JP2017151110A - Blood testing system and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system for testing characteristics of a blood sample at point-of-care.SOLUTION: A blood coagulation testing system includes an analyzer console device, and single-use components configured to be removably installed in the console device. The blood coagulation testing system can operate as an automated thromboelastometry system that is particularly useful, for example, at a point-of-care site. The system can be configured with features such as an individual actuation system for each measurement module, and firmware for initial and ongoing calibration and error detection.SELECTED DRAWING: None

Description

  This document relates to a system and method for examining the characteristics of a blood sample, such as an automated thromboelastometry system for point-of-care whole blood clotting analysis.

  Hemostasis is the human response to vascular injury and bleeding. Hemostasis refers to the joint action of platelets and a number of blood clotting proteins (or clotting factors), which results in the formation of a blood clot followed by stopping bleeding.

  Various methods have been introduced to form sufficient clots and to assess the ability of blood to determine clot stability. Common laboratory tests, such as platelet counts or fibrin concentration measurements, provide information on whether the tested components are available in sufficient quantities, but some of these tests are subject to physiological conditions Below, it may not be possible to determine whether the tested components work properly. For example, in a point-of-care situation (eg, at a surgical site during surgery), other laboratory tests may affect the plasma, thereby imposing further preparation steps and additional time beyond the preferred time. There is.

  Another group of tests that assess the ability of blood to form sufficient clots is known as the “viscoelastic method”. In at least some viscoelastic methods, the clot hardness (or other parameter depending on it) can be measured over a period of time, for example, from the formation of the first fibrin fiber to the clot lysis by the fibrinolysis phenomenon. Measured. Clot hardness is a functional parameter that contributes to hemostasis in vivo because clots must resist blood pressure and shear stress at vascular injury or incision locations. In many cases, clot hardness can result from a number of related processes including coagulation activation, thrombin formation, fibrin formation and polymerization, platelet activation, and fibrin-platelet interactions. In order to isolate and test specific functions of platelets, fibrinogen, and other factors in a blood sample, a reagent compound can be mixed with the blood sample, thereby allowing certain constants in the blood sample. Activate or inhibit the ingredient.

  Some of the systems for examining the properties of blood samples (which will be understood to include blood or plasma derivatives such as blood plasma as used herein) Embodiments include a control console configured to examine a blood sample to provide a point-of-care whole blood clotting analysis. For example, the system can be used as an automated thromboelastometry system to provide detailed and rapid results of blood clotting characteristics upon receipt of one or more blood samples mixed with various reagents it can.

  In some embodiments, the thromboelastometry system includes a reusable analyzer console and one or more single-use components configured to accommodate the console. In one example, to operate the thromboelastometry system, the user is prompted by the analyzer console user interface to initiate a number of blood and reagent transfer and mixing operations. The analyzer console then automatically performs the test (without further requiring user interaction with the analyzer console or the blood sample) and uses qualitative graphical displays and quantitative parameters. The result is displayed on a graphical display. Such an analysis provides information on all mechanisms of hemostasis such as clot time, clot morphology, clot stability, and dissolution. In addition, such information can be quickly output from the system's user interface to provide a reliable indication of the patient's blood characteristics at a point of care (eg, while the patient is undergoing surgery in the operating room). Yes, and can provide quick results.

  In one embodiment, a control console for measuring a clotting characteristic of a blood sample comprises: (i) a control unit housing; (ii) a user interface coupled to the control unit housing to reflect the clotting characteristic of the blood sample; And (iii) a plurality of individual thromboelastometry measurement modules housed in the control unit housing. Each measurement module of the plurality of individual thromboelastometry measurement modules includes a shaft configured to receive a probe for testing the blood sample using a probe cup device. Each individual measurement module of the plurality of individual thromboelastometry measurement modules is independent of the rotation of the shaft of all other individual measurement modules of the plurality of individual thromboelastometry measurement modules. A dedicated actuating unit for rotating each shaft of the measuring module.

