Needle detachment detection system and method

Abstract

The present disclosure teaches a system and method of monitoring an extracorporeal blood circuit of a patient and identifying a needle dislodgement. The method comprises identifying a potential needle dislodgement event based on a pressure change of the extracorporeal blood circuit, searching for a heart rate of the patient by analyzing an optical backscatter signal of an optical sensor attached to the extracorporeal blood circuit or by analyzing a pressure signal representing a pressure in the extracorporeal blood circuit, and verifying the potential needle dislodgement event as a needle dislodgement based on an absence of the heart rate.

Description

Cross-references to related applications

[0001] This application claims the benefit of priority to U.S. Provisional Patent Application Serial No. 63 / 593,653, filed October 27, 2023, which is incorporated herein by reference in its entirety as if fully set forth herein. Technical Field

[0002] This disclosure generally relates to the monitoring of extracorporeal blood circuits. In particular, but not exclusively, this disclosure relates to methods and systems for monitoring extracorporeal blood circuits and identifying needle dislodgement. Background Technology

[0003] In the medical field, various devices are known for drawing or supplying fluids to a patient via tubing. Access to the patient is typically established through catheters inserted into body organs or cannulas used for puncturing blood vessels. Maintaining proper access to the patient is crucial during external treatments. Therefore, monitoring the patient's access status is necessary.

[0004] Extracorporeal blood therapy devices, particularly those involving the flow of blood outside the body, require proper connection to the patient. Some extracorporeal blood therapy devices include, for example, dialysis systems and cell separators, which require connection to the patient's vascular system. During extracorporeal blood therapy, blood is drawn from the patient, for example, using an arterial line with an arterial cannula, and then re-supplyed to the patient via a venous line with a venous cannula.

[0005] Needle dislodgement during extracorporeal blood therapy (such as dialysis) is a rare event. However, if dislodgement, particularly venous needle dislodgement (VND), is not detected quickly, it can lead to fatal blood loss within minutes. For example, a patient with a normal blood volume of 3–5 L receiving dialysis at a standard extracorporeal blood flow rate of 200–500 ml / min may experience fatal blood loss within 2–5 minutes after a VND occurs. The reported incidence of VND per treatment ranges widely, from 0.0008% to 0.1%, and it is estimated that 10–33% of VNDs result in death.

[0006] Various access monitoring devices based on different principles have been developed and implemented. However, these conventional methods have several drawbacks. Some of these conventional methods measure venous line pressure in multiple ways, attempting to detect venous non-discharge (VND) based on sudden drops in venous line pressure. However, such pressure monitoring methods are unreliable because sometimes VND or partial VND only causes minute pressure changes in the venous return line. Conventional pressure monitoring systems with sufficient sensitivity to detect such minute pressure changes have been employed, but these systems require adequate damping or averaging to reduce measurement noise, otherwise it will negatively impact the system's response time. Furthermore, these systems often suffer from a large number of false alarms, increasing the burden of monitoring and handling false alarms. Another approach is to place a humidity detector at or near the patient access point, which alarms after blood leaks and accumulates at the detector. Humidity detectors are also not optimal because improper placement can cause the system to malfunction, and the leak path cannot always be reliably predicted. Mechanical line constriction devices are also not optimal due to the risk of improper implementation.

[0007] There is an urgent need for a reliable, robust, and cost-effective solution for detecting needle dislodgement, particularly for intravenous needle dislodgement in extracorporeal blood therapy. Summary of the Invention

[0008] This summary is provided to introduce a series of concepts in a simplified form, which will be further described in the detailed embodiments below. This summary is not intended to necessarily identify key or essential features of the claimed subject matter, nor is it intended to assist in determining the scope of the claimed subject matter.

[0009] This disclosure describes a needle dislodgement detection system and method that addresses common defects. For example, the system according to this disclosure provides a more reliable, robust, fast, and cost-effective needle dislodgement detection solution.

[0010] In one example, a method for monitoring a patient's extracorporeal blood circuit and identifying needle dislodgement includes: identifying potential needle dislodgement events based on pressure changes in the extracorporeal blood circuit; searching for the patient's heart rate by analyzing optical backscattering signals from optical sensors attached to the extracorporeal blood circuit; and verifying the potential needle dislodgement event as needle dislodgement based on the absence of heart rate.

[0011] Alternatively or additionally to any of the above examples, the method may further include: reducing the rotational speed of the blood pump in the extracorporeal blood circuit when a potential needle dislodgement event is identified; and searching for the patient's heart rate while the blood pump is in a reduced rotational speed state. Alternatively or additionally to any of the above examples, when a potential needle dislodgement event is identified, the blood pump rotational speed may be reduced to approximately 50–120 mL / min or a blood flow rate of approximately 100–170 mL / min. Alternatively or additionally to any of the above examples, the method may further include: verifying that the potential needle dislodgement event is not needle dislodgement based on the presence of the patient's heart rate. Alternatively or additionally to any of the above examples, the method may include: after verifying that the potential needle dislodgement event is not needle dislodgement, restoring the blood pump to its previous rotational speed. Alternatively or additionally to any of the above examples, a potential needle dislodgement event may be identified by an algorithm that calculates a needle dislodgement value based on the maximum arterial pressure differential, venous pressure change, arterial pressure, and venous pressure; when the needle dislodgement value is below a threshold, the algorithm identifies a potential needle dislodgement event. Alternatively or additionally to any of the above examples, the optical backscattering signal may represent the backscattering of detected red wavelength light energy. Alternatively or additionally to any of the above examples, an algorithm may be used to search for a patient's heart rate by analyzing the optical backscattering signal in the following manner: filtering the optical backscattering signal data to generate filtered optical backscattering data (FOBD); calculating peak-to-peak value (PTP) by subtracting the minimum FOBD from the maximum FOBD; calculating a significance value based on the PTP value; identifying and indexing peaks from the FOBD that have a significance value higher than a significance threshold (PT) and an inter-peak distance higher than the minimum inter-peak distance (min PD); calculating the peak time when more than one peak is indexed; and calculating the heart rate based on the peak time. Alternatively or additionally to any of the above examples, the method may further include: verifying that a potential needle dislodgement event is not needle dislodgement based on the presence of heart rate (HR) within a set heart rate range, FOBD variance within a set variance range, and blood pump rate (BPR) within a set blood pump rate range. Alternatively or additionally to any of the above examples, the method may further include: identifying a patient's arterial heart rate by analyzing changes in arterial pressure in the extracorporeal blood circuit, wherein a set HR range is determined based on the identified arterial heart rate. Alternatively or additionally to any of the above examples, verification of a potential needle dislodgement event may also be based on the presence of an arterial heart rate within a set arterial heart rate range. Alternatively or additionally to any of the above examples, the optical sensor may be attached to a venous line in the extracorporeal blood circuit, and needle dislodgement is defined as venous needle dislodgement.

[0012] In another example, a system for detecting needle dislodgement in a patient's extracorporeal blood circuit includes: a computing device; a processor; and a memory containing instructions that, when executed by the processor, cause the system to: receive venous pressure signals, arterial pressure signals, and optical backscatter signals from an optical sensor attached to a venous line in the extracorporeal blood circuit; identify potential needle dislodgement events based on changes in the arterial and venous pressure signals; search for the patient's heart rate by analyzing the optical backscatter signals; and verify that a potential needle dislodgement event is a needle dislodgement based on the absence of a heart rate.

[0013] Alternatively or additionally to any of the above examples, the instructions contained in the memory, when executed by the processor, enable the system to: reduce the pump speed of the extracorporeal blood circuit upon detecting a potential needle dislodgement event; and search for the patient's heart rate while the pump is operating at a reduced speed. Alternatively or additionally to any of the above examples, upon detecting a potential needle dislodgement event, the pump speed may be reduced to approximately 50–120 mL / min or a blood flow rate of approximately 100–170 mL / min. Alternatively or additionally to any of the above examples, the instructions contained in the memory, when executed by the processor, enable the system to verify, based on the presence of a heart rate, that the potential needle dislodgement event is not a needle dislodgement. Alternatively or additionally to any of the above examples, the instructions contained in the memory, when executed by the processor, enable the system to restore the pump speed to its previous speed after verifying that the potential needle dislodgement event is not a needle dislodgement. Alternatively or appended to any of the above examples, the instructions contained in the memory, when executed by a processor, enable an algorithm to calculate a needle dislodgement value based on the maximum arterial pressure difference, venous pressure change, arterial pressure, and venous pressure. When the needle dislodgement value is below a threshold, the algorithm identifies a potential needle dislodgement event. Alternatively or appended to any of the above examples, the optical backscattering signal may represent the backscattering of detected red light wavelength energy. Alternatively or appended to any of the above examples, the instructions contained in the memory, when executed by a processor, enable an algorithm to search for a patient's heart rate by analyzing the optical backscattering signal. The algorithm steps include: filtering the optical backscattering signal data to generate filtered optical backscattering data (FOBD); calculating the peak-to-peak value (PTP) by subtracting the minimum FOBD from the maximum FOBD; calculating a significance value based on the PTP value; identifying and indexing peaks from the FOBD that have a significance value higher than the significance threshold (PT) and an inter-peak distance higher than the minimum inter-peak distance (min PD); calculating the peak time when more than one peak is indexed; and calculating the heart rate based on the peak time. Alternatively or as an adjunct to any of the above examples, the instructions contained in the memory, when executed by the processor, enable the system to verify that a potential needle dislodgement event is not a needle dislodgement based on the presence of heart rate (HR) within a set heart rate range, FOBD variance within a set variance range, and blood pump rate (BPR) within a set blood pump rate range. Alternatively or as an adjunct to any of the above examples, the optical sensor may be attached to a venous line in an extracorporeal blood circuit, and the needle dislodgement is defined as venous needle dislodgement.

[0014] In another example, a computer-readable storage device for a needle dislodgement detection system for monitoring a patient's extracorporeal blood circuit includes instructions that, when executed by a processor, cause the needle dislodgement detection system to: receive venous pressure data, arterial pressure data, and optical backscattering data from an optical sensor attached to a venous line in the extracorporeal blood circuit; identify potential needle dislodgement events based on changes in arterial and venous pressure; search for the patient's heart rate by analyzing the optical backscattering signal; and verify that a potential needle dislodgement event is a needle dislodgement based on the absence of a heart rate.

