Device and method for identifying a malfunction in an extracorporeal blood circulation

Abstract

Methods and systems for identifying a malfunction in the extracorporeal blood circulation of a dialysis machine are disclosed. The malfunction may be identified by detecting at least one state parameter; determining a first evaluation criterion for identifying a malfunction in the extracorporeal blood circulation (FEB); using the first evaluation criterion, making a decision with respect to the presence of a malfunction in the extracorporeal blood circulation, generating a first error signal, and monitoring the detected state parameter; determining at least one further evaluation criterion; using the at least one further evaluation criterion, making a decision with respect to the presence of a malfunction in the extracorporeal blood circulation and generating at least one further error signal; combining the first error signal and the at least one further error signal to result in a combined error signal; and triggering an alarm if the combined error signal exceeds a predetermined limit value.

Claims

1. A machine control method for identifying a malfunction in an extracorporeal blood circulation of an extracorporeal blood treatment machine, comprising: flowing blood of a patient through the extracorporeal blood circulation; initializing, with a first evaluation unit, at least one state parameter characterizing the extracorporeal blood circulation; detecting, with at least one sensor unit, the at least one state parameter characterizing the extracorporeal blood circulation; detecting, with the at least one sensor unit, at least one disturbance variable in the extracorporeal blood circulation; calculating, with the first evaluation unit, a first state parameter evaluation criterion for identifying at least one malfunction in the extracorporeal blood circulation using the at least one state parameter detected by the at least one sensor unit after initializing; monitoring, with a first monitoring unit connected with the first evaluation unit, the detected at least one state parameter; generating, with the first monitoring unit, a first error signal by using the first state parameter evaluation criterion, and making a decision with respect to the presence of at least one malfunction in the extracorporeal blood circulation; calculating, with a second evaluation unit, at least one second state parameter evaluation criterion using the at least one state parameter detected by the at least one sensor unit after initializing, the at least one second state parameter evaluation criterion different from the first state parameter evaluation criterion; monitoring, with a second monitoring unit connected with the second evaluation unit, the detected at least one state parameter; generating, with the second monitoring unit, a second error signal by using the at least one further evaluation criterion, and making a decision with respect to the presence of a malfunction in the extracorporeal blood circulation; combining, with a combination unit connected to the first monitoring unit and the second monitoring unit, the first error signal and the second error signal, and taking into consideration the at least one detected disturbance variable, to result in a combined error signal indicating the presence of a malfunction; triggering, with the combination unit, an alarm if the combined error signal exceeds a predetermined limit value in positive or negative direction or is within a predetermined value range; and re-initializing, with at least one of the first evaluation unit or the second evaluation unit, one or more state parameters characterizing the extracorporeal blood circulation and one or more state parameter evaluation criteria after triggering the alarm or after detecting the at least one disturbance variable, wherein the at least one detected disturbance variable is considered by the at least one of the first evaluation unit or the second evaluation unit during the re-initializing to adjust monitoring of the detected at least one state parameter.

2. The method according to claim 1, wherein at least one of the first or the second error signal is subjected to a weighting process.

3. The method according to claim 1, wherein the first error signal and the second error signal are combined by mathematically linking the error signals.

4. The method according to claim 1, wherein the at least one state parameter is initialized by assigning an initial value to the state parameter, and at least one of the first or the at least one second state parameter evaluation criterion is determined by using the initial value as well as state parameters detected after the initialization.

5. The method according to claim 1, wherein the detected at least one state parameter is monitored and the at least one malfunction is identified by means of the first state parameter evaluation criterion with a temporal offset relative to monitoring the detected at least one state parameter and identifying a malfunction by means of the at least a second state parameter evaluation criterion.

6. The method according to claim 1, wherein the at least one detected disturbance variable is an ultrafiltration rate, a dialysis fluid flow rate, a blood flow rate, a level control or a preceding alarm.

7. The method according to claim 1, wherein at least one of the first or the at least a second state parameter evaluation criterion is determined by means of a polynomial regression or by means of an exponentially weighted, moving average.

8. The method according to claim 1, wherein a monitored state parameter is the venous blood pressure or the arterial blood pressure.

