Method and apparatus for vascular needle dislocation detection

Abstract

A method for vascular needle dislocation detection includes the steps of performing a blood treatment and / or analysis on a patient (104) at a predefined blood flow using a blood analysis loop (102), and recording a blood line pressure data set (202) at predefined time intervals using a blood line pressure sensor (108) of the blood analysis loop (102). The method further comprises a step of filtering the recorded blood line pressure dataset (202) using a processor configured to filter the recorded dataset using a predefined filter function, and a step of testing the filtered blood line pressure dataset using the processor, the processor is further configured to test the filtered blood line pressure dataset (202) based on the test function. Potential vascular needle dislocation is then detected based on a detection function resulting from the testing step (618). Finally, potential vascular needle dislocation (618) is validated or counteracted by static blood line pressure measurements performed by stopping blood flow and keeping the blood line of the blood analysis loop (102) unisolated from the patient (104).

Description

[0001] The present invention relates to medical treatment. More specifically, the present invention relates to a method for vascular needle dislocation detection, in particular a method for venous needle dislocation. Furthermore, the present invention relates to a device for vascular needle dislocation detection, in particular a device for venous needle dislocation detection.

[0002] In many medical treatments, blood is drawn from a patient. For example, hemodialysis treatment is used to remove waste products, toxins, and excess water from a patient via a blood analysis loop. The blood analysis loop pumps the patient's blood and re-injects the blood into the patient after the hemodialysis machine has performed the blood treatment. Needles are inserted into the patient's body, such as arteries and veins, to transport the patient's blood to and from the hemodialysis machine.

[0003] During such blood treatments, needle dislocations can occur unexpectedly, particularly venous needle dislocations. If a venous needle is dislocated, misplaced, or shifted, it can quickly endanger the patient's life if not promptly addressed. Prior art devices and methods for needle dislocation detection may lack sensitivity, accuracy, and specificity with respect to needle dislocation. High sensitivity and accuracy of detection are essential to ensure and facilitate rapid response times to minimize blood loss caused by needle dislocations.

[0004] Thus, it may be desirable to provide an improved method for vascular needle dislocation detection that alleviates at least some of the above-mentioned disadvantages of conventional systems and procedures.

[0005] The method is intended to provide an improved method for detecting accidental vascular (eg, venous or arterial) needle disconnection through improved processing of blood line pressure data.

[0006] This is achieved by the subject-matter of the independent claims, wherein further embodiments are defined in the dependent claims and in the following description.

[0007] According to a first aspect of the present disclosure, a method for detecting vascular needle dislocation is provided. The method comprises the following steps:

[0008] Performing blood therapy and / or analysis on a patient using a blood analysis loop at a predefined blood flow;

[0009] recording a blood line pressure data set at predefined time intervals using a blood line pressure sensor of a blood analysis loop;

[0010] filtering the recorded blood line pressure data set using a processor, the processor being configured to filter the recorded blood line pressure data set using a predefined filter function, in particular a Kalman filter;

[0011] testing the filtered blood line pressure data set using a processor, the processor being configured to test the filtered blood line pressure data set based on a test function, in particular a Wald test; and

[0012] Detect potential vascular needle dislocation based on the detection function λ;

[0013] Confirm or refute potential vascular needle dislocation by static vascular pressure measurement, which is performed by stopping blood flow and keeping the blood line of the blood analysis loop open to the patient.

[0014] The step of detecting a potential vascular needle dislocation comprises comparing the detection function λ with a predefined threshold value B.

[0015] In other words, in summary, to detect vascular needle dislocation, the blood line pressure reference function can track internal slow pressure changes using process statistics.

[0016] In the context of the present disclosure, vascular needle dislocation may refer to a venous needle dislocation, an arterial vein dislocation, or any other needle dislocation of a needle connected to any kind of blood vessel of a patient.

[0017] In the context of the present disclosure, the term "blood analysis loop" may refer to any device that removes blood from a patient and ultimately reinserts the blood into the patient, whether or not any blood therapy or blood analysis is performed.

[0018] In particular, the term "blood vessel" may refer to a blood vessel of the human body.The term "blood line" may in particular refer to a (partial or complete) extracorporeal part of a (blood) circuit (or a blood analysis loop, respectively).