[0015] In another example, a dialysis machine includes: a blood pump; an extracorporeal blood circuit configured to connect the blood pump and the dialyzer to a patient; an arterial pressure monitor and a venous pressure monitor; an optical sensor attached to a venous line of the extracorporeal blood circuit; and a computing device including a processor and a memory, configured to: receive venous pressure signals from the venous pressure monitor, receive arterial pressure signals from the arterial pressure monitor, and receive optical backscatter signals from the optical sensor; identify potential needle dislodgement events based on changes in arterial and venous pressure; search for the patient's heart rate by analyzing the optical backscatter signals; and verify that a potential needle dislodgement event is a needle dislodgement based on the absence of a heart rate.

[0016] Alternatively or additionally to any of the above examples, the computing device may be configured to: reduce the blood pump speed of the extracorporeal blood circuit when a potential needle dislodgement event is identified; and search for the patient's heart rate while the blood pump is at a reduced speed. Alternatively or additionally to any of the above examples, when a potential needle dislodgement event is identified, the blood pump speed may be reduced to approximately 50–120 mL / min or approximately 100–170 mL / min. Alternatively or additionally to any of the above examples, the computing device may be configured to verify that a potential needle dislodgement event is not a needle dislodgement based on the presence of a heart rate. Alternatively or additionally to any of the above examples, the computing device may be configured to restore the blood pump to its previous speed after verifying that the potential needle dislodgement event is not a needle dislodgement. Alternatively or additionally to any of the above examples, the computing device may be configured to execute a needle dislodgement algorithm that calculates a needle dislodgement value based on the maximum arterial pressure difference, venous pressure change, arterial pressure, and venous pressure; when the needle dislodgement value is below a threshold, the computing device identifies a potential needle dislodgement event. Alternatively or additionally to any of the above examples, the optical backscattering signal can represent the backscattering of detected red light wavelength energy. Alternatively or additionally to any of the above examples, an algorithm can be used to search for a patient's heart rate by analyzing the optical backscattering signal in the following ways: filtering the optical backscattering signal data to generate filtered optical backscattering data (FOBD); calculating the peak-to-peak value (PTP) by subtracting the minimum FOBD from the maximum FOBD; calculating a significance value based on the PTP value; identifying and indexing peaks from the FOBD whose significance is higher than the significance threshold (PT) and whose inter-peak distance is higher than the minimum inter-peak distance (min PD); calculating the peak time when more than one peak is indexed; and calculating the heart rate based on the peak time. Alternatively or additionally to any of the above examples, needle dislodgement refers to intravenous needle dislodgement.

[0017] In another example, a method for identifying potential needle dislodgement in an extracorporeal blood circuit based on arterial and venous pressure data includes: filtering the arterial and venous pressure data to reduce noise; calculating a current filtered arterial pressure data value (FAPD) based on at least three arterial pressure data values; calculating a current filtered venous pressure data value (FVPD) based on at least three venous pressure data values; storing the current FVPD values ​​in a queue of current FAPD values ​​and discrete groups; calculating the maximum arterial pressure (MAD) difference from the stored queue of current FAPD values; calculating the venous pressure change (VPC), which is the difference between the current FVPD and the average FVPD of the current FVPD queue; calculating a venous dislodgement value based on the VPC, MAD, current FAPD, and current FVPD; and identifying potential needle dislodgement when the venous dislodgement value is below a set threshold.

[0018] Alternatively or in addition to any of the above examples, the method further includes: identifying the patient's arterial heart rate by analyzing changes in arterial pressure in an extracorporeal blood circuit, wherein filtering of the venous pressure data includes utilizing lock-in signal processing techniques based on arterial heart rate.

[0019] In another example, a method for identifying and calculating a patient's heart rate by analyzing optical backscattered signals from an optical sensor attached to a patient's external blood circuit includes: filtering the optical backscattered signal data to generate filtered optical backscattered data (FOBD); calculating peak-to-peak value (PTP) by subtracting the minimum FOBD from the maximum FOBD; calculating a significance value based on the PTP value; identifying and indexing peaks from the FOBD that have a significance value higher than a significance threshold (PT) and a distance between peaks higher than the minimum interpeak distance (min PD); calculating the peak time when more than one peak is indexed; and calculating the heart rate based on the peak time.

[0020] Alternatively or in addition to any of the above examples, the method further includes: reducing the blood pump speed of the extracorporeal blood circuit to a blood flow rate of approximately 50 mL / min to 120 mL / min or approximately 100 mL / min to 170 mL / min before identifying and calculating the patient’s heart rate.

[0021] In another example, a method for identifying and calculating a patient's heart rate connected to an extracorporeal blood circuit by analyzing pressure signals from a pressure monitor attached to the circuit includes: filtering the pressure signal data to generate filtered pressure data (FPD); calculating peak-to-peak value (PTP) by subtracting the minimum FPD from the maximum FPD; calculating a significance value based on the PTP value; identifying and indexing peaks from the FPD that have a significance value higher than a significance threshold (PT) and a distance between peaks higher than the minimum interpeak distance (minPD); calculating the peak time when more than one peak is indexed; and calculating the heart rate based on the peak time.

[0022] In another example, a method for monitoring a patient's extracorporeal blood circuit and identifying needle dislodgement includes: identifying potential needle dislodgement events based on pressure changes in the extracorporeal blood circuit; searching for the patient's heart rate by analyzing the pressure changes in the extracorporeal blood circuit; and verifying that the potential needle dislodgement event is a needle dislodgement based on the absence of a heart rate. The step of searching for the patient's heart rate by analyzing pressure signals from a pressure monitor attached to the extracorporeal blood circuit includes: filtering the pressure signal data to generate filtered pressure data (FPD); calculating peak-to-peak value (PTP) by subtracting the minimum FPD from the maximum FPD; calculating a significance value based on the PTP value; identifying and indexing peaks from the FPD that have a significance value higher than a significance threshold (PT) and a peak-to-peak distance higher than the minimum peak-to-peak distance (min PD); calculating the peak time when more than one peak is indexed; and calculating the heart rate based on the peak time.

[0023] In another example, a method for monitoring a patient's extracorporeal blood circuit and identifying needle dislodgement includes: identifying potential needle dislodgement events based on changes in arterial and / or venous pressure in the extracorporeal blood circuit; identifying the patient's arterial heart rate by analyzing changes in arterial pressure in the extracorporeal blood circuit; searching for the patient's venous heart rate by analyzing changes in venous pressure in the extracorporeal blood circuit, wherein the search is based on identified enhancement of arterial heart rate; and verifying a potential needle dislodgement event as needle dislodgement based on the absence of venous heart rate.

[0024] Alternatively or additionally to any of the above examples, analyzing venous pressure changes may include filtering venous pressure data using locked signal processing techniques. Alternatively or additionally to any of the above examples, an algorithm may be used to search for a patient's venous heart rate, which analyzes venous pressure by: filtering the venous pressure signal data to generate filtered pressure data (FPD); calculating peak-to-peak value (PTP) by subtracting the maximum FPD from the minimum FPD; calculating a significance value based on the PTP value; identifying and indexing peaks from the FPD that have a significance value higher than a significance threshold (PT) and an inter-peak distance higher than the minimum inter-peak distance (min PD); calculating the peak time when more than one peak is indexed; and calculating the venous heart rate based on the peak time. Alternatively or additionally to any of the above examples, the method may further include: verifying that a potential needle dislodgement event is not needle dislodgement based on the presence of a venous heart rate (HR) within a set venous heart rate range, an FPD variance within a set variance range, and a blood pump rate (BPR) within a set blood pump rate range. Alternatively or additionally to any of the above examples, the set venous heart rate range may be determined based on the identified arterial heart rate. Alternatively, or in addition to any of the above examples, verifying that a potential needle detachment event is not a needle detachment can also be based on the presence of an arterial heart rate within a set arterial heart rate range. Attached Figure Description

[0025] To facilitate the identification of any element or action, the most significant one or more digits in the figure reference numerals refer to the figure number in which the element was first introduced.

[0026] Figure 1 A schematic diagram of an in vitro blood circuit and needle dislodgement detection system according to an embodiment of the present disclosure is shown.

[0027] Figure 2 A needle detachment detection system according to an embodiment of the present disclosure is shown.

[0028] Figure 3 The procedure for detecting needle detachment in an in vitro blood circuit according to an embodiment of the present disclosure is shown.

[0029] Figure 4 The procedure for detecting needle detachment in an in vitro blood circuit according to an embodiment of the present disclosure is shown.

[0030] Figure 5This invention illustrates a process for identifying potential needle dislodgement events based on external blood circuit pressure, according to an embodiment of the present disclosure.

[0031] Figure 6 This document illustrates a process for detecting missing needle detachment based on optical backscattering signals for heart rate detection according to an embodiment of this disclosure.

[0032] Figure 7 This illustrates a process for detecting heart rate and / or blood pump rate from optical backscattered signals according to embodiments of the present disclosure, which can be used as... Figure 6 Part of the process execution.

[0033] Figure 8A To illustrate the time-varying optical backscattered signal that can detect heart rate and blood pump rate, according to an embodiment of this disclosure.

[0034] Figure 8B To illustrate the changes over time in optical backscattering data of the center jump peak and blood pump peak during a clinical study visit (study visit 1), according to an embodiment of this disclosure.

[0035] Figure 9 The procedure for detecting needle detachment in an in vitro blood circuit according to an embodiment of the present disclosure is shown.

[0036] Figure 10 A flowchart of a dialysis system with needle detachment detection function is shown according to an embodiment of this disclosure.

[0037] Figure 11 This document illustrates a procedure for detecting heart rate loss based on changes in in vitro blood circuit pressure, according to an embodiment of the present disclosure, to verify needle detachment.

[0038] Figure 12 This invention illustrates a process for detecting blood pump rate and / or heart rate from changes in external blood circuit pressure according to embodiments of the present disclosure, which can be used as... Figure 11 Part of the process execution.