9. A system for identifying a malfunction in an extracorporeal blood circulation of an extracorporeal blood treatment machine, using the machine control method according to claim 1, comprising: the extracorporeal blood circulation through which blood of a patient is flowed; at least one sensor configured to: detect at least one state parameter characterizing the extracorporeal blood circulation, and detect at least one disturbance variable in the extracorporeal blood circulation; a first evaluation unit configured to: initialize the at least one state parameter characterizing the extracorporeal blood circulation, and calculate a first state parameter evaluation criterion for identifying the presence of the at least one malfunction in the extracorporeal blood circulation using the at least one state parameter detected by the at least one sensor after initializing; a first monitoring unit connected with the first evaluation unit, the first monitoring unit configured to: monitor the detected at least one state parameter, generate a first error signal by using the first state parameter evaluation criterion, and make a decision with respect to the presence of at least one malfunction in the extracorporeal blood circulation; a second evaluation unit configured to calculate at least one second state parameter evaluation criterion using the at least one state parameter detected by the at least one sensor unit after initializing, the at least one second state parameter evaluation criterion different from the first state parameter evaluation criterion; a second monitoring unit connected with the second evaluation unit, the second monitoring unit configured to: monitor the detected at least one state parameter, generate a second error signal by using the at least a second state parameter evaluation criterion, and make a decision with respect to the presence of a malfunction in the extracorporeal blood circulation; and a combination unit connected to the first monitoring unit and the second monitoring unit, the combination unit configured to: combine the first error signal and the second error signal, and taking into consideration the at least one disturbance variable, to result in a combined error signal indicating the presence of a malfunction, and trigger an alarm when the combined error signal exceeds a predetermined limit value in positive or negative direction or is within a predetermined value range; and wherein at least one of the first evaluation unit or the second evaluation unit is further configured to re-initialize one or more state parameters characterizing the extracorporeal blood circulation and one or more state parameter evaluation criteria after triggering the alarm or after detecting the at least one disturbance variable, wherein the at least one detected disturbance variable is considered by the at least one of the first evaluation unit or the second evaluation unit during the re-initializing to adjust monitoring of the detected at least one state parameter.

10. The system according to claim 9, wherein each sensor is connected with only a single evaluation unit for determining a single state parameter evaluation criterion, and each sensor is associated with only a single monitoring unit.

11. The system according to claim 9, wherein each sensor is connected with a plurality of evaluation units for determining a plurality of state parameter evaluation criteria, and each sensor is associated with a plurality of monitoring units.

12. The system according to claim 9 wherein the system is part of the blood treatment machine.

13. The system according to claim 12, wherein the blood treatment machine is a dialysis machine.

14. The system according to claim 9, further comprising at least one of a display device or an alarm device for generating an indication or the alarm, respectively, if the combined error signal exceeds a predetermined limit value in positive or negative direction or is within a predetermined value range.

15. The system according to claim 9, further comprising an emergency stop switch for switching off the blood treatment machine if the combined error signal exceeds a predetermined limit value in positive or negative direction or is within a predetermined value range.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) The invention is best understood from the following detailed description when read in connection with the accompanying drawings. Included in the drawings are the following figures:

(2) FIG. 1 shows a blood circulation of a dialysis machine during a hemodialysis,

(3) FIG. 2 is a schematic illustration of state machines for an evaluation unit and monitoring unit,

(4) FIG. 3 is a schematic illustration of a first embodiment of a system according to aspects of the invention,

(5) FIG. 4 is a schematic illustration of a second embodiment of the system according to aspects of the invention,

(6) FIG. 5 shows a diagram illustrating the venous pressure curve of a patient along with upper and lower limits, which have been determined with a first evaluation unit, as evaluation criteria, and

(7) FIG. 6 shows a diagram illustrating the venous pressure curve of a patient along with upper and lower limits, which have been determined with a second evaluation unit, as evaluation criteria.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

(8) The description of the invention on the basis of the exemplary embodiments of the system according to aspects of the invention and the method according to aspects of the invention is made with reference to so-called venous needle disconnections or dislodgements (VND, Venous Needle Dislodgement). This reference to VND is not limiting and the invention and the described exemplary embodiments may serve for detecting any malfunctions in the extracorporeal blood circulation of a blood treatment device.

