functional unit, which is connected in line with the pain-strength calculation functional unit P and with the anesthesia depth-calculation functional unit D, and performs comparisons of the calculated values with detected output / target values, and

- A display unit, which is intended to display the depth of anesthesia D and the associated pain intensity and monitoring. Not only can the anesthesia D and the pain intensity P be numerically displayed on the display unit, but the anesthesia D can be displayed in the form of a curved course D = D (t) and the pain intensity P can also be displayed in the form of a curve P = P (t) , The display unit may be implemented as a monitor for monitoring the displayed anesthesia depth D and the indicated pain intensity P, preferably as a special anesthetic pain monitor.

The ECG for detecting / measuring heartbeat signals may be replaced by an external input device prior to the induction of anesthesia detected heartbeat signals and conversion of biosignals formed in electrically digital form or in parallel to comparing the pre-operative heartbeats and heartbeats during the medical operation be connected.

The advantage of the invention is that, in contrast to the prior art, an EEG data usage can be explicitly dispensed with. In order to be able to separately measure and display the progress of the depth of anesthesia and the pain intensity of patients without additional equipment during surgery, so that an additional administration of either sleep aids and / or painkillers during ongoing anesthesia can take place and incorrect dosages are avoided, essentially the following Steps to be performed:

a measurement of heartbeat signals by means of a conventional method (preferably by ECG), which are suitable for indicating the change in the heart rate and

from the heart rate variability determined from the signals of the change in the heart rate, different parameters are used for the calculation and the comparison with certain values for corresponding decisions and the subsequent display, in particular parameters of the time range ZB for determining the pain intensity P and parameters of the symbolic dynamics SD and optionally the frequency range FB for determining the depth of anesthesia P.

With the device and the method, a system is to be created which, in addition to the information on the depth of anesthesia, also provides information on the level of pain.

The device comprises a heartbeat measuring device for signal detection and, furthermore, at least one evaluation unit with functional units for biosignal analysis and functional units for forming a rule-based decision system, the execution of the biosignal analysis and the mode of operation of the decision system being based on program-technical means.

The evaluation unit therefore contains functional units which, in their electronic hardware structure and in their program-technical mean interactions, represent a software-supported system for monitoring the depth of anesthesia D during an operative procedure by evaluating cardiovascular biosignals and at the same time statements about the instantaneous pain intensity occurring during the procedure P indicates. Characteristic segments for heart rate analysis, in particular from the ECG signals of the heart rate monitor, are obtained and evaluated. For advanced signal preprocessing, other signals can also be used for monitoring from the one heartbeat meter during anesthesia for cardiovascular anesthesia analysis.

The indicator for the depth of anesthesia D is the calculated special nonlinear parameter Symbolic dynamics SD and the indicator for the pain intensity P are the parameters time range ZB for the pain intensity P, wherein the respective parameters are assigned to functional units of the evaluation unit.

The invention thus describes the existence of a functional relationship between biosignals and the depth of anesthesia D and the pain intensity P.

In particular, three areas - severe pain intensity, average pain intensity, slight pain intensity / no pain intensity - are defined for the perception of pain intensity. The results provide information on the necessary follow-up measures, including medication.

For the depth of anesthesia D, at least three areas - deep anesthesia, general anesthesia and anesthesia - are defined.

It is essential that only one form of the output signals - the detected heartbeat signals - is used to determine the pain intensity P and the anesthesia D.