[0039] Figure 13A A front view of a hemodialysis machine according to an embodiment of the present disclosure is shown.

[0040] Figure 13B Show Figure 13A An enlarged view of the dashed box portion illustrates the flow paths of arterial and venous conduits according to an embodiment of this disclosure.

[0041] Figure 14 A shows a front view of an optical sensor clamping a segment of a vein, according to an embodiment of this disclosure.

[0042] Figure 14 B shows Figure 14An isometric view of the optical sensor and the venous tubing segment of A, according to an embodiment of this disclosure.

[0043] Figure 14 C shows Figure 14 A and Figure 14 A cross-sectional view of the optical sensor of B, according to an embodiment of this disclosure.

[0044] Figure 15A A graph showing the change in optical backscattering data over time collected during a clinical trial visit 1, during which the blood flow rate decreased from the patient's prescribed flow rate to 100 ml / min, according to an embodiment of this disclosure.

[0045] Figure 15B A graph showing the change in optical backscattering data over time collected during a clinical trial visit 1, during which the blood flow rate decreased from the patient's prescribed flow rate to 135 ml / min, according to an embodiment of this disclosure.

[0046] Figure 15C A graph showing the change in optical backscattering data over time collected during a clinical trial visit 1, during which the blood flow rate decreased from the patient's prescribed flow rate to 170 ml / min, according to an embodiment of this disclosure.

[0047] Figure 15D A graph showing the change of pulse rate over time, including the pulse rate from a pulse oximeter and the pulse rate calculated based on optical backscattering data from Study Visit 1, according to an embodiment of this disclosure.

[0048] Figure 16A A graph showing the change in optical backscattering data over time collected during a clinical trial visit 2, during which the blood flow rate decreased from the patient's prescribed flow rate to 100 ml / min, according to an embodiment of this disclosure.

[0049] Figure 16B A graph showing the change in optical backscattering data over time collected during a clinical trial visit 2, during which the blood flow rate decreased from the patient's prescribed flow rate to 135 ml / min, according to an embodiment of this disclosure.

[0050] Figure 16C A graph showing the change in optical backscattering data over time collected during visit 2 of a clinical testing study, during which the blood flow rate decreased from the patient's prescribed flow rate to 170 ml / min, according to an embodiment of this disclosure.

[0051] Figure 16D A graph showing the change of pulse rate over time, including the pulse rate from a pulse oximeter and the pulse rate calculated based on optical backscattering data from Study Visit 2, according to an embodiment of this disclosure.

[0052] Figure 17AA graph showing the change in optical backscattering data over time collected during a clinical trial visit 3, during which the blood flow rate decreased from the patient's prescribed flow rate to 100 ml / min, according to an embodiment of this disclosure.

[0053] Figure 17B A graph showing the change in optical backscattering data over time collected during a clinical trial visit 3, during which the blood flow rate decreased from the patient's prescribed flow rate to 135 ml / min, according to an embodiment of this disclosure.

[0054] Figure 17C A graph showing the change in optical backscattering data over time collected during a clinical trial visit 3, during which the blood flow rate decreased from the patient's prescribed flow rate to 170 ml / min, according to an embodiment of this disclosure.

[0055] Figure 17D A graph showing the change of pulse rate over time, including the pulse rate from a pulse oximeter and the pulse rate calculated based on optical backscattering data from Study Visit 3, according to an embodiment of this disclosure.

[0056] Figure 18 The graph shows the changes in optical backscattering data (infrared, red, green, and blue) over time during laboratory testing, with a blood flow rate of 420 mL / min, during which a simulated intravenous needle detachment was observed, according to an embodiment of this disclosure. Detailed Implementation

[0057] The foregoing has provided a summary of the features and technical advantages of this disclosure to facilitate a better understanding of the detailed description that follows. Those skilled in the art will understand that the embodiments disclosed herein can be readily used as the basis for modifications or the design of other structures to achieve the same objectives of this disclosure. The novel features (whether in organization or manner of operation) and other objects and advantages of this disclosure will be better understood by considering the following description in conjunction with the accompanying drawings. However, it should be clearly understood that the drawings are for illustrative and descriptive purposes only and are not intended to limit the scope of this disclosure.

[0058] The apparatus and methods described in this disclosure relate to using sensors (such as pressure sensors and optical sensors) to monitor extracorporeal blood circuits, detect and measure a patient's heart rate, and detect needle dislodgement.

[0059] Figure 1 A schematic diagram of an extracorporeal blood circuit 100 according to a non-limiting example of this disclosure is shown. Figure 1As shown, blood can be drawn from a patient's arm via an arterial line 102 connected to the patient through an arterial access 104 (e.g., a needle, catheter, cannula). After processing, the blood can be returned to the patient via a venous line 106 and a venous access 108 (e.g., a needle, catheter, cannula). The extracorporeal blood circuit 100 may also include, in particular, an arterial pressure monitor 110, a blood pump 112, a blood therapy device 114, a venous pressure monitor 116, and an optical sensor 118. The tubing can be used in one or more segments of the extracorporeal blood circuit 100 (arterial line 102, venous line 106).

[0060] like Figure 1 As shown, an arterial pressure monitor 110 can be connected to the arterial line 102 between the arterial access 104 and the blood pump 112, and is configured to measure the blood pressure (i.e., arterial pressure) within the arterial line 102 and transmit an arterial pressure signal 110a. The blood pump 112 can be configured to pump blood through an extracorporeal blood circuit 100, including a blood therapy device 114. The blood flow rate through the circuit 100 can be adjusted by increasing or decreasing the rotational speed of the blood pump 112. For example, the blood pump rotational speed can be controlled to produce a blood flow rate of 0 mL / min to approximately 600 mL / min or higher. The blood pump 112 can be, for example, a rotary pump or roller pump, or other suitable type of pump. The blood therapy device 114 can take various forms, including, for example, a dialyzer that can be used for dialysis (e.g., hemodialysis). A venous pressure monitor 116 can be disposed along a venous line 106 between the blood therapy device 114 and the venous access 108, and is configured to measure the blood pressure (i.e., venous pressure) within the venous line 106 and transmit a venous pressure signal 116a.

[0061] Optical sensor 118 may be configured to releasably receive and / or be coupled to venous access 106, for example, between venous pressure monitor 116 and venous access 108. Optical sensor 118 may be coupled to the outer surface of venous access 106 to achieve a non-invasive, airless connection with venous access 106. Optical sensor 118 may be configured to transmit light energy of one or more wavelengths to venous access 106 and blood flow. For example, optical sensor 118 may transmit light energy of red wavelength, infrared wavelength, green wavelength, blue wavelength, or other wavelengths. For example, optical sensor 118 may include one or more light sources (e.g., LEDs), with a first light source outputting red wavelengths and a second light source outputting infrared wavelengths. Optical sensor 118 may also detect backscattering of the transmitted light energy (e.g., red, green, blue, and / or infrared light) and generate an optical backscattering signal 118a. Optical backscattering signal 118a may include a single signal and / or multiple signals. For example, the optical backscatter signal 118a may include a red backscatter signal, an infrared backscatter signal, a green backscatter signal, a blue backscatter signal, separate red, infrared, blue, and / or green backscatter signals, or a combination of backscatter signals. A variety of optical sensors are applicable; one example includes the MAX30102, which is available from Maxim Integrated Products.

[0062] Optical sensors can be used to detect light scattering from blood (pulsating flow) within tubing. The backscattering of blood light detected by the optical sensor can originate from light scattering in a small area of ​​blood near the inner surface of the tubing, and can be based on the optical penetration depth. During each pulsating beat of the blood flow in the extracorporeal blood loop tubing, the flow profile, associated red blood cell concentration, and red blood cell shape within the tubing can all change, which can be detected by the backscattering of light from the optical sensor.

[0063] like Figure 1 As shown, the needle dislodgement detection system 120 can be configured to receive optical backscattering signal 118a, arterial pressure signal 110a, and venous pressure signal 116a from optical sensor 118.

[0064] Figure 2 A block diagram of a needle drop detection (NDD) system 120 is shown, which is a non-limiting example according to this disclosure. The NDD system 120 may include, in particular, a computing device 202 and a data storage device 204.

[0065] Data repository 204 may represent one or more systems for storing data that is accessible and provided to computing device 202, as further described herein. Although illustrated separately from computing device 202, some or all components of data repository 204 may be components of computing device 202.

[0066] The computing device 202 may include, in particular, a processor 208, a memory 210, and an input / output device 212. The processor 208 may include circuitry or processor logic, such as any of a variety of commercially available processors. In some examples, the processor 208 may include multiple processors, a multi-threaded processor, a multi-core processor (regardless of whether multiple cores coexist on the same or separate dies), and / or some other type of multiprocessor architecture through which multiple physically separate processors are linked in some way. Furthermore, in some examples, the processor 208 may include a graphics processing section and may include dedicated memory, multi-threaded processing, and / or some other parallel processing capability. In some examples, the processor 208 may be an application-specific integrated circuit (ASIC) or a field-programmable integrated circuit (FPGA).

[0067] Memory 210 may include a logic section, a portion of which includes an array of integrated circuits forming a non-volatile memory for persistent data storage, or a combination of non-volatile and volatile memory. It should be understood that memory 210 may be based on any of a variety of technologies. In particular, the array of integrated circuits included in memory 210 may be arranged to form one or more types of memory, such as dynamic random access memory (DRAM), NAND memory, NOR memory, and / or the like.

[0068] Input / output device 212 may be any of a variety of devices that receive input and / or provide output. For example, input / output device 212 may include a keyboard or keypad, a display (e.g., touch, non-touch, etc.), LEDs, and / or the like.

[0069] Network interface 214 may include logical components and / or features supporting communication interfaces. For example, network interface 214 may include one or more interfaces operating according to various communication protocols or standards for communication via direct or network communication links. Direct communication may be performed using communication protocols or standards described in one or more industry standards, including derivatives and variants. For example, network interface 214 may facilitate communication via buses such as PCIe, Non-Volatile Memory Express (NVMe), Universal Serial Bus (USB), System Management Bus (SMBus), SAS (e.g., Serial Connected Small Computer System Interface (SCSI)) interfaces, Serial AT Accessory (SATA) interfaces, and / or the like. Furthermore, network interface 214 may include logical components and / or features supporting communication via various wired or wireless network standards, such as the 802.11 communication standard. For example, network interface 214 may be configured to support wired communication protocols or standards such as Ethernet, RS-232, and / or the like. As another example, network interface 214 may be configured to support wireless communication protocols or standards such as Wi-Fi, Bluetooth, ZigBee, LTE, 5G and / or the like.