(9) Due to movements of the patient or because of an inadequate fastening of a needle or cannula on a patient or due to an insufficient attachment of a blood conduit of an extracorporeal blood circulation to a needle/cannula as the connection between the patient's bloodstream and the extracorporeal blood circulation of a dialysis machine, the needle may get unloosed completely or in part, i.e. a disconnection may occur. This is problematic in particular with a venous needle, as the blood which is correspondingly pressurized is returned back to the patient via said needle. This may additionally increase the risk of a disconnection.

(10) FIG. 1 schematically shows liquid systems of a dialysis machine for a hemodialysis. Instead of or in addition to a hemodialysis, a pure hemofiltration or a hemodiafiltration may be implemented. The dialysis machine is equipped with a system according to aspects of the invention for identifying a malfunction in the extracorporeal blood circulation and is adapted and suited for carrying out a method according to aspects of the invention. The explained exemplary embodiment relates to a venous needle disconnection as one kind of a malfunction in the extracorporeal blood circulation.

(11) In general, FIG. 1 illustrates an extracorporeal system in the form of an extracorporeal blood circulation (ECB) as well as a dialysis fluid system in the form of a dialysis fluid circulation (DKL).

(12) The extracorporeal blood circulation (ECB) connects the dialysis patient 12 to the dialysis machine. During a therapy, blood is taken from the patient 12 via an arterial cannula A and is conveyed, with an arterial blood pump 1 disposed in an arterial blood conduit, to a dialyzer 3 via an arterial air trap 2. The actual treatment of the blood, here a cleaning process, is performed in the dialyzer 3. The blood flows from the dialyzer 3 via a venous air trap 7 in a venous blood conduit and via a venous cannula V back into the patient 12.

(13) The dialysis fluid circulation comprises a dialysis liquid pump 9, a balancing equipment 10 and an ultrafiltration pump 11. With the dialysis liquid pump 9, the dialysis fluid is conveyed in counter-current to the blood through the dialyzer 3. The balancing equipment 10 serves for balancing the dialysis fluid of the dialysis fluid circulation, so that water is not extracted from the patient 12 in uncontrolled manner (dehydration) or he/she is not supplied with too much water (overhydration).

(14) The dialyzer 3 usually consists substantially of numerous hollow fibers each comprising a semipermeable membrane. In the example which is explained on the basis of FIG. 1 (hemodialysis), blood is on one side of the membrane, namely on the side of the extracorporeal blood circulation (ECB), and an electrolyte solution, the so-called dialysis fluid, is on the other side, i.e. on the side of the dialysis fluid circulation (DKL). A diffusion and convection takes place via the membrane of the dialyzer 3, so that the blood is cleaned.

(15) The exemplary embodiment according to FIG. 1 may further comprise additional measuring means, pumps, bubble catching devices etc. which are not shown.

(16) Pressure transducers or pressure sensors 4, 5, 6 serve for monitoring the therapy processes. Specifically, these are an input pressure transducer 4 in the area of the air trap 2, an arterial pressure transducer 5 between the arterial cannula A and the arterial blood pump 1 as well as a venous pressure transducer 6 in the area of the venous air trap 7. In the following, the venous pressure sensor 6 is looked at in detail by way of example.

(17) The venous pressure transducer 6 measures the pressure PV between the air trap 7 or the dialyzer 3 and the venous access V of the patient. Normally, PV is composed of the pressure generated by the blood pump 1 and the pressure in the venous access V of the patient. If there is a malfunction in the extracorporeal blood circulation in the form of a venous needle disconnection (VND), there will be a pressure drop at the venous access V, resulting in PV (venous pressure) showing a pressure drop which is detected with the pressure transducer 6. Due to the fact that the pressure drop corresponds to a VND, PV is a possible sensor value which can be used to detect an FEB in the context of the present invention.

(18) For monitoring the dialysis machine, at least three components are employed according to aspects of the invention: at least two evaluation units each determining an evaluation criterion for identifying an FEB, at least two monitoring units each determining an FEB from the determined evaluation criteria of the evaluation unit, and a combination unit which combines, according to aspects of the invention, the monitoring units and hence the evaluation units. One, more or all three units mentioned above may each comprise a memory unit, an arithmetic unit, an energy supply means and a data line.