[0019] The blood analysis loop may include several components and / or elements. The blood analysis loop may generally include a blood line and a blood pump. For example, it may also include an inlet for introducing an anticoagulant into the blood flowing in the loop. The blood analysis loop may also include a dialyzer, a treatment and / or analysis machine. Such a dialyzer or machine may also be connected to a dialysate reservoir and a waste receiving container. The blood analysis loop may also include a blood line clamp, such as a venous clamp.

[0020] The blood analysis loop may also include one or more interfaces for interacting with a person and / or another device, such as a user interface and / or an interface for wireless communication.

[0021] The blood analysis loop may comprise two or more blood line pressure sensors, all of which are configured to perform the step of recording blood line pressure data sets at predefined time intervals. This may, for example, be used as a redundancy measure.

[0022] The processor of the method for vascular needle dislocation detection can be physically connected to (and / or be part of) the blood analysis loop. Alternatively or additionally, an external processor can be provided and can interact with the blood analysis loop. The processor can, for example, be part of a computer device and / or a mobile device equipped with a wireless and / or wired interface. Alternatively and / or additionally, the blood line pressure sensor can be equipped with a wireless and / or wired interface.

[0023] The blood line pressure sensor can be a venous pressure sensor or an arterial pressure sensor. If the blood analysis loop includes a blood treatment or analysis machine, the blood line pressure sensor can be placed downstream of the blood treatment or analysis machine. A blood pump can be placed upstream of the blood line pressure sensor.

[0024] The filter function can be any mathematical algorithm that uses a series of measurements or data sets observed over time and produces an estimate of the unknown variable. The filter function according to the present invention can be more accurate than a filter function based only on a single measurement. Preferably, the filter function is a filter function based on a recursive algorithm. Further preferably, the filter function is a Kalman filter function. Alternatively, the filter function can be any filter function based on the method of least squares.

[0025] After filtering the recorded vascular pressure data set, the filtered data set can be tested in a further step via a test function, such as a Wald test function. Alternatively or additionally, a Lagrange multiplier test and / or a likelihood ratio test can also be used as a test function. Preferably, the test performs the following calculation:

[0026] λ(k)=λ(k-1)+μ(k) / σ 2 (k)*(γ(k)-1 / 2μ(k)) (1)

[0027] If λ(k)<0, then λ(k) can be reinitialized to 0. (k) can be a function that models the pressure change due to needle dislocation, and σ 2 (k) can be the variance of the detection function λ(k).

[0028] When the detection function (k) exceeds the threshold B, the vascular needle dislocation event can be detected; where the threshold B is given by the following formula

[0029] B=ln((1-β) / α), (2)

[0030] Where α is the false alarm probability and β is the false negative probability. Note that the thresholds may be defined alternatively.

[0031] The threshold value B may be controlled / controllable by the user. Alternatively or additionally, the threshold value may be a blood analysis loop related parameter.

[0032] The proposed method may use an algorithm based on a combination of a filter function (e.g., a Kalman filter) and a test function (e.g., a Wald test function). It has been found that the method for vascular needle dislocation detection has a very high accuracy, especially when confirming a true vascular needle dislocation and / or refuting a potential false vascular needle dislocation. The detection delay time of the method may be small, comprising, for example, 5 or less, in particular 3 or less (recording) steps and / or lasting, for example, 50 seconds or less, preferably 30 seconds.

[0033] The sampling time T (=time difference between two samples) may be at least 2 seconds, or at least 5 seconds, or at least 8 seconds, and / or 20 seconds or less, or 12 seconds or less, such as 10 seconds.

[0034] According to an embodiment, the method further comprises the step of initializing the filter function based on at least one statistical parameter.The at least one statistical parameter is preferably dependent on the blood analysis loop.

[0035] The at least one statistical parameter may for example be the variance of the measurement noise and / or the variance of the process noise (i.e. in particular the measurement derivative noise which models the internal dynamics of the blood analysis loop), wherein both the process noise and the measurement noise may be time-dependent functions. The variance of the process noise may be calculated by segmenting the recorded pressure data set into time segments and taking the slope of a linear regression of the corresponding time segments.