[0070] Memory 210 may contain instructions 216. During operation, processor 208 may execute instructions 216 to cause computing device 202 to access data from repository 204, such as current and / or historical data of optical backscatter signal 118a, arterial pressure signal 110a, and venous pressure signal 116a, each of which may reside in a record within one or more data repositories 104 or be stored in memory 210. Instructions may include various methods and processes (e.g., processes 300, 400, 500, 600, 700, 900, 1000, 1100, 1200) discussed further herein.

[0071] Figure 3 Process 300 illustrates steps for monitoring a patient's extracorporeal blood circuit (e.g., circuit 100) and identifying needle dislodgement according to some embodiments of this disclosure. Process 300 can be performed, for example, by the NDD system 120 or other devices and systems described herein (e.g., the dialysis system 1300 of FIG. 13). In step 302, process 300 can identify potential needle dislodgement events based on pressure changes in the extracorporeal blood circuit (e.g., arterial and / or venous pressure). Various techniques exist for identifying potential needle dislodgement events based on pressure changes. References herein Figure 5 The further described process 500 is an example of how step 302 can be performed.

[0072] In step 304, process 300 can examine the patient's heart rate by analyzing the optical backscattered signal (e.g., 118a) of an optical sensor (e.g., optical sensor 18) attached to the external blood circuit 100. (See references to this document.) Figure 6 and Figure 7 The further described processes 600 and 700 are examples of how step 304 can be performed.

[0073] In step 306, process 300 can verify a potential needle dislodgement event as an actual needle dislodgement based on the absence of heart rate. For example, if no heart rate is detected (e.g., via step 304), the potential needle dislodgement can be verified as an actual needle dislodgement. If a heart rate is detected, the potential needle dislodgement can be verified as a false alarm. In response to needle dislodgement verification, NDD system 120 can initiate appropriate measures and alarms; alternatively, in response to false alarm verification, NDD system 120 can clear or reset the potential needle dislodgement alarm (e.g., triggered by step 302).

[0074] Figure 4 Process 400 illustrates steps for monitoring a patient's extracorporeal blood circuit (e.g., circuit 100) and identifying needle dislodgement according to some embodiments of this disclosure. Process 400 may be performed, for example, by NDD system 120 or other devices and systems described herein. Process 400 may include some of the same steps as process 300, while also including some different and / or additional steps. In step 402 of process 400, pressure in the extracorporeal blood circuit (e.g., arterial pressure and / or venous pressure) may be monitored. For example, arterial pressure signal 110a and venous pressure signal 116a may be received and analyzed to search for potential needle dislodgement events. In step 404, process 400 may check whether a potential needle dislodgement has been identified. In step 404, if no potential needle dislodgement has been identified (i.e., step 404, "No"), process 400 may return to step 402 and continue. In step 404, if a potential needle dislodgement has been identified (i.e., step 404, "Yes"), process 400 may proceed to step 406. References herein Figure 5 The further described process 500 is an example of a process that can be used to perform steps 402 and / or 404.

[0075] In step 406, the blood pump speed can be reduced. For example, the blood pump speed can be reduced to a speed where the blood flow rate is less than about 200 mL / min, about 150 mL / min, about 125 mL / min, about 100 mL / min, about 75 mL / min, or about 50 mL / min, or between about 130–170 mL / min, about 150–200 mL / min, about 125–150 mL / min, about 100–125 mL / min, about 75–100 mL / min, about 50–75 mL / min, or about 50–120 mL / min. In some embodiments, the blood pump speed can be reduced to a flow rate of about 0 mL / min. The blood pump speed can be reduced rapidly, for example, within less than about 10 seconds, 5 seconds, 4 seconds, 3 seconds, 2 seconds, or 1 second. In step 408, the optical backscatter signal can be analyzed and used to search for and verify whether a patient's heart rate has been detected. (References provided in this document) Figure 6 and Figure 7 The further described processes 600 and 700 together provide an example of how step 408 can be performed. In step 408, if a patient's heart rate is detected (i.e., step 408, "Yes"), the identified potential needle dislodgement is confirmed as a false alarm, and process 400 can proceed to step 410. In step 410, the blood pump speed can be increased to restore the blood pump to its previous operating speed (e.g., the speed before step 406), and then process 400 can return to step 402. In step 408, if no patient's heart rate is detected (i.e., step 408, "No"), the identified potential needle dislodgement is confirmed as an actual needle dislodgement, and process 400 can proceed to step 412. In step 412, process 400 can stop the blood pump and activate the needle dislodgement alarm state, and / or initiate other appropriate response measures.

[0076] Figure 5 Flow 500 illustrates steps for identifying potential needle dislodgement events based on changes in extracorporeal blood circuit pressure according to some embodiments of the present disclosure. For example, flow 500 can be used to perform actions such as... Figure 3 Step 302 shown Figure 4 Steps 402 / 404 Figure 9 Step 902 and / or Figure 10 Steps 1002 / 1004. Process 500 may be performed, for example, by NDD system 120 or other devices and systems described herein (see, for example, dialysis system 1300 of Figure 13).

[0077] Identifying needle dislodgement events based on pressure changes is challenging because pressure fluctuations are caused by a variety of factors. Blood loss from dislodged intravenous needles can lead to a drop in venous pressure; however, other factors can also cause a drop in venous pressure, such as vertical movement of the patient's arm. Furthermore, treatment conditions and other system components of the dialysis system can also affect pressure, including, for example, the blood pump, ultrafiltration pump, replacement pump, and balance chamber.

[0078] In step 502, process 500 may include, for example, processing the raw arterial pressure data and venous pressure data received via arterial pressure signal 110a and venous pressure signal 116a through a filter. The processing may include filtering the raw data, for example, through a low-pass filter to minimize noise in the data. The processed pressure data values ​​(e.g., PPD1, PPD2, PPD3, PPD…) may be stored, for example, in a data repository 204 and / or a memory 210. The raw arterial and venous pressure data may be sampled at frequencies such as once per second, twice per second, five times per second, ten times per second, twenty times per second, thirty times per second, or higher.

[0079] Step 504 may include calculating and storing current arterial filtered pressure data value queues and current venous filtered pressure data value queues using the corresponding processed arterial and venous pressure data. The current filtered pressure data (FPD) for each may be calculated based on one or more previous PPD values ​​(e.g., PPD1, PPD2, PPD3). For example, the FPD may be calculated using the following Formula 1: FPD3=PPD1+PPD3+2*PPD2—k1*FPD1+k2*FPD2 Formula 1 Constants k1 and k2 can be adjusted based on the desired smoothness level. Formula 1 can be executed and repeated for arterial and venous PPD values ​​to establish a current arterial filtered pressure data (AFPD) queue and a current venous filtered pressure data (VFPD) queue. The current AFPD or VFPD value queue can contain more than 100, 150, 200, 250, or 300 values. For example, according to one implementation, the queue can contain 280 AFPD values ​​or 280 VFPD values, corresponding to a 14-second data duration sampled at a rate of 20 times per second. Other sampling rates and / or sample numbers can be used in other implementations. Each data queue (i.e., AFPD and VFPD) can be continuously updated as new data is received and new FPD values ​​are calculated, thereby replacing the oldest data.

[0080] Step 506 may include calculating and storing the maximum arterial pressure difference (MAD) based on the maximum and minimum AFPDs in the AFPD cohort. This can be calculated, for example, using the following Equation 2: MAD=Maximum AFPD—Minimum AFPD Formula 2 In step 508, process 500 may include calculating and tracking venous pressure changes (VPC). VPC may be calculated based on the current venous pressure variability (VFPD) and the average VFPD of the cohort, for example using the following formula 3: VPC = Current VFPD - Queue Average (VFPD) Formula 3 In step 510, process 500 may optionally include filtering the VPC and MAD values. For example, VPC or MAD values ​​above a specific threshold or differing from the moving average by one standard deviation may be excluded. This helps filter out data anomalies that could lead to false alarms.

[0081] In step 512, process 500 may include calculating a needle detachment detection (NDD) value, which may be calculated, for example, based on VPC, MAD, VFPD, and AFPD using the following formula 4: NDD value = VPC + (MAD*(1+((venous FPD3-arterial FPD3) / 500))) Formula 4 In step 514, the NDD value can be compared with a set threshold. If the NDD value is lower than the set threshold (i.e., step 514, "Yes"), process 500 can proceed to step 516, where a possible needle detachment is identified or marked. Reaching step 516 and thereby identifying a possible needle detachment can trigger, for example, process 300 moving from step 302 to step 304, process 400 moving from step 404 to step 406, process 900 moving from step 902 to step 904, and / or process 1000 moving from step 1004 to step 1006. If the NDD value is higher than the set threshold (i.e., step 514, "No"), process 500 can return to step 502 and repeat.

[0082] Figure 6 Process 600 illustrates executable steps for verifying needle dislodgement as actual needle dislodgement based on the absence of a patient's heart rate. For example, process 600 can be configured as follows: Figure 3 The completion of step 302 indicates that process 600 can be used to execute steps 304 and 306. Process 600 can also be... Figure 4 The completion of step 406 is shown, and process 600 can be used to execute step 408.

[0083] In step 602, process 600 may include receiving optical backscattered data and storing it in a corresponding queue. The optical backscattered data may include data of multiple wavelengths, such as all four wavelengths (red, infrared, green, and blue), and / or combinations of two or more of these four. The optical backscattered data may be sampled at, for example, at least 2 times per second, 5 times per second, 10 times per second, 20 times per second, 30 times per second, or higher.