  Such a control console for measuring the clotting characteristics of a blood sample may optionally include one or more of the following features. In some embodiments, the actuation unit comprises a stepper motor. The stepper motor may optionally include a threaded drive shaft. In various embodiments, the actuation unit also includes a sliding unit. The sliding unit may have a threaded collar threadedly engaged with the threaded drive shaft of the motor, whereby the motor converts the sliding unit into a linear shape. Can be driven. In certain embodiments, the actuation unit also includes a spring wire. In some such embodiments, due to the spring wire extending between the sliding unit and the shaft, a linear transformation of the sliding unit may cause a rotational movement of the shaft.

  In various embodiments of a control console for measuring the clotting characteristics of a blood sample, the actuation unit further comprises a magnet that attracts the spring wire to the sliding unit. The spring wire may be magnetically attracted to the curved surface of the sliding unit. If necessary, the actuation unit may include a sensor configured to detect the position of the sliding unit. In some embodiments, the sensor includes a Hall effect sensor. In various embodiments, the actuation unit may include one or more moving end sensors configured to detect a displacement limit of the sliding unit. The control console may include one or more vibration sensors housed in the control unit housing. In some embodiments, each individual measurement module of the plurality of individual thromboelastometry measurement modules includes one or more vibration sensors.

  In a particular embodiment of a control console for measuring the clotting characteristics of a blood sample, each individual measurement module of the plurality of individual thromboelastometry measurement modules is for evaluating a charge coupled device (CCD) component. Includes evaluation unit. In some embodiments, the evaluation unit (i) receives luminance distribution data from the CCD, (ii) generates CCD calibration data based on the luminance distribution data, and (iii) the CCD calibration. The data may be configured to be compared with CCD brightness distribution data measured in real time. In some embodiments, each individual measurement module of the plurality of individual thromboelastometry measurement modules may further include a heater configured to heat a cup in the probe cup apparatus.

  In another embodiment, a method for evaluating a CCD component of a thromboelastometry analysis system is performed by one or more processors of a thromboelastometry analysis system or one or more processors of a separate AD module. . The method receives brightness distribution data from the CCD, generates CCD calibration data (where the CCD calibration data is generated based on the brightness distribution data from the CCD), and Comparing CCD calibration data with real-time measured CCD brightness distribution data (where the thromboelastometry analysis system is performing thromboelastometry analysis). In some embodiments, the luminance distribution data from the CCD represents individual luminance distribution data from a plurality of individual pixels of the CCD.

  Such a method for evaluating a CCD component of a thromboelastometry analysis system performed by one or more processors of the thromboelastometry analysis system or one or more processors of a separate AD module is One or more of the following features may be included. In some embodiments, the method further comprises determining a position of a falling edge or rising edge of the luminance distribution data from the CCD.

  In another embodiment, the method for controlling the accuracy of the thromboelastometry analysis system is performed by one or more processors of the thromboelastometry analysis system or one or more processors of a separate AD module. . The method receives vibration data indicative of a level of vibration detection of the thromboelastometry analysis system, compares the received vibration data with an acceptable threshold, and received vibration data greater than the acceptable threshold. In response to generating a vibration error indication.

  Such a method for controlling the accuracy of the thromboelastometry analysis system may optionally include one or more of the following features. In some embodiments, the method includes position indication data indicative of the position of the sliding unit detected relative to an operating unit of the thromboelastometry analysis system, the one or more processors of the thromboelastometry analysis system. Including receiving at. In certain embodiments, the method also includes comparing the received position indication data to one or more tolerance thresholds by one or more processors of the thromboelastometry analysis system. In various embodiments, the method comprises the one or more processors of the thromboelastometry analysis system and based on a comparison of one or more tolerance thresholds with the received position indication data. Generating a position error indication in response to the received location indication data being greater than one or more tolerance thresholds.