[0036] According to an embodiment, the method further comprises a step of initializing the filter function when (whenever) a therapy parameter of the blood analysis loop changes, in particular based on at least one statistical parameter, wherein the at least one statistical parameter may depend on the blood analysis loop.

[0037] The treatment parameters may include blood flow parameters (e.g. blood flow velocity and / or blood flow rate) and / or blood pump parameters, in particular blood pump delivery rate (and / or blood pump rotation speed). The filter function may be initialized or reinitialized each time the treatment parameters are modified or changed. Thus, the filter function may have a time-dependent dynamic behavior. For example, the filter function may have a wide bandwidth at the beginning of the treatment and may gradually reduce its bandwidth (in particular as the knowledge of the process increases). Increased knowledge of the process may, for example, mean that the accuracy and / or efficiency of the filter function increases over time.

[0038] According to an embodiment, the method further comprises the following steps:

[0039] Automatically restart blood flow if a potential vascular needle dislocation is proven to be erroneous.

[0040] In particular, if an actual vascular needle dislocation does not occur, the blood analysis loop can be controlled, such as to restart treatment and / or restart the blood pump. The blood analysis loop can be controlled and / or actuated by a processor. For example, the processor can actuate the blood pump of the blood analysis loop based on whether the detected vascular needle dislocation is proven to be a false positive.

[0041] This may have the advantage that if a detected needle dislocation happens to be detected falsely, then medical personnel are not required to restart blood flow and / or reactivate the blood pump.

[0042] According to an embodiment, the method further comprises the following steps:

[0043] If a potential vascular needle dislocation is confirmed, the blood analysis loop remains stopped and / or an alarm is triggered.

[0044] Stopping the blood analysis loop may mean that the blood pump is stopped, preferably automatically. For example, when a potential vessel dislocation is confirmed, the processor may trigger the blood pump and preferably (all) other elements of the blood analysis loop to stop. In particular, stopping the blood analysis loop may mean that the blood line clamp is closed.

[0045] In addition, an alarm may be triggered, such as a visual or acoustic alarm. The processor may trigger the mobile device or alarm system to sound an alarm. The alarm may also include information about the patient associated with the needle dislocation. In particular, the alarm includes information about the patient's geographic location (e.g., their ward) and / or the treatment the patient is receiving.

[0046] According to an embodiment, the predefined threshold value B is a function of the false vascular needle dislocation detection probability and the missed vascular needle dislocation detection probability.

[0047] It is also contemplated that the predefined thresholds may be reinitialized or initialized when a treatment parameter of the blood analysis loop changes.

[0048] According to an embodiment, the detection function λ is a time-dependent function and depends on a time-dependent difference between a recorded blood line pressure data set and a filtered recorded blood line pressure data set.

[0049] In other words, the detection function may depend on the function (k), ie, the difference between the recorded venous pressure and the filtered recorded venous pressure, and may thus be given by

[0050] (k)=Z(k)-VP f (k), (3)

[0051] Where Z(k) may be the recorded blood line pressure and VPf(k) may be the recorded blood line pressure after filtering.

[0052] According to an embodiment, the blood flow is constant during each predefined time interval.

[0053] The blood flow can be controlled using a blood pump of the blood analysis loop.

[0054] It may be preferred to control the blood pump of the blood analysis loop such that it pumps blood with a constant blood flow, in particular during each predefined time interval of the blood treatment.

[0055] The blood pump may be controlled or actuated by the processor or another processor.

[0056] According to an embodiment, when the detection function λ exceeds a threshold value B according to a predefined false alarm probability α and false negative probability β, at least the step of detecting potential vascular needle dislocation based on the detection function λ generated by the testing step is triggered.

[0057] In the context of the present disclosure, the predefined confidence interval may include two alarm limits, an upper limit and a lower limit. The confidence interval may depend on the blood flow, i.e., on the configuration of the blood pump of the blood analysis circuit. Exceeding the upper and lower limits mentioned above may mean an additional alarm, alerting the user that there is a problem with the vascular access.