(19) An evaluation criterion for identifying an FEB is determined by an evaluation unit for a specific state parameter which is detected with a suitable sensor prior to, during or after a therapy. Examples for evaluation units will be explained below. The evaluation units for the evaluation of the sensor values in the extracorporeal blood circulation can be chosen as desired and depend on the type of the sensor values. The evaluation units may be implemented as self-contained units or as logical units comprising the respective monitoring unit.

(20) FIG. 2 shows a schematic illustration of a state machine for a system according to aspects of the invention. FIG. 3 gives an overview of the individual components and their connection to the dialysis machine.

(21) The state machine provided for a system according to aspects of the invention and illustrated in FIG. 2 shows exemplary states which are passed for a singular/not yet combined identification of an FEB with a detected state parameter (sensor value) and an evaluation criterion applied thereon. In an initialization state, state parameters are initialized which have been evaluated with an arbitrary evaluation unit. To give an example, the evaluation unit may define the limits of a venous pressure PV as the evaluation criteria.

(22) According to one embodiment, the system may stay in the initialization state or the initialization state may be maintained until a desired starting time of the evaluation unit is reached. The initialization advantageously starts at the beginning of a therapy. On the other hand, a re-initialization advantageously occurs after a disturbance variable has been identified and/or after an alarm has been triggered. In this context, disturbance variables may represent factors which could have an adverse effect on an evaluation criterion, so that an FEB is not recognized or is recognized in a wrong way (false alarm).

(23) When the starting time is reached, the evaluation unit changes to an evaluation state in one embodiment of the invention. In said evaluation state, the evaluation unit is supplied with a sensor value as an input and, as the case may be, additionally with a possible disturbance variable with any scanning rate. If the disturbance variable changes, the corresponding evaluation criterion and the evaluation unit can be re-initialized. The re-initialization may be achieved by switching to the initialization state again.

(24) In the evaluation state, an evaluation criterion for the state parameters detected with the sensor is defined preferably in continual manner. This is utilized to identify an FEB. If there are state parameters (e.g. PV values), for example, which are below a limit which is defined as an evaluation criterion, an FEB is assumed in the detection state.

(25) According to an option of the invention, a period of time, in the following referred to as an identification period TIME, can be defined for identifying an FEB. If the state parameter measured by a sensor is outside defined evaluation criteria (limits) for a time which is longer than a selected identification period, an FEB is implied and is detected as such.

(26) An identification period TIME, which has to be exceeded for the identification of an FEB, may be advantageously used to avoid false alarms which may be caused, for instance, by short-term state parameter deviations, e.g. pressure variations. Typically, the identification period TIME is determined depending on the characteristics of an evaluation unit and is not set on the basis of changes in sensor values, as it is known from the patent EP 1 815 878 B1, for example. If a sensor value is beyond the evaluation limits for a time which is not longer than the identification period TIME, a corresponding counter in the arithmetic unit of the monitoring unit concerned can be reset, so that the evaluation unit calculates a new evaluation criterion on the basis of the sensor values. If, however, the identification period TIME is exceeded for an evaluation criterion, there will be a change to the alerting state. In this state, an alarm is triggered. Preferably, possible consequences of an alarm are stopping the blood pump (actuator), closing the venous hose shut-off clip as well as alerting the patient and/or the nursing staff by acoustic and/or visual signals or the like. After a corresponding check and acknowledgement, there will be a change from the alerting state back to the initialization state again. In the latter state, the previously described procedure for identifying an FEB starts anew.

(27) Sensor units, e.g. the pressure sensors 4, 5, 6, are in operative connection with the extracorporeal blood circulation ECB of the dialysis machine illustrated in FIG. 1. FIG. 3 shows the use of n sensor units, for example a first sensor unit 1 and an n-th sensor unit n, with n being a whole natural number. If there are e.g. three sensor units, n is equal to 3, in the case of five units n is equal to 5 etc.

(28) Each sensor unit is connected to an evaluation unit 18, 19, 20 and forwards detected state parameters/sensor values to these. In the example of FIG. 3, the first sensor unit, e.g. the pressure transducer 4, is connected to a first evaluation unit 18 and then to a first monitoring unit 13, the second sensor unit, e.g. the pressure transducer 5, is connected to a second evaluation unit 19 and then to a second monitoring unit 14, and the n-th sensor unit, e.g. the pressure transducer 6, is connected to an n-th evaluation unit 20 and then to an n-th monitoring unit 15. Each evaluation unit 18, 19, 20 and each monitoring unit 13, 14, 15 comprises a memory unit and an arithmetic unit.