[0084] In step 604, process 600 may include filtering the optical backscattering data stored in the queue to generate filtered optical backscattering data (FOBD). Filtering may include smoothing once or multiple times, for example, sorting the optical backscattering data based on the smoothness of the data, such as dividing it into two categories (i.e., “smoothed” or “micro-smoothed”), and then subtracting the smoothed data from the micro-smoothed data. In some embodiments, step 604 may include additional filtering and / or processing to generate FOBD, such as resampling at a higher rate, taking the first derivative of the data, and / or taking the second derivative of the data. In some embodiments, step 604 may include a combination of steps, such as resampling, smoothing, and taking the first and second derivatives of the data.

[0085] In step 606, process 600 may include calculating the variance of FOBD. The variance may be calculated, for example, by taking the average of the squared deviations from the mean. Alternative variance calculation techniques may also be used.

[0086] In step 608, process 600 may include searching for and detecting (if present) blood pump rate (BPR) and / or patient heart rate (HR) from the FOBD. For example, Figure 7 The process 700 illustrates the steps that can be used to perform step 608, which will be described in further detail herein.

[0087] In step 610, process 600 may include checking whether variance, BPR, and / or HR are within acceptable ranges. For example, if variance is less than a set threshold (e.g., variance threshold), BPR is within a set range (e.g., BPR range), and HR is within a set range (e.g., HR range), these conditions can be used to verify that no intravenous needle dislodgement has occurred (i.e., step 610, "Yes"), process 600 may continue to step 612, and may clear [the process]. Figure 5Step 516 indicates a possible needle detachment. After step 612, process 600 may return to step 602 or 604. In some embodiments, instead of checking variance, BPR, and HR, step 610 may check whether two or only one of these three variables is within a corresponding set range. For example, in some embodiments, step 610 may check that the variance is within an acceptable variance range or below a variance threshold, and check that HR is present and / or within a set HR range. In another embodiment, step 610 may only check that HR is present and / or within a set HR range; if so, process 600 may proceed to step 612. In other embodiments, additional conditions may be checked in addition to variance, BPR, and HR. In step 610, if the variance, BPR, and / or HR are not within acceptable limits (i.e., step 610, "No"), process 600 may proceed to step 614, where a warning counter is incremented (e.g., +1). Then, step 616 may check whether the warning counter has reached a warning counter limit setpoint (e.g., 1, 2, 3, 4, 5, 6…). If the warning counter limit has not been reached (i.e., step 616, "No"), process 600 may return to step 602 or step 604, allowing process 600 to repeat. If the warning counter limit has been reached (i.e., step 616, "Yes"), process 600 may proceed to step 618 and confirm that no patient heart rate was detected. In some embodiments, after step 610 is "No", process 600 may proceed directly to step 618. Reaching step 618 can be used as a determination that no HR was detected and to verify that a possible needle dislodgement is an actual needle dislodgement. For example, reaching step 618 may trigger the completion of step 306, or as… Figure 4 The process 400 shown proceeds from step 408 to step 412.

[0088] Now turning Figure 7 The process 700. According to some implementations, the steps of process 700 can be performed as described herein to complete step 608 of process 600. Other techniques or processes may be implemented for performing step 608.

[0089] Process 700 may begin at step 702, which may optionally include additional filtering and / or processing of the FOBD. For example, this may include processing non-numerical values ​​(if present), removing DC offset, and / or applying a moving average to the FOBD. In some embodiments, step 702 may include additional filtering and / or processing of the FOBD, such as resampling at a higher rate, taking the first derivative of the data, and / or taking the second derivative of the data. In some embodiments, step 702 may include a combination of steps, such as resampling, smoothing, and taking the first and second derivatives of the data.

[0090] The duration of FOBD in the queue used for process 700 can be, for example, approximately 0–5 seconds, 5–10 seconds, 5–15 seconds, 5–20 seconds, or 10–20 seconds. As new data is received and processed, the new data can replace the oldest FOBD in the queue.

[0091] In step 704, process 700 may include calculating the peak-to-peak value (PTP). For example, PTP can be calculated using Formula 5: PTP = Maximum (FOBD) - Minimum (FOBD) Formula 5 In step 706, process 700 may include calculating a significance (PROM) value for process 700. For example, PROM can be calculated using Formula 6: PROM = 0.5 * PTP (Formula 6) In step 708, process 700 may include calculating and indexing peaks in the FOBD (if any). The indexed peaks may be filtered such that the PROM of the indexed peaks is higher than a significance threshold and the distance between peaks is higher than the minimum peak spacing (PD MIN).

[0092] In step 710, process 700 may check whether more than one peak is indexed. If more than one peak is indexed (i.e., step 710, "Yes"), process 700 may proceed to step 712, which may include calculating the peak time.

[0093] Step 714 may calculate the blood pump rate (BPR) and / or heart rate (HR) based on peak times. In some embodiments, after identifying multiple peak times, step 714 may include running a clustering algorithm on the peaks to select a refined set for calculating BPR and / or HR. Step 714 may include associating peaks with blood pump rate or heart rate. For example, in some embodiments, the two most significant index peaks may be associated with the blood pump, and the blood pump rate may be calculated based on the time between these two peaks. Other peaks (i.e., less significant) may be associated with the patient's heartbeat, and the patient's heart rate may be calculated based on these less significant peaks. In some embodiments, the NDD system 120 may be configured to receive blood pump rate as input, for example from the blood pump or an associated machine (e.g., dialysis machine 1300), and peaks associated with the BPR rate (e.g., "most significant") may be identified, or in some embodiments may be identified by the BPR input.

[0094] The calculated BPR and / or HR can be used as the output of step 608 in process 600 and the input of step 610. Figure 8A Figure 8 shows the calculated FOPD (FoD) of BPR and HR over time, based on laboratory data. As shown in Figure 8, the blood pump operated at a blood flow rate of 100 mL / min, and a heart rate of 72 beats / min was detected and calculated. In this experiment, the pump was used to simulate the patient's heartbeat.

[0095] Figure 8B To plot the FOPD over time for the identified peak blood pump and peak heart rate, the blood pump rate (e.g., approximately 135 ml / min) and heart rate (e.g., approximately 69.7 bpm) can be calculated. This is used for plotting... Figure 8B The data comes from clinical study visits (study visit 1), and this article references... Figure 15A –15D is discussed further.

[0096] In step 710, if no more than one peak is indexed (i.e., step 710, "No"), process 700 may proceed to step 716. In step 716, a check may be run to see if the maximum peak search count has been exceeded. If, in step 716, the maximum peak search count has been exceeded (i.e., step 716, "Yes"), process 700 may proceed to step 718, which may report that no HR and / or BPR were identified. This can be used as the output of step 608 in step 610, which will cause step 610 to be "No". If, in step 716, the maximum peak search count has not been exceeded (i.e., step 716, "No"), process 700 may proceed to step 720, in which the significance threshold used in step 708 is reduced. Process 700 may then return to step 710 to repeat with the reduced significance threshold, thereby relaxing the filter for indexing peaks.

[0097] In some implementations of process 700, instead of identifying and calculating BPR and / or HR based on peak-to-peak values, trough values ​​can be used to calculate BPR and / or HR. For example, this can be performed by inverting FOBD (e.g., as part of FOBD filtering and / or processing in step 702), thereby converting troughs to peaks, which can be used in steps 704–720. In some implementations, BPR can be calculated based on peak-to-peak values, while HR can be calculated based on trough values. For example, process 700 can be performed using peak-to-peak values ​​to calculate BPR, and then, in parallel, process 700 can be run using trough values ​​(i.e., by inverting FOBD in step 702) to calculate HR.

[0098] Contrary to process 300, in some embodiments of this disclosure, pressure in the extracorporeal blood circuit can be used to identify and check the patient's heart rate and verify needle dislodgement, rather than using optical backscattering signals. For example, Figure 9 Process 900 and Figure 10 Procedure 1000 illustrates a process for monitoring a patient's extracorporeal blood circuit (e.g., circuit 100) and identifying needle dislodgement based on analysis of pressure changes in the extracorporeal blood circuit. Procedure 900 can be performed, for example, by NDD system 120 or other devices and systems described herein. In step 902, procedure 900 can identify potential needle dislodgement events based on pressure changes in the extracorporeal blood circuit (e.g., arterial and / or venous pressure). Various techniques exist for identifying potential needle dislodgement events based on pressure changes. References herein Figure 5 The described process 500 is an example of how step 902 can be performed.

[0099] In step 904, process 900 can search for the patient's heart rate by analyzing pressure changes (e.g., arterial and / or venous pressure) in the extracorporeal blood circuit 100. (See references in this article.) Figure 11 and Figure 12 The further described processes 1100 and 1200 are examples of how step 904 can be performed.

[0100] In step 906, process 900 can verify a potential needle dislodgement event as an actual needle dislodgement based on the absence of heart rate. For example, if no heart rate is detected (e.g., in step 904), the potential needle dislodgement can be verified as an actual needle dislodgement. If a heart rate is detected, the potential needle dislodgement can be verified as a false alarm. In response to needle dislodgement verification, NDD system 120 can initiate appropriate measures and alarms; alternatively, in response to false alarm verification, NDD system 120 can clear or reset the potential needle dislodgement alarm.