[0058] Another aspect of the present disclosure relates to a device for vascular needle dislocation detection. The device includes a blood analysis loop and a processor, which is configured to control the blood analysis loop and detect potential vascular needle dislocation. The blood analysis loop is configured to perform blood treatment and / or analysis on a patient. In addition, the blood analysis loop includes a blood pump, a blood line pressure sensor, and a blood line clamp. The pressure sensor is configured to record a blood line pressure data set of the patient's blood and transmit the recorded blood line pressure data set to the processor. The processor is also configured to confirm or refute potential vascular needle dislocation, and operate the blood line clamp and / or blood pump based on the confirmation or refutation of potential vascular needle dislocation detection.

[0059] Generally speaking, the apparatus may be configured to perform the methods as described above and below.

[0060] Note that the processor may also be configured to operate, control and / or activate some or all elements of the blood analysis loop.

[0061] According to an embodiment, the processor is further configured to filter the recorded blood line pressure data set using a predefined filter function, in particular a Kalman filter.

[0062] According to an embodiment, the processor is further configured to test the difference between the recorded blood line pressure data set and the filtered blood line pressure data set based on a test function, in particular a Wald test.

[0063] According to an embodiment, the processor is further configured to stop the blood pump of the blood analysis loop, keep the blood line clamp open and instruct the pressure sensor to perform a static vascular pressure measurement to confirm or refute a potential vascular needle dislocation.

[0064] According to an embodiment, the processor is communicatively coupled to the blood analysis loop.

[0065] The communication connection between the processor and the blood analysis loop can be realized via a wireless connection and / or via a cable connection. Note that the communication connection between the processor and the blood analysis loop is preferably a bidirectional connection, so that data and / or information can be transferred (transmitted) in both directions.

[0066] The processor may be communicatively coupled to some elements of the blood analysis loop, such as a blood pump, a blood line clamp, and / or a blood line pressure sensor of the blood analysis loop.

[0067] According to an embodiment, the processor is further configured to trigger an alarm when a potential vascular needle dislocation is confirmed.

[0068] Generally speaking, any features, functions, and / or elements described above and below with reference to one aspect of the disclosure are also applicable to any other aspect of the disclosure as described above and below.

[0069] It should be noted that different aspects of the invention have been disclosed with reference to different subject matters. In particular, some aspects have been disclosed with reference to device claims, while other aspects have been disclosed with reference to method claims. However, a person skilled in the art can infer from the above description and the following description that, unless otherwise disclosed, any combination of features relating to different categories of subject matter, in addition to any combination of features belonging to one category of subject matter, is deemed to be disclosed by the present disclosure. In particular, combinations between features of device claims and features of method claims may be disclosed.

[0070] These and other aspects of the invention will be apparent from and elucidated with reference to the exemplary embodiments described hereinafter.

[0071] In the following, the present invention is described with reference to the drawings, including background explanation and specific embodiments of the present invention. The scope of the present invention is not limited to the specific features disclosed in the context of the drawings.

[0072] Figure 1 An apparatus for vascular needle dislocation detection according to an exemplary embodiment is shown.

[0073] Figure 2 Shown is a blood line pressure data set recorded using a method according to an exemplary embodiment.

[0074] Figure 3 A state-of-the-art mathematical model of blood line pressure based on statistical methods is shown.

[0075] Figure 4 A blood line pressure mathematical model according to an exemplary embodiment of the present invention is shown.

[0076] Figure 5 A blood line pressure data set according to a further exemplary embodiment of the present invention is shown.

[0077] 6 to 12 illustrate simulations of an apparatus for vascular needle dislocation detection according to an exemplary embodiment.

[0078] The accompanying drawings are merely schematic and are not drawn to scale. In principle, identical or similar parts, elements and / or steps in the drawings have identical or similar reference numerals.

[0079] Figure 1 An apparatus for vascular needle dislocation detection according to an exemplary embodiment is shown.

[0080] Figure 1 The device 100 can be used to perform the method described above and below. In particular, Figure 1 The device 100 in the embodiment can be used to perform blood treatment and / or analysis on a patient 104 with a predefined blood flow using a blood analysis loop 102. The blood analysis loop 102 can pump blood toward a blood treatment and / or analysis machine 114 or the like using a blood pump 118. During the blood treatment and / or analysis, a blood line pressure data set is recorded at predefined time intervals using a blood line pressure sensor 108 of the blood analysis loop 102. Reference numeral 109 indicates an optional blood line arterial pressure sensor.