(29) Finally, the monitoring units 1 to n (13, 14, 15) are connected to a combination unit 16 where the signals transmitted by the monitoring units 13, 14, 15 are processed (combined) and linked to result in a combined signal. The output of the combination unit 16 is used for controlling the dialysis machine in an open or closed loop, being indicated by a signal line 17.

(30) According to the illustration of FIG. 3, each sensor unit 4, 5, 6 has an evaluation unit 18, 19, 20 associated to it.

(31) After having been transmitted via data lines, the results of the individual monitoring units are combined in the combination unit. For combination, also this unit may utilize the corresponding state machine described above as well as an arithmetic unit, a memory unit, data lines and an energy supply means for identifying a VND/an FEB. In the example given here, the combination unit 16 controls corresponding actuators, among others a venous hose shut-off clip 8 and the blood pump 1 in the extracorporeal blood circulation via the data line 17, so that a safe state is assured in case a malfunction is detected in the extracorporeal blood circulation.

(32) FIG. 3 illustrates the combination of several evaluation units 18, 19, 20 and monitoring units 13, 14, 15 with a combination unit 16. The monitoring units 13, 14, 15 monitor any sensor values independently of one another for a respective singular identification of an FEB. In this context, it is possible to use any evaluation units 18, 19, 20 of different or identical type, and also equal or different sensor values.

(33) Corresponding to FIG. 4, one sensor unit 4 may also have several evaluation units 18, 19 and/or monitoring units 13, 14 associated to it. This means that state parameters (sensor values) detected with a sensor unit can be processed according to aspects of the invention not only by one evaluation unit and the monitoring unit associated to it, but the state parameters (sensor values) can also be delivered to several evaluation units where they are individually processed depending on the evaluation unit and forwarded to the corresponding monitoring unit.

(34) At each point in time of the therapy, each monitoring unit has a variable isFEB as an output of the identification of malfunctions in the extracorporeal blood circulation. The variables isFEB are numbered in FIG. 3 in correspondence with the respective monitoring unit and are named isFEB.sub.1 (for the first monitoring unit 13), isFEB.sub.2 (for the second monitoring unit 14) and isFEB.sub.n (for the n-th monitoring unit 15). The variable isFEB is 1 in the case of an identified malfunction and is 0 in the event that no FEB has been identified. Here, reference is made to the fact that the variable may also take a value between 0 and 1. A combination of the individual monitoring unitswhich make use of various evaluation units for identifying an FEBtakes place in the combination unit 16. The variable isFEB of each of the monitoring units may be multiplied with a weighting w which is defined for each monitoring unit. The product of each multiplication for all monitoring units can be summed up in the arithmetic unit. In other words, the weighted sum of the outputs isFEB of the monitoring units can be established with the weighting w. If said sum exceeds a limit value , one can assume the presence of an FEB and an alert can be initiated.

(35) The combination described above represents only one of numerous possible variants. It is within the scope of the invention to combine the monitoring units with all reasonable mathematical methods and models. Possible other combination variants, for instance, belong to the field of machine learning, for instance weighted or unweighted case analyses, fuzzy models, neuronal networks, SVRs or physical or mathematical models which depend on the temperature or any other physical variables.

(36) The provision of several individual monitoring units and their combination with the combination unit allow that individual evaluation units can have an arbitrarily weighted proportion in the identification of an FEB. This is achieved by a suitable selection of the weighting w and of the limit value . Furthermore, a suitable selection of the respective starting time of the individual evaluation units allows to specify a starting order in which the following monitoring units begin to monitor state parameters. In addition, a suitable starting time further allows to define a temporal delay of the starting points of the evaluation units. These attributes allow the evaluation units to calculate their evaluation criteria (initially) on the basis of sensor values at different points in time and hence to represent a staggered alarm system. Advantageously, this circumstance can reduce or even minimize the number or occurrence frequency of false alarms.