[0101] Now switching to process 1000 and Figure 10 Process 1000 may be performed, for example, by NDD system 120 or other devices and systems described herein. Process 1000 may include some of the same steps as process 900, while also including some different and / or additional steps. In step 1002, the pressure in the extracorporeal blood circuit (e.g., arterial pressure and / or venous pressure) may be monitored. For example, arterial pressure signal 110a and / or venous pressure signal 116a may be monitored and analyzed to search for potential needle dislodgement events. In step 1004, process 1000 may check whether a potential needle dislodgement has been identified. In step 1004, if no potential needle dislodgement has been identified (i.e., step 1004, "No"), process 1000 may return to step 1002. In step 1004, if a potential needle dislodgement has been identified (i.e., step 1004, "Yes"), process 1000 may proceed to step 1006. (References herein) Figure 5The described process 500 is an example of how steps 1002 and 1004 can be performed. In step 1006, the blood pump speed can be reduced. For example, the blood pump speed can be reduced to a speed such that the flow rate is less than about 200 mL / min, about 150 mL / min, about 125 mL / min, about 100 mL / min, about 75 mL / min, or about 50 mL / min, or between about 150–200 mL / min, about 125–150 mL / min, about 100–125 mL / min, about 75–100 mL / min, about 50–75 mL / min, or about 50–120 mL / min. In some embodiments, the blood pump speed can be reduced to a flow rate of 0 mL / min. The blood pump speed can be reduced rapidly, for example, within less than about 5 seconds, 4 seconds, 3 seconds, 2 seconds, or 1 second. In step 1008, pressure signals from the extracorporeal blood circuit (e.g., arterial and / or venous pressure signals) can be analyzed and used to search for and verify whether a patient's heart rate has been detected. (References provided in this article) Figure 11 and Figure 12 The further described procedures 1100 and 1200 are examples of how step 1008 can be performed. In step 1008, if a patient's heart rate is detected (i.e., step 1008, "Yes"), the identified potential needle dislodgement is confirmed as a false alarm, and procedure 1000 can proceed to step 1010. In step 1010, the blood pump speed can be increased to restore the blood pump to its previous operating speed (e.g., the speed before step 1006), and then procedure 1000 can return to step 1002. In step 1008, if no patient's heart rate is detected (i.e., step 1008, "No"), the identified potential needle dislodgement is confirmed as an actual needle dislodgement, and procedure 1000 can proceed to step 1012. In step 1012, procedure 1000 can stop the blood pump and activate the needle dislodgement alarm state, and / or take other appropriate response measures.

[0102] Figure 11 Process 1100 illustrates executable steps for verifying needle dislodgement as actual needle dislodgement based on the absence of a patient's heart rate. For example, process 1100 may be initiated by completion of process step 902, and process 1100 may be used to perform steps 904 and 906, and / or process 1100 may be initiated by completion of step 1006 and used to perform step 1008.

[0103] In step 1102, process 1100 may include receiving the latest pressure signal data (e.g., arterial pressure signal 110a data and / or venous pressure signal 116a data) and storing it in the corresponding queue. The pressure signal data may be sampled at, for example, at a frequency of at least 2 times per second, 5 times per second, 10 times per second, 20 times per second, 30 times per second, or higher.

[0104] Step 1104 may include filtering the pressure signal data stored in the queue to generate filtered pressure signal data (FPD). In some embodiments, the FPD may be only venous pressure data, or in some embodiments, the FPD may be a combination of venous pressure data (VPD) and arterial pressure data (APD). For example, the FPD value may be based on the following formula 7: FPD = Scale Factor * APD - VPD (Formula 7) Filtering the FPD may include, for example, sorting the stress data based on the smoothness of the data, such as dividing it into two categories (i.e., “smooth” or “micro-smooth”), and then subtracting the smoothed data from the micro-smoothed data. Step 1106 may include calculating the variance of the FPD. The variance may be calculated, for example, by taking the average of the squared deviations from the mean. Alternative variance calculation techniques may also be used. Step 1108 may include searching for and detecting (if present) the patient’s heart rate (HR) and / or blood pump rate from the FPD. Figure 12 Process 1200 is an example of an executable process and related steps that can perform step 1108, which will be described in further detail herein.

[0105] Step 1110 may include checking whether the variance, BPR, and / or HR are within acceptable ranges. For example, if the variance is less than a set threshold (e.g., a variance threshold), the BPR is within a set range (e.g., a BPR range), and the HR is within a set range (e.g., a HR range), these conditions can be used to verify that no intravenous needle dislodgement has occurred (i.e., step 1110, "Yes"), and process 1100 may continue to step 1112, and may clear [the process]. Figure 5Step 516 indicates a possible needle detachment. After step 1112, process 1100 may return to step 1102. In some implementations, instead of checking variance, BPR, and HR, step 1110 may check only two or only one of these three conditions. For example, in some implementations, step 1110 may check whether the variance is within an acceptable range and / or below a variance threshold, and check whether HR exists and / or is within a set HR range. In another implementation, step 1110 may only check whether HR exists and / or is within a set range; if so, process 1100 may proceed to step 1112. In other implementations, additional conditions may be checked in addition to variance, BPR, and HR. In step 1110, if the variance, BPR, and / or HR are not within acceptable limits (i.e., step 1110, "No"), process 1100 may proceed to step 1114, where a warning counter is incremented (e.g., +1). Then, step 1116 may check whether the warning counter has reached a warning counter limit setpoint (e.g., 1, 2, 3, 4, 5, 6…). If the warning counter limit has not been reached (i.e., step 1116, "No"), process 1100 may return to step 1102, allowing process 1100 to be repeated. If the warning counter limit has been reached (i.e., step 1116, "Yes"), process 1100 may proceed to step 1118 and confirm that no patient heart rate was detected. In some embodiments, after step 1110 is "No", process 1100 may proceed directly to step 1116. Reaching step 1118 can be used as… Figure 9 The process shown in step 906 of step 900 is triggered, and / or triggered as follows: Figure 10 The process 1000 shown proceeds from step 1008 to step 1012.

[0106] Now turning Figure 12 The process 1200. According to some implementations, the steps of process 1200 can be performed as described herein to complete step 1108 of process 1100. Other techniques or processes may be implemented for performing step 1108.

[0107] Process 1200 may begin at step 1202, which may optionally include additional filtering and processing of the FPD. For example, this may include processing non-numerical values ​​(if present), removing DC offset, and / or applying a moving average to the FPD. The duration of the FPD in the queue used for process 1200 may be, for example, approximately 0–5 seconds, 5–10 seconds, 5–15 seconds, 5–20 seconds, or 10–20 seconds. As new pressure data is received and processed, the oldest FPD in the queue may be replaced.

[0108] In step 1204, process 1200 may include calculating the peak-to-peak value (PTP). For example, PTP can be calculated using Formula 8: PTP = Maximum (FPD) - Minimum (FPD) (Formula 8) In step 1206, process 1200 may include calculating a significance (PROM) value for process 1200. For example, PROM can be calculated using Formula 9: PROM = 0.5 * PTP (Formula 9) In step 1208, process 1200 may include calculating and indexing peaks in the FPD (if any). The indexed peaks may be filtered such that the PROM of the indexed peaks is higher than a significance threshold and the distance between peaks is higher than the minimum peak spacing (PD MIN).

[0109] In step 1210, process 1200 may check whether more than one peak is indexed. If more than one peak is indexed (i.e., step 1210, "Yes"), process 1200 may proceed to step 1212, which may include calculating the peak time. Step 1214 may calculate the blood pump rate (BPR) and / or heart rate (HR) based on the peak time. Step 1214 may include associating the peaks with the blood pump rate or heart rate. For example, in some embodiments, the two most significant indexed peaks may be associated with the blood pump, and the blood pump rate may be calculated based on the time between these two peaks. Other peaks (i.e., less significant) may be associated with the patient's heartbeat, and the patient's heart rate may be calculated based on these less significant peaks. In some embodiments, NDD system 120 may be configured to receive the blood pump rate as input, for example from the blood pump or an associated machine (e.g., a dialysis machine), and the peaks associated with the BPR rate (e.g., "most significant") may be identified, or in some embodiments may be identified by the BPR input. The calculated BPR and / or HR can be used as the output of step 1108 in process 1100 and the check in step 1110.

[0110] In step 1210, if no more than one peak is indexed (i.e., step 1210, "No"), process 1200 may proceed to step 1216. In step 1216, a check may be run to see if the maximum peak search count has been exceeded. If, in step 1216, the maximum peak search count has been exceeded (i.e., step 1216, "Yes"), process 1200 may proceed to step 1218, which may report that no HR and / or BPR were identified, which can be used as the output of step 1208. If, in step 1216, the maximum peak search count has not been exceeded (i.e., step 1216, "No"), process 1200 may proceed to step 1220, in which the salience threshold used in step 1208 is reduced. Process 1200 may then return to step 1210 and repeat with the reduced salience threshold, thereby relaxing the filter for indexing peaks.

[0111] In some implementations of process 1200, instead of identifying and calculating BPR and / or HR based on peak-to-peak value calculation, trough-to-peak value calculation can be used to calculate BPR and / or HR. For example, this can be performed by inverting the FPD (e.g., as part of FPD filtering and / or processing in step 1202), thereby converting troughs to peaks, which can be used in steps 1204–1220. In some implementations, BPR can be calculated based on peak-to-peak value, while HR can be calculated based on trough-to-peak value. For example, process 1200 can be performed using peak-to-peak value to calculate BPR, and then, in parallel, process 1200 can be run using trough-to-peak value (i.e., by inverting the FPD in step 1202) to calculate HR.

[0112] In some embodiments of this disclosure, processes 300 and 900 may be combined. For example, a patient's heart rate can be checked by analyzing pressure changes in the extracorporeal blood circuit and by analyzing optical backscattering signals from optical sensors attached to the extracorporeal blood circuit. Verifying a potential needle dislodgement as an actual needle dislodgement may be based on the absence of heart rate detected in both processes 600 / 700 and 1100 / 1200. Similarly, in some embodiments, processes 400 and 1000 may be combined.

[0113] In some embodiments of this disclosure, arterial pressure (e.g., via arterial pressure signal 110a) can be analyzed to identify a patient's heart rate (e.g., arterial heart rate) on an arterial line. Because arterial lines are closer to the patient's vascular access, the pressure pulses generated by the patient's heart rate are generally more pronounced in arterial lines than in venous lines. Therefore, it is easier to identify the patient's arterial heart rate. Various techniques can be implemented to analyze the arterial pressure signal 110a to identify the arterial heart rate. For example, the procedure 1200 described herein can be used to identify the arterial heart rate by using arterial pressure signal data as input data. Simplified versions of procedure 1200 can also be used, such as procedures that identify peaks or troughs in the arterial pressure signal data and calculate the arterial heart rate based on the peak time.

[0114] In some embodiments of this disclosure, the identified arterial heart rate can be used to enhance the steps of searching for a patient's heart rate and / or verifying a potential needle dislodgement event as a needle dislodgement based on the absence of a heart rate, steps applicable to the various procedures described herein (e.g., 300, 400, 900, and / or 1000). According to one exemplary embodiment, the arterial heart rate can be used to define a set heart rate range used in step 610 and / or step 1110. For example, a set heart rate range can be defined as an arterial heart rate fluctuating above and below a certain value. In some embodiments, step 610 and / or step 1110 may include additional checks (i.e., (4)), such as the presence of an arterial heart rate, an arterial heart rate within a expected range, and / or an arterial heart rate within a defined range of HR (e.g., calculated by step 714 and / or step 1214).