[0081] The predefined time interval may also be referred to as a sampling step. The predefined time interval may be, for example, 10 seconds, 8 seconds, or 6 seconds. The blood line pressure data set may include 1000 sampling steps. Thus, the recording of the blood vessel pressure data set may last, for example, 160 minutes.

[0082] The recorded blood line pressure data set may be transmitted to a processor so that the processor may filter the data set. The data set may be transmitted wirelessly or using wires. The processor is configured to filter the recorded data set using a predefined filter function. A preferred filter function may be a Kalman filter (see Figure 4 ).

[0083] The processor will then test the filtered data set based on a test function. A so-called Wald test function may be used.

[0084] Based on the detection function λ generated by the testing step, a potential venous or arterial dislocation can be detected. However, at this stage of the method, it may happen that the recorded pressure change leading to the detection of needle dislocation has nothing to do with the actual needle dislocation. Therefore, a verification step is performed. After the potential needle dislocation is detected, a static vascular pressure measurement is performed to confirm or refute the potential needle dislocation. To this end, the blood flow is stopped when the blood line of the blood analysis loop 102 is not isolated from the patient 104. In other words, during the static vascular pressure measurement, the blood pump 118 is stopped, but the blood clamp 106 (e.g., venous clamp 106) remains open.

[0085] If confirming that there is potential vascular needle dislocation, blood line clamp 106 is closed, and alarm can be triggered. However, if there is no potential vascular needle dislocation, blood pump 118 can be restarted and blood treatment can be continued.

[0086] Figure 1 The arrow on indicates the flow direction of blood into the blood analysis loop 102. In addition, Figure 1 The blood analysis loop 102 includes an inlet for introducing an anticoagulant 116 into the blood flowing in the loop. A blood treatment and / or analysis machine 114 may be placed on the blood line of the blood analysis loop 102. The blood treatment and / or analysis machine 114 is connected to the dialysate preparation device 110 and the waste receiver device 112.

[0087] Note that, Figure 1 The blood analysis loop 102 shown in the figure can be controlled, operated and / or actuated in whole or in part by a processor, which can be placed outside or inside the blood analysis loop. Therefore, it is contemplated that the blood analysis loop is equipped with one or more communication interfaces, such as (one or more) wireless interfaces (not shown).

[0088] Figure 2 A blood line pressure dataset 202 recorded using a method according to an exemplary embodiment is shown. In particular, the recorded blood line pressure dataset 202 is displayed in relation to the recording time on the horizontal axis. The time may be indicated in seconds. The pressure on the vertical axis may be indicated in mmHg. The recorded pressure dataset shown may be one of many datasets measured during a blood treatment or blood analysis.

[0089] A statistical parameter for a method according to an exemplary embodiment may be the variance of the slope of a plurality of data set segments. The internal variability of the blood pressure measured or recorded in a patient's blood vessel may be represented by so-called process noise. The process noise may be estimated by the variance of the slope of each data set segment, which lasts for a predetermined time, such as 1000 seconds or 100 sampling steps. The corresponding slope may be calculated using a linear regression model 204.

[0090] Therefore, for Figure 2 From the pressure data set, ten slope coefficients can be calculated. Based on this, the variance of the slope can be calculated. Thus, the process noise is obtained.

[0091] A slope calculation based on a linear regression model at each data set segment can be performed for each recorded pressure data set, and a global process noise can be calculated as the average of all treatment variances. Note that the variance of the slope can be calculated based on the linear slope coefficient of each slope. The linear slope coefficient can be given in units of mmHg / sec.

[0092] exist Figure 3 to Figure 1 2, the blood line will be assumed to be a venous line (ie, the blood vessel may be a vein), but this should not be construed as limiting. Other blood vessels / lines may still be considered.

[0093] Figure 3 The mathematical model of venous pressure is shown. In particular, Figure 3 A filter function is shown which enables filtering of the recorded venous pressure data set.