  In another embodiment, a method for controlling the accuracy of a thromboelastometry analysis system is performed by one or more processors of the thromboelastometry analysis system or by one or more processors of a separate AD module. The The method receives position indication data indicating a position of a sliding unit detected relative to an operating unit of the thromboelastometry analysis system, and compares the received position indication data to one or more tolerance thresholds. And (based on a comparison of the one or more tolerance thresholds with the received position indication data), and in response to the received position indication data greater than the one or more tolerance thresholds, Generating a position error indication.

  Such a method for controlling the accuracy of a thromboelastometry analysis system may include one or more of the following features, as appropriate. In some embodiments, the position indication data includes one or more signals from one or more moving end sensors that indicate whether or not the sliding unit is located at the intended movement limit position. . In certain embodiments, the position indication data is one or more from one or more sensors that indicate the real-time position of the sliding unit as the sliding unit moves back and forth linearly along a linear path. Contains signals.

  Some or all of the embodiments described herein may provide one or more of the following advantages. First, some embodiments of the thromboelastometry system described herein are configured with independent operating units of multiple test and measurement channels for individual modules or channels. . For example, in some embodiments, the thromboelastometry system includes four modules or channels, each of which has an independent actuation unit. Thus, the operation of each inspection and measurement module can be controlled independently of other inspection and measurement modules. In addition, the use of an independent operating unit for each module of the plurality of test and measurement modules can result in a modular design that can benefit the maintenance performance of the system in some situations.

  Second, the actuation unit of some embodiments of the thromboelastometry system comprises a position-controllable rotary actuator (eg, a stepper motor coupled to a programmable stepper motor control system, or a feedback encoder) And another type of suitable rotary actuator) coupled to the control system. The use of position-controllable actuation devices (eg motors) is advantageous in that it allows a programmable actuation pattern. In addition, in some embodiments, a stepper motor allows a rotating thromboelastometry system to operate more accurately than some other types of motors. Further, in some embodiments, the stepper motor increases isolation from certain external error factors such as vibration.

  Third, some embodiments of the thromboelastometry system are configured with firmware for self-evaluation and calibration of the CCD (charge coupled device) components of the thromboelastometry inspection system. Thus, in some cases, measurement inaccuracies are reduced or eliminated. In some such embodiments, the functionality of each individual pixel of the CCD is verified before performing a thromboelastometry test. As a result, the constancy of the thromboelastometry system is enhanced.

  Fourth, some embodiments of the thromboelastometry system are configured with an additional firmware for monitoring and evaluating the functional aspects of the rotational thromboelastometry operation and detection system. The For example, in some embodiments, vibrations that may distort the measurement signal are detected and used to manage the thromboelastometry system. Further, in some embodiments, a sensor is included that detects the movement of the rotary thromboelastometry actuation system and the position of the moving end. These systems that monitor and evaluate the functional aspects of the rotary thromboelastometry actuation and detection system provide a robust measurement system and enhance the quality of the measurement (eg, the accuracy of the thromboelastometry measurement). Increase the accuracy and / or precision).

  The details of one or more embodiments of the invention are set forth in the accompanying drawings and the detailed description below. Other features, objects, and advantages of the invention will be apparent from the detailed description and drawings, and from the claims.

FIG. 1 is a perspective view of an exemplary thromboelastometry system, according to some embodiments. FIG. 2 is an example of a graphic for quantifying clot stiffness during clot formation, as calculated and displayed by the thromboelastometry system of FIG. FIG. 3 is a schematic diagram illustrating an exemplary rotary thromboelastometry detection system portion of the thromboelastometry system of FIG. FIG. 4 illustrates an exemplary actuation and detection module (also referred to herein as an “AD module” or “ADM”) for the individual thromboelastometry measurement channels of the thromboelastometry system of FIG. It is a perspective view. FIG. 5 is an enlarged perspective view of the exemplary AD module of FIG. 6 is an enlarged perspective view of an exemplary AD module actuation unit of FIG. FIG. 7 is an enlarged perspective view of a sliding portion of the operation unit of FIG. FIG. 8 is a flowchart of an exemplary CCD evaluation process that may be used with the thromboelastometry system of FIG. FIG. 9 is a flowchart of another CCD evaluation process that may be used with the thromboelastometry system of FIG. FIG. 10 is a flowchart of a process for controlling the quality of thromboelastometry measurements that may be used with the thromboelastometry system of FIG. FIG. 11 is a flowchart of a process for controlling the quality of another thromboelastometry measurement that may be used with the thromboelastometry system of FIG.