Among other things, the program-technical means of the evaluation unit realize a mathematical model with an evaluation of characteristic signal segments, in particular the heart rate variability of the heartbeat signals for a rule-based decision system for anesthesia guidance. The following program-technical steps are carried out in the functional units of the evaluation unit:

A) Description of statistical measures of the parameter time domain ZB in a first signal channel and

B) Description of statistical measures of a state space in which the original heartbeat-to-heartbeat intervals are transformed, in the form of the parameter of the symbolic dynamics SD in a second signal channel. The advantages of the invention derive from the intelligent / program-technical evaluation of the algorithms stored in the functional units, which combine the measured variables, parameters and their actual values in terms of content:

a reliable and timely delimitation of depth of anesthesia D and pain intensity P,

- an objective measurement of pain intensity parallel to anesthesia depth monitoring,

- appropriate treatment with pain medications,

- avoidance of incorrect dosages,

- independence from the pEEG partial electroencephalogram procedure and

- use of at least one standard equipment for anesthesia depth monitoring without additional equipment.

The standard equipment may comprise at least one conventional arrangement for measuring heartbeat signals - a heartbeat meter.

Economic advantages are:

- an optimal treatment adaptation and

the routine sensor used - i.e. a conventional arrangement for measuring heartbeat signals - requires no additional sensors on

Patients. In general, an exploitation of existing operating room-related routine sensor technology takes place. Further developments and special embodiments of the invention are specified in further subclaims.

The invention will be explained with reference to an embodiment by means of several drawings.

Show it:

1 shows a device for the non-invasive monitoring and determination of pain intensity P and of depth of anesthesia D during medical interventions with a single arrangement for heartbeat measurement with signal detection,

FIG. 2 shows a parameter symbolic dynamics (SD) -arcosine depth (D) -functional representation, FIG.

Fig. 3 is a Veriaufsdarstellung the anesthesia depth D (t) during various

Periods t of the perioperative phase,

4 shows a parameter time range (ZB) pain intensity (P) function representation and

FIG. 5 is a plot of pain intensity P (t) during various periods of the perioperative phase. FIG. In the following, FIGS. 1 and 2 are considered together.

FIG. 1 shows in general form a device 13 for noninvasive monitoring and for determining the pain severity P and the depth of anesthesia D during medical surgical interventions, wherein at least one conventional arrangement 2 for heart rate measurement and signal acquisition 3, eg an ECG, is provided. In Fig. 1, a patient 1 for signal acquisition 3 of heartbeats connected to the arrangement 2 for heart rate measurement. After a signal acquisition 3 downstream signal preprocessing 4 taking into account the heart rate variability takes place taking into account already stored in the device 13 biometric signals together with the preprocessed signals performing a biosignal analysis. 5

In the method, the parameter time range ZB and the parameter symbolic dynamics SD are determined from the available biosignals, wherein the symbolic dynamics parameter SD is intended to determine and display the depth of anesthesia D, while the parameter time range ZB for determining the pain intensity P and the display thereof on a monitoring unit designed as a display unit 12.

At least with the following steps:

Signal detection of heartbeats by means of a device 2 for heart rate signal measurement,

Biosignalanalyse at least with the determination of time domain based parameters ZB for the pain intensity P and with determination of nonlinear-based symbolic dynamics parameters SD for the depth of anesthesia D, are

Information about

- Anesthetic depth D and

- pain intensity P

the results are achieved,

wherein the determination of the depth of anesthesia D by means of the determined symbolic dynamics parameters SD via a predetermined functional dependence D = D (SD) according to FIG. 2 and the predetermined time domain based parameters ZB via a predetermined functional dependence P = P (ZB) according to FIG 4, the determination of the pain intensity P is carried out and the ascertained depth of anesthesia D and the determined pain intensity P are monitored by means of a monitor 12.

A decision system 6 evaluates the parameter symbolic dynamics SD and the parameter time range ZB for estimating the depth of anesthesia D and the pain intensity P and shows for monitoring appropriate statements on the continuation of the medical intervention by a user 7.

In FIG. 2, an associated parameter symbolic dynamics (SD) - anesthesia depth (D) function representation is shown, wherein in the values of the areas SDo and Do normal heartbeat signals and an associated normal alertness level are present.

The normal level of alertness of a patient is determined prior to induction of anesthesia, the measurement of heartbeats taking into account a determined heart rate variability HRV and its evaluation prior to induction of anesthesia as reference measurement and determination for time domain parameters ZB and symbolic dynamics parameters SD in the stage before the induction of anesthesia.