(37) In the example of FIGS. 5 and 6, a first evaluation unit calculates a first evaluation criterion for identifying an FEB on the basis of the venous pressure PV, as a first state parameter, detected with the venous pressure transducer 6. Among others, this process results from FIG. 5 where the abscissa shows the time t in seconds and the ordinate shows the venous pressure PV in mmHG. A continuous line illustrates the course of the venous pressure PV. The first evaluation unit calculates evaluation criteria in the form of an upper limit (UCL, broken line) and a lower limit (LCL, dot-and-dash line) for the venous pressure. FIG. 5 and the way of calculation will be elucidated in more detail below.

(38) A second evaluation unit calculates a second evaluation criterion on the basis of a state parameter, in the present example again captured by the venous pressure transducer 6 on the basis of the venous pressure PV. This procedure is apparent inter alia from FIG. 6 where the abscissa shows the time t in seconds and the ordinate shows the venous pressure PV in mmHG. A continuous line illustrates the course of the venous pressure PV. The second evaluation unit calculates a (second) upper limit (UCL, broken line) and a (second) lower limit (LCL, dot-and-dash line) for the venous pressure. FIG. 6 and the way of calculation will be elucidated in more detail below.

(39) It is possible to use further evaluation units which calculate further evaluation criteria for the presence of an FEB for the same or different state parameters and with identical, similar or other calculation methods. In this respect, reference is made to FIG. 3.

(40) According to aspects of the invention, a monitoring unit detects an FEB on the basis of an evaluation criterion calculated with an evaluation unit. With regard to the example of FIGS. 5 and 6, this means that a first monitoring unit, e.g. the monitoring unit 13, establishes the presence of an FEB on the basis of the first evaluation criterion (PV is between the first lower limit and the first upper limit) calculated by the first evaluation unit 18. To give an example, the first monitoring unit recognizes PV values outside the limit illustrated in FIG. 5, which are present for a longer time period, as being a venous needle disconnection. A second monitoring unit, e.g. the monitoring unit 14, establishes the presence of an FEB on the basis of the second evaluation criterion (PV is between the second lower limit and the second upper limit) calculated by the second evaluation unit 19. To give an example, the second monitoring unit recognizes PV values outside the limit illustrated in FIG. 6, which are present for a longer time period, as being a venous needle disconnection. A further monitoring unit or further monitoring units may establish the presence of an FEB on the basis of evaluation criteria calculated by one or more further evaluation units.

(41) Each monitoring unit generates an error signal which is delivered to the combination unit 16. The latter is used for combining as many monitoring units as desired and hence also the error signals output by them. This combination is of decisive advantage. The presence of an FEB is implied not only on the basis of an evaluated error signal, as is known from prior art, but the combination unit processes a plurality of error signals which have been evaluated preferably in different ways. The strengths and weaknesses of the respective evaluation units and the evaluations processed therein are known, and in this way it is possible to improve the quality of detecting and displaying the malfunction and to minimize false alarms by a targeted selection or processing of the error signals delivered to the combination unit.

(42) In the example of FIGS. 5 and 6, the venous pressure PV detected by the venous pressure transducer 6 is the state parameter which is under evaluation. The first evaluation unit 18 determines the above-mentioned evaluation criteria in the form of the upper limit (UCL) and lower limit (LCL) of the venous pressure on the basis of a polynomial regression, as is explained in more detail below.

(43) The equation for the employed polynomial regression is as follows:

(44) $y\left(t\right)=w_0+w_1.Math.t+w_2.Math.t^2+\mathrm{.Math.}+w_M.Math.t^M=\underset{j=0}{\overset{M}{.Math.}}{w}_j.Math.t^j$

(45) In this equation, w is the weighting of a monom, t is the index of the therapy time and M is the highest order of the polynomial. The detected state parameter (PV value of the venous pressure transducer 6 as the sensor) is modeled by a calculation according to this equation. Any appearing deviation, the so-called approximation error, between the model of the sensor value and the actual sensor values is used for determining the evaluation criteria in the form of the lower limit (LCL for lower control limit) as well as the upper limit (UCL for upper control limit) with the aid of the following equations:

(46) ${\mathrm{UCL}}_t:=y\left(t\right)+k.Math.\sqrt{\frac{{}^2}{t}}$${\mathrm{CenterPoint}}_t:=y\left(t\right)$${\mathrm{LCL}}_t:=y\left(t\right)-k.Math.\sqrt{\frac{{}^2}{t}}$

(47) Here, k is a factor defining the width of the limit value window. The index of the therapy time t is used for determining the averaged approximation error of .sup.2 at a certain point in time of the therapy. Then, the square root of said averaged error is calculated to determine the deviation at a desired index t. This deviation multiplied by the factor k plus or minus the modeled sensor value results in the upper limit of the venous pressure (UCL=upper control limit) and the lower limit of the venous pressure (LCL=lower control limit), respectively.