[0094] The variable X is the venous blood line pressure state, e.g., the venous pressure model state: X = (x1, x2). The variable x1 represents the combination of the venous pressure of the patient 104 and the pressure drop caused by the connection between the blood line and the patient's blood vessels, and depends on time k. The variable x2 is the (time) derivative of x1 and therefore represents the rapidity of the change in venous pressure over time. The vector function F is Figure 3 is represented by a box and given by

[0095]

[0096] where T is the sampling time and w(k) is the process noise, modeling the internal variability of blood pressure. Then, the venous pressure VP(K) or Z(k) affected by the measurement noise r(k) is given by

[0097] VP(k)=Z(k)=x1(k)+r(k). (5)

[0098] Note that the process noise is only used in the calculation of x2.

[0099] Figure 4 A blood line pressure mathematical model according to an exemplary embodiment of the present invention is shown. In particular, Figure 4 A Kalman filter function according to an exemplary embodiment of the present invention is shown, which is capable of filtering a recorded venous pressure data set.

[0100] The vector function K(k) is given by Figure 4 The boxes in are represented and are calculated based on the variance Q of the process noise w(k) (ie, an estimate of the variance of the slope as discussed previously) and the variance R of the measurement noise r(k). Note that the vector K is also a function of time k. Figure 4 The characteristics of the Kalman filter shown in change over time. Therefore, the Kalman filter is able to closely track the output of any initialization and reduce / mix (at least part of) the measurement noise.

[0101] Function (k) is the difference between the recorded venous pressure and the filtered recorded venous pressure, and is therefore given by γ(k) = Z(k) - VP f (k) is given and can be used by the test function.

[0102] Figure 5 A blood line pressure data set, such as a venous pressure data set, according to a further exemplary embodiment is shown. In particular, Figure 5 A recorded venous pressure data set 202 obtained via a method according to an exemplary embodiment of the present invention is shown. Figure 5 The gray line in the figure shows the Figure 4 The filtered venous pressure data set 504 is obtained by using a filtering function (filter function).

[0103] Figure 6a and Figure 6b A simulation of an apparatus for vascular needle dislocation detection according to an exemplary embodiment is shown. Figure 6a A venous pressure data set 202 is shown in FIG. 1 . Time may be indicated in seconds. Pressure on the vertical axis may be indicated in mmHg. Figure 6a The corresponding filtered venous pressure data set 504 is also shown on the graph. The dashed line 604 represents the values ​​that are typically set as alarm limits for venous pressure. It is known that these limits can be set automatically by default and may be adjusted manually. The two limits can also be referred to as confidence intervals. The thicker black line 602 represents the blood pump flow setting 602 and is Figure 6a and Figure 6b remains constant throughout the treatment duration.

[0104] Figure 6b and Figure 6aThe results of the test function applied to the treatment, in particular the Wald test function used in the method according to the exemplary embodiment, shown in . Figure 6b The horizontal axis of is a given time (eg, in seconds), and the vertical axis is the detection function λ.

[0105] The test function used (eg, the Wald test function) is given by λ(k)=λ(k-1)+μ(k) / σ 2 (k)*(γ(k)-1 / 2μ(k)) (6)

[0106] And when (if) λ(k) < 0, λ(k) is reinitialized to 0. (k) is a function that models the pressure change due to venous needle dislocation and is a constant, for example, μ(k) = -40 mmHg. σ 2 (k) is the variance of the detection function λ(k), which is a function of Q, R, and time k. The function γ(k) is given by equation (3). Finally, when (if) the detection function (k) exceeds threshold B 606, a venous needle dislocation event 608 is detected. Where threshold B is given by

[0107] B=ln((1-β) / α), (7)

[0108] where α is the false alarm probability and β is the false alarm probability. Figure 6b In FIG. 6 , when the detection function (k) exceeds the threshold value B, a venous needle dislocation event 608 is detected. Figure 6a Obviously, if the detection is based only on the normally set alarm limits 604 (ie, confidence intervals), such events would not be detected.

[0109] Figure 7a and Figure 7b Shown with Figure 6a and Figure 6b Here again, it is worth noting that when the venous pressure remains continuously above the lower alarm limit of the two alarm limits 604, a venous needle dislocation event 610 is detected. Figure 7b Obviously, there is a detection delay. The detection delay may be, for example, three sampling steps, for example, 30 seconds.