[0115] According to another exemplary embodiment, arterial heart rate can be used to enhance venous pressure signals and / or filter and / or process venous pressure signal data (e.g., improve signal-to-noise ratio). For example, a lock-in amplifier or lock-in signal processing technique can be implemented, in which the identified arterial heart rate is used. This enhancement filtering and / or signal processing technique can be implemented, for example, as part of step 604 of process 600, step 702 of process 700, step 1104 of process 1100, and / or step 1202 of process 1200.

[0116] In some embodiments, the NDD system 120 described herein can be integrated into a dialysis machine. For example, Figure 13A The front view of the dialysis machine 1300 is shown. Figure 13B Show Figure 13A An enlarged view of the dashed box portion of the dialysis machine 1300 and example flow paths of the arterial and venous tubing. In some embodiments, the functionality and / or hardware of the NDD system 120 may be integrated with or be part of the dialysis machine 1300. For example, the dialysis machine 1300 and its associated extracorporeal blood circuit 1301 may include, in particular, an arterial tubing 1302, an arterial pressure monitor 1310, a blood pump 1312, a venous tubing 1306, a venous pressure monitor 1316, and an optical sensor 1318. The dialysis machine 1300 may use a dialyzer (not shown), which can be as follows: Figure 13B The diagram shows the flow path connecting the arteries and veins.

[0117] The optical sensor 118 described herein can be integrated into a dialysis machine in the form of an optical sensor 1318 or 1318', for example, dialysis machine 1300, such as... Figure 13A and Figure 13B As shown. In some embodiments, the optical sensor 1318 may be located below or downstream of the intravenous infusion chamber 1320 and near the venous clamp 1322. In other embodiments, the optical sensor 1318' may be located further downstream, closer to the patient's venous access. Placing the optical sensor 1318' further downstream can improve performance by placing it along a portion of the venous line where blood flow is primarily laminar, such as a portion with less, limited, or almost zero turbulence. Conversely, the portion of the venous line below the intravenous infusion chamber 1320 and near the venous clamp 1322 may experience increased, greater, or significant turbulence, which could negatively impact the performance of the optical sensor 1318 and the optical backscattered signal. For example, increased turbulence may increase noise in the optical backscattered signal. Therefore, the optical sensors 118, 1318' may be placed along portions of the venous line that primarily experience laminar, transitional, or non-turbulent flow. For example, the Reynolds number of blood flow in a venous system can be expressed as follows: greater than about 4000 is considered turbulent flow, about 2300–4000 is transitional flow, and less than about 2300 is laminar flow.

[0118] Figure 14 A shows the front view. Figure 14 B shows an isometric view of optical sensor 1318. Optical sensor 1318 may include a housing 1402 configured to receive a venous conduit 1306. Optical sensor 1318 may also include a sensor gate 1404 configured to close and releasably secure the venous conduit 1306. Figure 14 C shows a cross-sectional view of the optical sensor 1318. (As shown) Figure 14 As shown in Figure C, the optical sensor 1318 may include one or more light sources 1406 configured to direct light energy to the vein conduit 1306. The light source 1406 may be part of a printed circuit board contained within the housing. The optical sensor 1318 may include a window 1408 located between the light source 1406 and the vein conduit 1306, configured to allow light energy and optical backscattering to pass through. In some embodiments, optical backscattering signals from the optical sensor 1318 can be used to indicate whether a door 1404 is properly closed. When a door 1404 is detected as not closed, an alarm or message can be triggered to prompt the operator to close and / or inspect the door of the optical sensor 1318.

[0119] In some embodiments, the optical sensors 118 / 1318 can also be used to sense blood within the venous conduit 106 / 1306. For example, the optical backscatter signal 110a can be monitored and used to identify when blood is present in the venous conduit. In some embodiments, analyzing the optical backscatter signal 110a can enable an estimation of the blood concentration within the venous conduit. For example, the optical backscatter signal can be used to identify when the blood concentration in the venous conduit is greater than about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70% or higher, and / or alternatively less than about 70%, about 60%, about 50%, about 40%, about 30%, about 20%, about 10% or lower.

[0120] In various embodiments of this disclosure, the processes 300, 400, 500, 600, 700, 900, 1000, 1100 and / or 1200 described herein may be programming instructions and / or one or more programming algorithms that may be stored in memory and executed by a processor that may be part of the NDD system 120, computing device 202, dialysis machine 1300 and / or another controller / machine.

[0121] Some of the devices and procedures described herein have been tested in a clinical setting. This study was conducted in a dialysis clinic during routine dialysis treatments for patients undergoing chronic hemodialysis via arteriovenous fistulas or grafts. Dialysis treatments were performed using a Model 2008T hemodialysis machine, with an optical sensor (e.g., optical sensor 118) connected to the venous tubing to collect optical backscatter data from the optical sensor during treatment. An FDA-approved pulse oximeter was connected to the patient's finger on the non-vascular access side as a reference device for continuous heart rate recording. During study visits, patients received routine hemodialysis treatments according to their individual prescriptions, except that the blood flow rate was briefly reduced several times during treatment (approximately 30 seconds or less), after which the patient's prescribed blood flow rate was restored. The changes in blood flow rate were implemented instantaneously by trained clinic personnel according to an approved protocol, rather than gradually. This test of reducing blood flow rate was designed to simulate, for example, step 406 of procedure 400, which can be initiated in response to the identification of a potential needle dislodgement event (e.g., step 404 being "yes").

[0122] Figure 15A This is a graph of some optical backscattering data (infrared and red light) collected during one of the study visits (study visit 1), during which the blood flow rate decreased from the patient's prescribed flow rate to 100 ml / min for about 30 seconds. Figure 15B To study another portion of the optical backscattering data (infrared and red light) collected during visit 1, during which the blood flow rate decreased from the patient's prescribed flow rate to 135 ml / min. Figure 15C To investigate another portion of optical backscattering data (infrared and red light) curves collected during Visit 1, during which the blood flow rate decreased from the patient's prescribed rate to 170 ml / min. The patient's prescribed blood flow rate for Visit 1 was 450 ml / min, and the patient's access was an arteriovenous fistula. During Visit 1, the patient's prescribed blood flow rate decreased a total of 11 times: four times to 100 ml / min, four times to 135 ml / min, and three times to 170 ml / min. The optical backscattering data during these periods of reduced blood flow rate were analyzed (e.g., using flowchart 700) to verify the presence of the patient's heart rate and to calculate the heart rate. Figure 15D A graph showing the heart rate identified and calculated during each reduction in blood flow rate (based on infrared and red backscatter data) and the heart rate simultaneously measured by a pulse oximeter.

[0123] Figure 16A The image shows a partial optical backscattering data (infrared and red light) curve collected during another study visit (study visit 2), during which the blood flow rate decreased from the patient's prescribed flow rate to 100 ml / min for approximately 30 seconds. Figure 16BA graph of another portion of optical backscattering data (infrared and red light) collected during the same study visit (study visit 2), during which blood flow rate decreased from the patient's prescribed flow rate to 135 ml / min. Figure 16C This is a graph of another portion of optical backscattering data (infrared and red light) collected during the same study visit, during which the blood flow rate decreased from the patient's prescribed rate to 170 ml / min. The patient's prescribed blood flow rate for Study Visit 2 was 450 ml / min, but it decreased to 400 ml / min during treatment; the patient's access was an arteriovenous fistula. During Study Visit 2, the blood flow rate decreased a total of 10 times: three times to 100 ml / min, three times to 135 ml / min, and four times to 170 ml / min. The optical backscattering data during these periods of reduced blood flow rate were analyzed (e.g., using flowchart 700) to verify the presence of the patient's heart rate and to calculate the heart rate. Figure 16D A graph showing the patient's heart rate calculated during each reduction in blood flow rate and the heart rate simultaneously measured by a pulse oximeter.

[0124] Figure 17A The image shows a partial optical backscattering data (infrared and red light) curve collected during another study visit (study visit 3), during which the blood flow rate decreased from the patient's prescribed flow rate to 100 ml / min for approximately 30 seconds. Figure 17B A graph of another portion of optical backscattering data (infrared and red light) collected during the same study visit (study visit 3), during which blood flow rate decreased from the patient's prescribed flow rate to 135 ml / min. Figure 17C This is a separate plot of optical backscattering data (infrared and red light) collected during the same study visit (Study Visit 3), during which the blood flow rate was reduced from the patient's prescribed rate to 170 ml / min. The patient's prescribed blood flow rate for Study Visit 3 was 450 ml / min, but it was reduced to even lower rates (e.g., 350 ml / min) during certain treatment periods, and the patient's access was an arteriovenous graft. During this study visit, the blood flow rate was reduced a total of 11 times: four times to 100 ml / min, four times to 135 ml / min, and four times to 170 ml / min. The optical backscattering plot for Study Visit 3 shows a sharp rise and fall in optical backscattering values ​​at the start of the 30-second blood flow rate reduction period, which was not observed in Study Visits 1 or 2. This difference is because reducing the blood flow rate to the target reduction rates (i.e., 100, 135, and 170 ml / min) during Study Visit 3 triggered a transmembrane pressure alarm and stopped the blood pump, but it was restarted to the reduced blood flow rate each time. The optical backscattering data during these periods of reduced blood flow are analyzed (e.g., using process 700) to verify the presence of the patient's heart rate and to calculate the heart rate. Figure 17DA graph showing the patient's heart rate calculated during each reduction in blood flow rate and the heart rate simultaneously measured by a pulse oximeter.

[0125] like Figure 15D , 16D As shown in Figure 17D, the patient's calculated heart rate and the heart rate measured by the pulse oximeter have high tracking accuracy. This demonstrates that optical backscatter data can be used to verify the presence (or absence) of a heartbeat / rate to confirm whether an actual needle dislodgement event has occurred, and also demonstrates the ability to monitor a patient's heart rate by analyzing optical backscatter data.