(48) FIG. 5 illustrates the evaluation criteria which have been determined with the evaluation unit described above in the form of a polynomial regression. On the basis of the detected venous pressure PV and with the polynomial regression, the evaluation criteria in the form of the limits LCL and UCL are calculated over a period of 140 seconds. After approximately 125 secondssaid point in time is marked with DC (for disconnected)a venous needle disconnection (VND) occurs in the illustrated example.

(49) In FIG. 5, the Center Line CL represents a modeling of the venous pressure PV with a polynomial regression of order one. For calculating the limits UCL and LCL, a value of k=4 has been chosen. At the beginning of the calculation, the values have been set near the pulsation of PV. At the point in time DC of the venous needle disconnection, the limits will open. The variable TIME in the monitoring unit has to be chosen such that VND is realized early enough, in particular before the limits are opened too wide. In this example, only the lower limit LCL for identifying the VND is necessary, as the limit of a corresponding monitoring unit is used to identify a VND for PV values below LCL. However, for other sensor values or other malfunctions in the extracorporeal blood circulation, this upper limit UCL may also play a role for identifying.

(50) Some advantages and disadvantages of the polynomial regression are apparent from FIG. 5. After a time lapse of approximately 75 seconds, one can see a short-term increase of the venous pressure in the form of a pulse peak. This entails, directly or within a very short time, a divergence of the upper and lower limits. Such a quick reaction to a short-term, unproblematic pulse peak is disadvantageous because of the divergence of the evaluation criteria. The phenomenon can also be seen after the occurrence of the disconnection DC. However, it is of advantage thatafter the beginning of the measurementthe evaluation criteria in the form of the upper and lower limits are determined in a very short time (after approximately 2 to 3 seconds), and monitoring with respect to FEB is possible.

(51) In the second evaluation unit (see FIG. 6), the evaluation criteria in the form of the upper limit (UCL) and the lower limit (LCL) of the venous pressure are determined on the basis of an averaged exponential weighted average, as explained in more detail below.

(52) The second evaluation unit is essentially based on an exponentially weighted average and a heuristic variance for determining the evaluation criteria in the form of the limits UCL and LCL. In the following, this evaluation unit is also referred to as EWMA. First, the weighting .sub.l with which a sensor value, here the venous pressure, is adopted in the mean, is determined with the equation:
.sub.l=(1{tilde over ()}).Math..sub.l-1+{tilde over ()}.Math..sub.

(53) This is a recursive formula and the parameter {tilde over ()} determines the decrease of the weighting for each recursive step. .sub. an asymptotic value of the weighting, to which the weighting .sub.l converges. The equation
Z.sub.i:=(1.sub.l).Math.Z.sub.i-1+.sub.l.Math.X.sub.l

(54) specifies the actual exponentially weighted average. This equation is a recursive equation and also uses the sensor value X apart from the weighting, in order to calculate an average value. The result of a calculation with this equation is averaged once again using the following calculation:

(55) $p_t:=\frac{1}{t}.Math.\underset{i=1}{\overset{t}{.Math.}}{Z}_i,f\stackrel{\mathrm{.Math.}}{u}rt1$

(56) In this way, it is reached in an advantageous way that the determination is more robust in terms of short-term fluctuations of the sensor value. The averaged result p.sub.l is used in the calculation of the variance according to the following equation

(57) $V\left[p_t\right]=\frac{p_t\left(1-p_t\right)}{t}.Math.\left(1-\frac{1}{t}.Math.\frac{1-{}_t}{{}_t\left(2-{}_t\right)}.Math.\left(1-{\left(1-{}_t\right)}^t\right).Math.\left(2+\left(1-{}_t\right).Math.\left(1-{\left(1-{}_t\right)}^t\right)\right)\right)$

(58) with the current weighting .sub.l to calculate the variance V[p.sub.l]. The result of the variance V[p.sub.l] defines, along with the factor k and the value p, the evaluation criteria in the form of the upper limit UCL and the lower limit LCL at each point in time according to the following equations:
UCL.sub.l:=p.sub.l+k.Math.{square root over (V[p.sub.l])}
CenterPoit.sub.l:=p.sub.l
LCL.sub.l:=p.sub.tk.Math.{square root over (V[p.sub.t])}

(59) FIG. 6 illustrates the evaluation criteria which are determined with the above-mentioned calculation. Sensor values PV of the venous pressure transducer have been detected as state parameters over a time period of 650 seconds. After a period of approximately 570 seconds, there is a venous needle disconnection (VND), and said point in time is marked as DC (disconnected).