  Like reference symbols in the various drawings indicate like elements.

  Referring to FIG. 1, some embodiments of an exemplary blood test system 100 include a graphical user interface 120 coupled to the blood analyzer console 110 along with a blood analyzer console 110. In the illustrated embodiment, blood test system 100 is a thromboelastometry system configured to measure a number of blood clotting characteristics of a blood sample. An example of such a thromboelastometry system 100 is the ROTEM® Delta thromboelastometry system available from Tem International GmbH, headquartered in Munich, Germany. Thromboelastometry and thromboelastography provide a continuous view of clot stiffness during clot formation and subsequent fibrinolysis events (eg, related to coagulation factors and inhibitors, platelets, and fibrin). Based on measuring the elasticity of blood by recording.

  The exemplary thromboelastometry system 100 performs in vitro blood diagnostics, especially at point-of-care sites (eg, at the surgical site when the patient is in surgery and preparing for surgery). It is advantageous. In addition, the thromboelastometry system 100 can be used as a laboratory-installed whole blood coagulation analysis system. The thromboelastometry system 100 provides a quantitative and qualitative indication of the coagulation state of a blood sample.

  In some embodiments, the graphical display displayed on the graphical user interface 120 may include various blood diagnostic results (eg, one or more plots, numerical data or measurement results, which may be referred to as TEMograms). Or a combination of these), the various blood diagnostic results may explain the interaction between components such as coagulation factors and inhibitors, fibrinogen, platelets and the fibrinolytic system. For example, referring also to FIG. 2, in some embodiments, the graphical user interface 120 provides the clot hardness as a graphical display 200 continuously recorded as a diagram during clot formation. FIG. 2 is an example of a graphic 200, for example, while performing an analysis, the graphic is calculated and displayed by the thromboelastometry system 100, thereby quantifying clot hardness during clot formation. Is done. In some embodiments, a plurality of such graphical displays 200 related to clot hardness are simultaneously displayed on the graphical user interface 120 during clot formation.

  Still referring to FIG. 1, in some embodiments, the analyzer console 110 houses hardware devices and subsystems that control the operation of the thromboelastometry system 100. For example, the analyzer console 110 contains one or more processors and a memory device that can store the operating system and other executable instructions. In some embodiments, the executable instructions are executed by the one or more processors, such as analysis of blood test result data indicative of blood clotting characteristics, and output via a user interface 120, etc. The system 100 is configured to execute an operation.

  In some embodiments, the analyzer console 110 also houses various internal subsystems, includes various electronic connection receptacles (not shown), and includes a cartridge port (not shown). The various electronic connection receiving units include, but are not limited to, one or a plurality of USB ports, Ethernet (registered trademark) ports (for example, RJ45), VGA connectors, sub D9 connectors (RS232), and the like. Such network and device connectors may be included. Such connection receptacles may be located on the back side of the analyzer console 110 or other convenient location on the analyzer console 110. For example, in some embodiments, one or more USB ports may be located on the front side or near the front side of the analyzer console 110. A USB port so arranged may provide user convenience for storage of data on a memory stick, for example. In some embodiments, the thromboelastometry system 100 operates using wireless communication schemes such as, but not limited to, Wi-Fi, Bluetooth, NFC, RF, IR, etc. Configured as follows.