FIG. 2 shows a linear functional assignment of the parameter symbolic dynamic SD to the depth of anesthesia D:

the range Do of the normal state and without anesthesia corresponds to the high range of the parameter SDo,

- the area D "of anesthesia corresponds to the central area of the parameter symbolic dynamics SD _n and

- The range Dtn of deep anesthesia corresponds to the low range of the parameter symbolic dynamics SDtn.

Deviations from the depth of anesthesia Do (normal state) are reproduced by a deviation of the parameter symbolic dynamics SD ₀ to SD _n , as a result of which the heartbeat measured values obtained can be monitored and evaluated in accordance with FIG. 2.

FIG. 3 contains a progression diagram D = D (t) of the depth of anesthesia D during different periods of time t1 to t6 of the perioperative phase. Taking into account the assignment of the depth of anesthesia D shown in FIG. 2 from the calculated parameter symbolic dynamics SD, the temporal change of the anesthetic depth level D (t) of a patient in the time intervals t1 to t6 is displayed on the monitor 12, wherein the ranges of the parameter SD with SDo, SD _n and SDm are associated with areas Do, D "and Dm of anesthesia depth as shown in FIG.

FIG. 4 shows an associated parameter time range (ZB) - pain intensity (P) - functional representation, whereby normal heartbeat signals and an associated normal level of pain intensity - range without operative pain - are present at the values P ₀ and ZB ₀ . Deviations from the pain intensity Po are reproduced by a deflection of the parameter time range ZBo, as a result of which the received heartbeat measurement values can be evaluated in accordance with FIG. 4.

FIG. 4 shows a functional assignment of the parameter time range ZB to the pain intensity P (pain intensity):

the range P _{0 of} the normal pain intensity state (without operative pain) corresponds to the high range of the parameter time range ZBo, the range Pi of a slight pain intensity corresponds to the middle range of the parameter time range ZBi and

- the range Ps severe pain (high pain intensity) corresponds to the low range of the parameter time range ZB _S. FIG. 5 shows a progression representation of the parameter of pain intensity P during different periods of time t1 to t7 of the perioperative phase. Taking into account the assignment of the pain strengths P shown in FIG. 4 from the calculated parameter time range ZB, the temporal change in the pain intensity level P is displayed in the time intervals t1 to t7 of a patient, corresponding to the ranges of the parameter time range ZB with ZBo, ZBj and ZB _S. Areas Po, Pi and P _{s of} the pain intensity, as shown in Fig. 4 are assigned.

The inventive method and the associated device make it possible that due to the use of a conventional arrangement for heart rate signal measurement no additional sensor on and / or in the patient must be introduced, which means no additional risk burden for the patient 1. The associated device 13 for noninvasive monitoring and for determining pain intensities P and depths of anesthesia D during medical procedures comprises, as shown in a schematic illustration in FIG. 6, at least

an arrangement 2 for detecting / measuring heartbeat signals,

a downstream converter 9 for the conversion of the detected heartbeat signals into electrically digitized biosignals,

a functional unit 4 for signal preprocessing in order to channel the electrical bio-signals, taking into account a determined heart rate variability on the one hand for the processing in parameters PA for the pain intensity P and on the other hand for the processing in parameters symbolic dynamics SD for the depth of anesthesia D,

an evaluation unit 8 having two signal channels 18, 19, which is connected downstream of the signal preprocessing functional unit 4 and receives the signals of the parameter time range ZB via the first signal channel 18 and the signals of the parameter symbolic dynamics SD via the second signal channel 19,

wherein the evaluation unit 8 has a functional unit 10 for determining / calculating the pain intensity curve P and a functional unit 11 for determining the calculation of the depth of anesthesia course D including program-technical means stored therein, and

- has a decision-making functional unit 6, which is connected in line with the pain intensity curve P function / calculation unit 10 and with the depth-of-depth detection / calculation functional unit 11, and makes comparisons of the detected / calculated values with detected output / target values , and

- A monitor / anesthesia pain monitor 12, which is intended to display the depth of anesthesia course D and the associated pain intensity curve P and monitoring.