[0110] Figure 8a and Figure 8b A further example of a simulation of an apparatus for vascular needle dislocation detection according to an exemplary embodiment is shown. Figure 8a In the example, the initial pressure increase 612 is evident, which may be due to a vascular access problem, but should not be associated with a venous needle dislocation. If the venous pressure exceeds the alarm limit 604, then detection of a vascular access problem will be triggered. However, Figure 8bClearly, the detection function λ does not exceed the threshold B, and thus no potential venous needle dislocation is detected.

[0111] As from Figure 9a and Figure 9b As will be apparent, a filter function (eg, a Kalman filter) can advantageously track larger changes in venous pressure without triggering any false needle dislocation detections.

[0112] pass Fig.10 The example shown in shows further features of the filter functions used. The filter functions and in particular the Kalman filter have a time-dependent dynamic behavior, with a wide bandwidth at the beginning and (gradually) narrowing the bandwidth as the knowledge of the process increases. Fig.10 This feature is illustrated in the example of where the filter function is reinitialized each time the user applies a change in blood pump speed 602. Even in this treatment scenario, no false detection occurs and thus no false alarm is triggered.

[0113] Fig.11 The first blood flow change is shown Fig.10 The details of the previous example. In particular, Fig.11 The high robustness of the method according to the exemplary embodiment of the invention is emphasized. Fig.11 The details of the reinitialization of the filter after a blood flow change 602 are illustrated, where the filter function tracks the measurement of the start of the blood pump change very closely and gradually recovers its standard filtering capability over the next few steps, e.g., over the next 6 to 7 steps. While the filter function is being reinitialized, i.e., during the transition, the filter function may be in a fast tracking mode, thereby keeping the detection of dislocations effectively disabled. This is a temporary situation that may last for a few steps, e.g., 6 to 7 steps (roughly 1 minute).

[0114] Fig.12a and Figure 12b An example of a situation that results in a false vascular needle dislocation detection is shown. A potential vascular needle dislocation 618 is detected when λ(k)>B. Fig.12a and Figure 12b In the example shown, a detected potential vascular needle dislocation can be refuted by a static vascular pressure measurement performed by stopping blood flow and keeping the blood line of the blood analysis loop 102 disconnected from the patient 104 (i.e., keeping the blood line clamp open). Refuting a potential vascular needle dislocation 618 allows blood therapy to continue, such as Fig.12a shown.

[0115] In the claims, the word "comprising" does not exclude other elements or steps and the indefinite article "a" does not exclude a plurality. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Any reference signs in the claims should not be construed as limiting the scope. Parentheses and the term "particularly" indicate optional features (if such parentheses or expressions are not used, it does not mean that any other features are mandatory in the corresponding context).

[0116] I. List of Reference Symbols

[0117] 100 Device for detecting vascular needle dislocation

[0118] 102 Blood Analysis Loop

[0119] 104 patients

[0120] 106 Blood Line Clamp

[0121] 108 Blood line (venous) pressure sensor

[0122] 109 Blood line (arterial) pressure sensor

[0123] 110 Dialysis fluid preparation equipment

[0124] 112 Waste receiver equipment

[0125] 114 Blood treatment and / or analysis machines

[0126] 116 Anticoagulants

[0127] 118 Blood Pump

[0128] 202 Blood Line Pressure Dataset

[0129] 204 Linear Regression Model

[0130] 504 Filtered blood line pressure dataset

[0131] 602 Pump flow setting

[0132] 604 Alarm limit

[0133] 606 Threshold

[0134] 608 Vascular needle dislocation detected

[0135] B Threshold

[0136] w(k) process noise

[0137] r(k) measurement noise

[0138] Q Variance of process noise

[0139] R Variance of measurement noise

[0140] λ(k) test function

[0141] γ(k) is the function used by the test function

[0142] Z(k) recorded blood line pressure

[0143] VP f (k) Recorded blood line pressure after filtration

[0144] T Sampling time

[0145] μ(k) is a function that models the pressure change due to vessel dislocation.