  Still referring to FIG. 1, in some embodiments, the graphical user interface 120 is in graphical and / or textual form to assist the user during preparation of a blood sample for examination by the thromboelastometry system 100. It is also used to convey user commands. Optionally, the graphical user interface 120 is coupled to the analyzer console 110 and is a touch screen display. Thereby, the user can input information and can select a menu item, for example. In some embodiments, the graphical user interface 120 is fixedly attached to the analyzer console 110. In certain embodiments, the graphical user interface 120 is rotatable and / or otherwise adjustable or removable with respect to the analyzer console 110.

  Blood test system 100 may include a keyboard 130 and / or other types of user input devices such as a mouse, touchpad, trackball, and the like. In some embodiments, the thromboelastometry system 100 also includes an external barcode reader. Such external barcode readers are not limited to these, but simple one-dimensional or two-dimensional barcode entry of data such as blood sample data, user identifiers, patient identifiers, normal values, etc. Can be made smooth. Alternatively or additionally, the thromboelastometry system 100 may include a reader configured to read near field communication tags, RFID tags, and the like. In some embodiments, a computer data network (eg, intranet, internet, LAN, etc.) may be used so that a remote device can receive and / or enter information from the thromboelastometry system 100. Good.

  The illustrated thromboelastometry system 100 also includes an electronic system pipette 160. Using the pipette 160 of the system, a user can easily dispense a measured volume of liquid (such as blood or reagent) during the process of preparing a pre-test blood sample. In some embodiments, the system pipette 160 is a semi-automated software managed device. For example, in some embodiments, the pipette 160 of the system automatically draws a target amount of liquid from one container, after which the user can dispense the target amount of liquid into another container. .

  In some embodiments, operation of blood test system 100 includes using one or more reagents 170 that are mixed with a blood sample prior to performing thromboelastometry. For example, reagent 170 may comprise compounds such as, but not limited to, CaCl2, ellagic acid or phospholipid, tissue factor, heparinase, polybrene, cytochalasin D, tranexamic acid, and the like, and combinations thereof. it can. In some embodiments, the thromboelastometry system 100 provides a user command (eg, via the graphical user interface 120) to mix a particular reagent 170 with the blood sample using the system pipette 160. Will do.

  The thromboelastometry analyzer console 110 also includes one or more individual thromboelastometry measurement stations 180 (sometimes referred to herein as “channels” or “measurement modules”). The illustrated embodiment of the thromboelastometry system 100 includes four individual thromboelastometry measurement stations 180 (ie, four channels or four measurement modules).

  As described further below, each thromboelastometry measurement station 180 includes a cup holder in which a user places a sample cup containing blood and reagents in preparation for a thromboelastometry test. In some embodiments, the cup holder is mounted with a heating system so that the sample is warmed to and maintained at near body temperature (eg, 37 ± 1.0 ° C.). Can do.

  As described further below, in some embodiments, each thromboelastometry measurement station 180 includes a pin or probe that may be removably disposed within a cup that contains the sample to be examined. There is a gap between the probe and the cup. In some embodiments, the shaft and probe are swung back and forth by less than about 10 ° (in both directions of rotation), preferably from about 3 ° to 6 ° (in both directions of rotation), or other It is rotated as a method. Such swinging of the shaft and probe may be equal in amplitude in both rotational directions. The sway is measured and the sway is reduced as the blood / reagent mixture begins to harden due to thrombolysis. Measuring such oscillation over time by the thromboelastometry measurement station 180 produces a thromboelastometry result.

  Referring also to FIG. 3, an exemplary rotary thromboelastometry operation and detection system 300 that may be present in each thromboelastometry measurement station 180 (measurement module) is schematically illustrated. In some embodiments, the shaft 310 of the actuation and detection system 300 can engage a single use probe 138 to perform rotational thromboelastometry on a blood sample contained within the single use cup 136. . In FIG. 3, the probe 138 and the cup 136 are generally shown in a longitudinal section so that the exemplary rotary thromboelastometry actuation and detection system 300 can be easily seen and understood. In some embodiments, the probe 138 has an outer diameter of about 6 mm and the cup 136 has an inner diameter of about 8 mm. However, the dimensions of the cup 136 and the probe 138 can be increased or decreased as appropriate.