Before the induction of anesthesia, an external input device 15 with recorded heartbeat signals in the state of analgesia and without anesthesia and in electrically formed biosignals alternatively be used instead of the arrangement 2 or parallel to the arrangement 2.

A memory unit 16 for patient-characteristic data shown in FIG. 1 may be associated with the functional unit 3 for detecting and converting heartbeat signals and the evaluation unit 8 including the decision system 6. Patient characteristic data can be eg BMX, age, sex, medication, type of medical intervention. In addition, according to FIGS. 1 and 6, a unit 17 for problem-triggering alarm activation can be connected in addition to the monitor / anesthetic pain monitor 12 designed as a display unit and / or monitoring unit.

LIST OF REFERENCE NUMBERS

1 patient

2 Arrangement for heart rate signal measurement

3 acquisition / measurement

4 signal preprocessing

5 Biosignal analysis

6 decision-making system

7 users

8 evaluation unit

9 transducers

10 functional unit for storing the parameter time range

11 Function unit for storing the parameters Symbolic dynamics

12 display unit

13 Inventive device

14 Functional unit for biosignal analysis

15 External input device for biosignals for subsequent signal preprocessing

16 Memory unit for patient-characteristic data

17 Problem warning alarm unit

18 First signal channel for determining the time range ZB parameters

19 Second signal channel for determining the parameters Symbolic dynamics SD

SD parameter Symbolic dynamics

D anesthesia depth

t time

Eg parameter time range

P pain intensity

Claims

claims

1. A method for non-invasively monitoring and determining pain severity P and depth of anesthesia D during medical procedures,

with at least the following steps:

Signal acquisition of heartbeats by means of an arrangement (2) for

Heartbeat signal measurement,

o signal conditioning taking into account a heart rate variability determined from the heartbeat signals and evaluation of processed signals to biosignals,

o Biosignalanalyse at least with the determination of time domain based parameters ZB for the pain intensity P and with determination of non-linear-based symbolic dynamics parameters SD for the depth of anesthesia D, where

Information about

o Anesthetic depth D and

o pain intensity P

the results are,

wherein the determination of the depth of anarithm P is carried out by means of the determined symbolic dynamics parameters SD via a predetermined functional dependency D = D (SD) and the determined time domain based parameters ZB via a predetermined functional dependency P = P (ZB) and the determined depth of anesthesia D and the determined pain intensity P are monitored by display.

2. The method according to claim 1,

characterized,

in that for the calculation of the parameter time range ZB and the parameter symbolic dynamics SD, the heart rate variability is used as a change of the heartbeat duration for each heartbeat in the form of a change of the heartbeat-to-heartbeat interval.

3. The method according to claim 1 or 2, characterized,

that the following steps are carried out in detail:

Measurement of heartbeat signals by means of conventional method steps, which are intended to show the change of the heart rate in the form of a heart rate variability.

Calculation of various parameters from the heart rate variability and comparison of the parameters with specific values for corresponding decisions and subsequent display, wherein the parameters of the time range ZB for determining the pain intensity P and the symbolic dynamics SD for determining the depth of anesthesia D are taken into account as parameters.

4. Method according to claims 1 and 2,

characterized,

from the heart rate variability as a further parameter, the parameter of the frequency range is taken into account in addition to the parameter symbolic dynamics SD for the determination of the depth of anesthesia D and its monitoring. 5. The method according to claim 3 or 4,

characterized,

that the following steps are completed:

o detection of heartbeat signals by means of a heartbeat measuring device (2), whereby the heartbeat signals show the change of the heart rate in the form of the heart rate variability,

o calculating different parameters from the heart rate variability in an evaluation unit (8) having functional units (10, 11) to which the parameters are assigned, and

Comparing the calculated parameters with predetermined target values for decisions in at least one comparison unit or functional unit (6) for decisions and

o Display of calculated parameters ZB of the time range for determining the pain intensity P and o Display of calculated parameters Symbolic dynamics SD and optionally of parameters of the frequency range for determining the depth of anesthesia D on a connected display unit (12) for monitoring.