(60) The Center Line has been calculated by p. Further, factors k=3, .sub.=0.0095 and {tilde over ()}=0.01 have been used for the calculation. The first value of the weighting .sub.l has been initialized with 1.

(61) FIG. 6 illustrates that the evaluation criteria, in the form of the upper limit UCL and lower limit LCL, which are determined according to the preceding calculation approach PV. However, this procedure takes a certain time, which is disadvantageous when using the second evaluation unit for identifying an FEB shortly after the beginning of the monitoring process, in the present case approximately within the first 300 seconds. But when the evaluation criteria in the form of the upper limit UCL and lower limit LCL are sufficiently close to the pulsation PV after the expiration of said time, they are robust against changes, as can be seen at point in time DC of the VND. Here too, only LCL is necessary for identifying a VND, but also UCL may be relevant in the case of other sensor values or FEBs.

(62) If it should happen that an FEB is determined on the basis of one or both of the previously mentioned evaluation criteria and an error signal is output, a combination in a combination unit is performed according to aspects of the invention. In the present example, a grid search algorithm has been used for determining the optimum parameters for the combination unit. This is an optimization method which has been applied to a test data set of therapies with FEB and without FEB. In this way, it was possible to define most suitable parameters and possibly the best combinations of monitoring units. In doing so, various parameters and combinations are tested with grid search. Such parameters and combinations with the least number of false alarms and the highest number of detected FEBs are taken as the best possible combination or best possible parameters for identifying an FEB. For the optimization with grid search, e.g. five therapies with a respective duration of approximately four hours have been used. Here, ten venous needle disconnections have been simulated in each case. In the course of each individual therapy, machine parameters have been changed every 15 minutes in order to simulate therapy situations which are as difficult as possible and, usually or frequently, trigger false alarms. In order to ensure realistic data, the venous pressure curve during the simulated VNDs has been recorded under realistic conditions and with an internal shunt pressure and shunt flow as in a human.

(63) In the preceding optimization on the basis of the data sets described above, three monitoring units as the best possible combination have been determined by grid search. Here, two polynomial regressions and one EWMA have been used as evaluation criterion. In doing so, the monitoring units are started with special advantage in the following order with a temporal offset of approximately 60 seconds: 1. polynomial regression 2. polynomial regression 3. EWMA

(64) For each monitoring unit, the value for the weightings co amounted to 1.5 and the limit for identifying an FEB was 1.5. Each monitoring unit was able to recognize a VND independently of the other monitoring units. In the course of the determination with a polynomial regression, the values of the venous pressure PV had to be below the lower limit LCL for a period of approximately twelve seconds (TIME) for identifying a VND. With the EWMA method, the values of the venous pressure PV had to be below the lower limit LCL for a period of approximately 60 seconds. The other parameters were as described above and are summarized in the following table:

(65) TABLE-US-00001 Time Posi- Lag M K [s] .sub. {tilde over ()} tion w [s] Polynomial 1 4 12 NA NA 1 1.5 NA NA regression Polynomial 1 4 12 NA NA 2 1.5 NA NA regression EWMA NA 3 60 0.095 0.01 3 1.5 NA NA

(66) This combination has been evaluated with the cited parameters for 58 VNDs, as an example of an FEB and on the basis of fifteen therapies without FEB with a respective duration of four hours. The data sets have been produced in exactly the same way as the data sets which have been used in the previously described grid search method, so that realistic conditions were ensured. The combination unit, with the combination described above and the parameters described above, has identified 55 of a total of 58 VNDs and has triggered 71 false alarms. Compared to this, a conventional alarm system has identified only one single VND and triggered 77 false alarms under identical conditions. This shows the potential of the invention presented here.