[0146] σ 2 (k) Variance of the test function

[0147] x1(k) blood line pressure

[0148] x2(k) Rapidity of change of blood line pressure over time

Claims

1. A method for detecting vascular needle dislocation, comprising the following steps: Performing blood treatment and / or analysis on a patient (104) using a blood analysis loop (102) at a predefined blood flow; Recording a blood line pressure data set (202) at predefined time intervals using a blood line pressure sensor (108) of a blood analysis loop (102); filtering the recorded blood line pressure data set (202) using a processor configured to use a predefined filter function, in particular a Kalman filter, filtering the recorded blood line pressure data set; testing the filtered blood line pressure data set (202) using a processor configured to test the filtered blood line pressure data set based on a test function, in particular a Wald test; and Detecting potential vascular needle dislocation based on a detection function λ (618); confirming or refuting a potential vascular needle dislocation (618) by static vascular pressure measurements performed by stopping blood flow and maintaining the blood line of the blood analysis circuit (102) disconnected from the patient's (104) blood vessels, Detecting potential vascular needle dislocation (618) includes comparing the detection function λ with a predefined threshold value B.

2. The method according to claim 1, further comprising the steps of: • Initializing a filter function based on at least one statistical parameter, wherein the at least one statistical parameter is blood analysis loop related.

3. The method according to any one of the preceding claims, further comprising the steps of: When a treatment parameter of the blood analysis loop (102) changes, a filter function is initialized based on at least one statistical parameter, wherein the at least one statistical parameter is blood analysis loop related.

4. The method according to any one of the preceding claims, further comprising the steps of: If a potential vascular needle dislocation (618) is refuted, blood flow is automatically restarted.

5. The method according to any one of the preceding claims, further comprising the steps of: If a potential vascular needle dislocation is confirmed, the blood analysis loop (102) remains stopped and / or an alarm is triggered.

6. The method according to any one of the preceding claims, The predefined threshold B is a function of the probability of false needle dislocation detection and the probability of missed needle dislocation detection.

7. The method according to any one of the preceding claims, The detection function λ is a time-dependent function and depends on the time-dependent difference between the recorded blood line pressure data set (202) and the filtered recorded blood line pressure data set (504).

8. The method according to any one of the preceding claims, wherein the blood flow is constant during each predefined time interval; and A blood pump (118) of the blood analysis loop (102) is used to control blood flow.

9. The method according to any one of the preceding claims, When the detection function λ exceeds a threshold value B according to a predefined false alarm probability α and false negative probability β, at least the step of detecting potential vascular needle dislocation based on the detection function λ generated by the testing step is triggered.

10. A device (100) for detecting vascular needle dislocation, comprising: blood analysis loop (102); as well as a processor configured to control the blood analysis loop (102) and detect potential vascular needle dislocation (618); wherein the blood analysis loop (102) is configured to perform blood treatment and / or analysis on a patient (104); The blood analysis loop (102) includes a blood pump (118), a blood line pressure sensor (108) and a blood line clamp (106); wherein the blood line pressure sensor (108) is configured to record a blood line pressure data set (202) of the patient's (104) blood and transmit the recorded blood line pressure data set (202) to the processor; The processor is further configured to confirm or refute a potential vascular needle dislocation (618) and, based on confirming or refuting the potential vascular needle dislocation detection, operate the blood line clamp (106) and / or the blood pump (118).

11. The device (100) according to claim 10, The processor is further configured to filter the recorded blood line pressure data set (504) using a predefined filter function, in particular a Kalman filter.

12. The device (100) according to any one of claims 10 to 11, The processor is further configured to test the difference between the recorded blood line pressure data set and the filtered blood line pressure data set based on a test function, in particular a Wald test.

13. The device (100) according to any one of claims 10 to 12, The processor is also configured to stop the blood pump (118) of the blood analysis loop (102), maintain the blood line clamp (106) open and instruct the blood line pressure sensor (108) to perform a static vascular pressure measurement, such as to confirm or refute a potential vascular needle dislocation (618).

14. The device (100) according to any one of claims 10 to 13, The processor is communicatively connected to the blood analysis loop (102).

15. The device (100) according to any one of claims 10 to 14, The processor is further configured to trigger an alarm when a potential vascular needle dislocation (618) is confirmed.

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