Process according to claims 1 to 5,

characterized,

the following program-technical steps are carried out in the functional units of the evaluation unit (8):

A) Description of statistical measures of the parameter of the time range ZB and

B) Description of statistical measures of a state space in which the original heartbeat-to-heartbeat intervals are transformed, in the form of the parameter of the symbolic dynamics SD.

Process according to claims 1 to 6,

characterized,

at least one functional assignment of the parameter symbolic dynamics SD to the depth of anesthesia D is specified:

the area D _{n of} the narcosis corresponds to the central area of the parameter symbolic dynamics SD _n and

- the range Dm of deep anesthesia corresponds to the low range of the parameter symbolic dynamics SDtn-

Process according to claims 1 to 6,

characterized,

at least one functional assignment of the parameter time range ZB to pain intensity P is indicated:

the range Po of the normal pain intensity state corresponds to the high range of the parameter time range ZB ₀ , the range Pi of a slight pain intensity corresponds to the middle range of the parameter time range ZB and

- the range P _{s of} severe pain with a high level of pain corresponds to the low range of the parameter time range ZBs-

Device (13) for non-invasive monitoring and determination of

Pain severity P and of depth of anesthesia D,

according to the method according to claims 1 to 8,

characterized,

that it at least includes

o an arrangement (2) for detecting / measuring heartbeat signals, o a downstream converter (9) for the conversion of the detected

Heartbeat signals in electrically digitized biosignals,

o a functional unit (4) for signal preprocessing, in order to calculate the electrical biosignals taking into account a determined heart rate variability on the one hand for processing in parameter time range ZB for pain intensity P and on the other hand for processing in parameter symbolic dynamics SD for anesthetic depth D from the ascertained heart rate variability

o an evaluation unit (8) having at least two signal channels (18, 19) which is connected downstream of the functional unit (4) for signal preprocessing and the signals of the parameter time range ZB from the first signal channel (18) and the signals of the parameter symbolic dynamics SD from the second signal channel (19),

o wherein the evaluation unit (8) has a functional unit (10) for determining the pain intensity P and a functional unit (11) for determining the depth of anesthesia D including program-technical means stored therein, and

o has a functional unit (6) for a decision system, which is connected to the functional unit (10) for determining the pain intensity P and to the functional unit (1 1) for determining the depth of anesthesia D. is moderately connected and performs comparisons of the calculated values with detected output / setpoints, and

o a display unit (12) on which an indication of the depth of anesthesia D and the associated pain intensity P is provided for monitoring.

10. Device according to claim 9,

characterized,

in that the display unit (12) is designed in such a way that an indication of the depth of anesthesia course D = D (t) and of the associated pain intensity curve P = P (t) is provided for monitoring.

11. Device according to claim 10,

characterized,

the display unit (12) is designed as a monitor.

12. Device according to claim 9,

characterized,

in that an external input device (15) is provided with heartbeat signals detected before the induction of anesthesia and biosignals formed in electrically digital form and optionally connected to the transducer (9) for converting the heartbeat signals at least into the heart rate variability HRV.

13. Device according to claim 9,

characterized,

in that a memory unit (16) for patient-characteristic data is assigned to the functional unit (3) for detection and conversion of heartbeat signals and to the evaluation unit (8) including the decision system (6).

14. Device according to claims 9 to 13,

characterized, in that a unit (17) for problem-indicating alarm triggering is connected in addition to the monitor (12) in the form of a display unit and / or monitoring unit.