[0126] Figure 18 This is a graph showing the changes in optical backscattering data (infrared, red, green, and blue light) collected during laboratory testing over time. An extracorporeal circuit was used, with the dialysis machine running at a blood flow rate of 420 mL / min and a pump simulating the patient's heartbeat (70 bpm). During this time, a simulated extracorporeal circuit venous needle dislodgement occurred (approximately at time 2260). Figure 18 As shown by the dashed line, a visible oscillation exists in the signal trough before the simulated intravenous needle dislodges. This oscillation changes after the simulated intravenous needle dislodges (e.g., disappears or significantly weakens). This oscillation in the signal trough can indicate a simulated heartbeat. The systems and methods described herein (e.g., process 700) can be used to identify and calculate heart rate, and / or identify the absence or non-existence of a heartbeat, thereby identifying and / or confirming intravenous needle dislodgement at full prescription blood flow rate (i.e., without first reducing the blood pump speed).

[0127] The terms used in this document should be given their ordinary meaning in the relevant field, or the meaning indicated by the context, unless otherwise specified.

[0128] In this document, references to "an embodiment," "a particular embodiment," "a method of implementation," or "a particular method of implementation" do not necessarily refer to the same embodiment or method of implementation, although this may be the case. Unless the context explicitly requires otherwise, throughout the specification and claims, the words "comprising," "including," etc., should be understood to have an inclusive meaning, rather than an exclusive or exhaustive meaning; that is, meaning "including but not limited to." The use of singular or plural forms of words also includes the plural or singular meaning, respectively, unless explicitly limited to one or more. Furthermore, the words "this document," "above," "below," and similar terms used herein, when applied to this application, refer to the entire application and not any particular part of it. When the word "or" is used in the claims to refer to a list of two or more items, the word covers all of the following interpretations: any item in the list, all items in the list, and any combination of items in the list, unless explicitly limited to one of them. In this specification, the words "first," "second," "top," "bottom," "upward," "downward," etc., should be understood as convenience terms and should not be construed as restrictive terms unless explicitly stated otherwise. Any term not explicitly defined herein has its conventional meaning as commonly understood by one of ordinary skill in the art.

[0129] All references cited herein are incorporated herein by reference in their entirety. Unless otherwise expressly stated or clearly understood from the context, the singular form of an object shall be understood to include the plural form, and vice versa.

[0130] The numerical ranges described herein are not intended to be limiting, but rather to refer individually to any and all values ​​falling within those ranges, unless otherwise stated herein, and each individual value within the range is incorporated into the specification as if described separately herein. When words such as “about” or “approximately” accompany numerical values, they should be understood to indicate a deviation that a person skilled in the art would consider acceptable for the intended purpose. For example, “about” as used herein may indicate a numerical deviation of up to 10%. Furthermore, red light refers to light with wavelengths ranging from approximately 620 nm to approximately 750 nm, for example, approximately 700 nm. Green light refers to light with wavelengths ranging from approximately 495–570 nm, for example, approximately 525 nm. Blue light refers to light with wavelengths ranging from approximately 450 to 495 nm, for example, approximately 475 nm. Infrared light refers to radiation with wavelengths ranging from approximately 780 nm to approximately 1000 micrometers, for example, approximately 780 nm to approximately 2500 nm (near-infrared), approximately 2.5 micrometers to approximately 50 micrometers (mid-infrared), or approximately 50 micrometers to approximately 1000 micrometers (far-infrared). Similarly, when approximate terms such as “about,” “approximately,” or “substantially” are used to refer to physical characteristics, they should be understood to cover a range of deviations that a person skilled in the art would consider sufficient to satisfy the corresponding use, function, purpose, etc. The numerical ranges and / or values ​​provided herein are merely examples and do not constitute a limitation on the scope of the embodiments described. Wherever a numerical range is given herein, that range is also intended to include all values ​​falling within that range, as listed individually herein, unless explicitly stated otherwise. All examples or exemplary language used herein (e.g., “for example,” etc.) are intended only to better illustrate the embodiments and do not constitute a limitation on the scope of the embodiments. No language in this specification should be construed as indicating that any unclaimed element is essential for the implementation of the embodiments.

Claims

1. A method for monitoring a patient's extracorporeal blood circuit and identifying needle dislodgement, the method comprising: Potential needle dislodgement events can be identified based on pressure changes in the extracorporeal blood circuit. The patient's heart rate is searched by analyzing the optical backscattered signals from the optical sensors attached to the extracorporeal blood circuit; and Based on the absence of the heart rate, the potential needle dislodgement event is verified as needle dislodgement.

2. The method according to claim 1, further comprising: When the potential needle dislodgement event is identified, the speed of the blood pump used for the extracorporeal blood circuit is reduced; as well as The patient's heart rate is searched when the blood pump is operating at a reduced speed.

3. The method according to claim 2, wherein, When a potential needle dislodgement event is identified, the blood pump speed is reduced to a blood flow rate of approximately 100–170 mL / min.

4. The method of claim 2 further includes verifying, based on the presence of the patient's heart rate, that the potential needle dislodgement event is not needle dislodgement.

5. The method of claim 4, further comprising, after verifying that the potential needle dislodgement event is not a needle dislodgement, restoring the blood pump to its previous speed.

6. The method according to claim 1, wherein, The potential needle dislodgement event is identified by an algorithm that calculates a needle dislodgement value based on the maximum arterial pressure difference, venous pressure change, arterial pressure, and venous pressure. When the needle dislodgement value is below a threshold, the algorithm identifies the potential needle dislodgement event.

7. The method according to claim 1, wherein, An algorithm is used to search for the patient's heart rate, and this algorithm analyzes the optical backscattered signal in the following way: The optical backscattering signal data is filtered to generate filtered optical backscattering data (FOBD). Peak-to-peak value (PTP) is calculated by subtracting the minimum FOBD from the maximum FOBD. Calculate the significance value based on the PTP value; Identify and index peaks from the FOBD that have a significance higher than the significance threshold PT and an inter-peak distance higher than the minimum inter-peak distance minPD; Calculate peak time when more than one peak is indexed; and Heart rate is calculated based on the peak time.

8. The method according to claim 7 further includes verifying that the potential needle dislodgement event is not a needle dislodgement based on the presence of HR within a set heart rate (HR) range, FOBD variance within a set variance range, and BPR within a set blood pump rate (BPR) range.

9. The method of claim 8, further comprising identifying the patient's arterial heart rate by analyzing changes in arterial pressure in the extracorporeal blood circuit, wherein, The set HR range is determined based on the identified arterial heart rate.

10. The method according to claim 9, wherein, Verification of the potential needle dislodgement event is also based on the presence of arterial heart rate within the set arterial HR range.

11. The method according to claim 1, wherein, The optical sensor is attached to the venous tubing of the extracorporeal blood circuit, and the needle detachment is the detachment of the venous needle.

12. A system for detecting needle dislodgement in a patient's extracorporeal blood circuit, the system comprising: Computing device; processor; Memory, the memory containing instructions, which, when executed by the processor, cause the system to: The optical sensor attached to the extracorporeal blood circuit venous line receives venous pressure signals, arterial pressure signals, and optical backscatter signals; Potential needle dislodgement events can be identified based on changes in the arterial and venous pressure signals. The patient's heart rate is searched by analyzing the optical backscattered signal; and Based on the absence of the heart rate, the potential needle dislodgement event is verified as needle dislodgement.

13. The system according to claim 12, wherein, The memory contains instructions that, when executed by the processor, cause the system to: When the potential needle dislodgement event is identified, the speed of the blood pump used for the extracorporeal blood circuit is reduced; and The patient's heart rate is searched when the blood pump is operating at a reduced speed.

14. The system according to claim 13, wherein, When a potential needle dislodgement event is detected, the blood pump speed is reduced to a blood flow rate of approximately 50–120 mL / min.

15. The system according to claim 13, wherein, The memory contains instructions that, when executed by the processor, cause the system to verify, based on the presence of the heart rate, that the potential needle dislodgement event is not needle dislodgement.

16. The system according to claim 15, wherein, The memory contains instructions that, when executed by the processor, cause the system to restore the blood pump to its previous speed after verifying that the potential needle dislodgement event is not a needle dislodgement.

17. The system according to claim 12, wherein, The memory contains instructions that, when executed by the processor, cause an algorithm to calculate a needle dislodgement value based on the maximum arterial pressure difference, venous pressure change, arterial pressure, and venous pressure. When the needle dislodgement value is below a threshold, the algorithm identifies the potential needle dislodgement event.

18. The system according to claim 12, wherein, The memory contains instructions that, when executed by the processor, cause an algorithm to search for the patient's heart rate by analyzing the optical backscattering signal, the algorithm comprising the following steps: The optical backscattering signal data is filtered to generate filtered optical backscattering data (FOBD). Peak-to-peak value (PTP) is calculated by subtracting the minimum FOBD from the maximum FOBD. Calculate the significance value based on the PTP value; Identify and index peaks from the FOBD that have a significance higher than the significance threshold PT and an inter-peak distance higher than the minimum inter-peak distance minPD; calculate peak time when more than one peak is indexed; and Heart rate is calculated based on the peak time.

19. The system according to claim 18, wherein, The memory contains instructions that, when executed by the processor, cause the system to verify that the potential needle dislodgement event is not a needle dislodgement based on the presence of HR within a set heart rate (HR) range, FOBD variance within a set variance range, and BPR within a set blood pump rate (BPR) range.

20. A dialysis machine, comprising: Blood pump; An extracorporeal blood circuit, configured to connect the blood pump and dialyzer to the patient; Arterial pressure monitor and venous pressure monitor; An optical sensor, the optical sensor being attached to the venous line of the extracorporeal blood circuit; A computing device, comprising a processor and a memory, configured to: The system receives venous pressure signals from the venous pressure monitor, arterial pressure signals from the arterial pressure monitor, and optical backscattering signals from the optical sensor. Potential needle dislodgement events can be identified based on changes in arterial and venous pressure. The patient's heart rate is searched by analyzing the optical backscattered signal; and Based on the absence of the heart rate, the potential needle dislodgement event is verified as needle dislodgement.

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