  In this particular embodiment, a schematically illustrated rotary thromboelastometry actuation and detection system 300 includes a base plate 302, a shaft 310, a bearing 312, a mirror 314, a reaction force spring line 320, a light source 330, and a detection. 340 including a charge coupled device (CCD), for example. The single use cup 136 can be lifted (eg, by the user) as indicated by arrow 318 so that the tip position of the shaft 310 enters the hole 139 of the probe 138 and is detachable from the probe 138. Will be coupled to. The bearing 312 is engaged with the base plate 302 and the shaft 310 to cause a rotational movement of the shaft 310 relative to the base plate 302. The spring wire 320 is coupled to the shaft 310, and the induced movement of the spring wire 320 (as driven by a motor, further described below), as indicated by arrow 316 (both rotational directions). The shaft 310 can be guided to swing back and forth by less than 10 °, preferably by about 3 ° to about 6 ° (in both directions of rotation). The mirror 314 is coupled to the shaft 310. The light source 330 is configured to emit light toward the mirror 314, and the light can be reflected from the mirror 314 toward the detector 340 (in a direction that depends on the rotational direction of the shaft 310). Accordingly, the operation of probe 138 is detected by an optical detection system (eg, detector 340). It should be understood that other configurations of the rotary thromboelastometry actuation and detection system 300 are also contemplated within the present disclosure.

  As the blood in cup 136 begins to clot, the amplitude of motion of shaft 310 begins to decrease (as detected by the reflection of light from mirror 314 to detector 340). During clotting, the fibrin skeleton of the blood (with platelets) creates a mechanical elastic bond between the surface of the cup 136 and the surface of the probe 138. Thus, an ongoing coagulation process induced by adding one or more of the activators (eg, reagents) can be observed and quantified.

  The operational data detected by detector 340 is analyzed by an algorithm running on analyzer console 110 to process and determine the results of thromboelastometry. This system includes, but is not limited to, clot time, clot formation time, alpha angle, amplitude, clot maximum hardness, dissolution start time, dissolution time, dissolution index (%), and maximum dissolution Facilitates various thromboelastometry parameters such as (%). Thus, for a suitable medical intervention, various deficiencies in the patient's hemostatic state can be revealed and various deficiencies in the patient's hemostatic state can be explained. At the end of the inspection process, the cup 136 can be lowered to uncouple the shaft 310 from the probe 138.

  Still referring to FIG. 1, the analyzer console 110 is one or more rotary thromboelastometry operations corresponding to one or more individual thromboelastometry measurement stations 180 (eg, one to one). And a detection module (AD module) 400 can be accommodated. Such a rotary thromboelastometry AD module 400 can be operated like, for example, the exemplary rotary thromboelastometry actuation and detection system 300 described above with reference to FIG.

  Referring to FIG. 4, a separate rotary thromboelastometry AD module 400 can generally include a housing 410 and a shaft 420. The shaft 420 can be removably coupled to a single use probe (eg, probe 138 of FIG. 3) to perform thromboelastometry and / or thromboelastography, as previously described. . That is, as explained above, the shaft 420 is swung back and forth rotatably by less than 10 ° (in both directions of rotation), preferably from about 3 ° to about 6 ° (in both directions of rotation). Can.

  Referring to FIG. 5, an enlarged view of the rotary thromboelastometry AD module 400 makes the main parts of the AD module 400 easier to see. For example, the rotary thromboelastometry AD module 400 includes a housing 410 (including three housing portions 410a, 410b, and 410c), a shaft 420, an actuation unit 430, a spring wire 440, an LED 450, a CCD 460, and a print. A substrate (PCB) assembly 470 is included.

  In some embodiments, the housing 410 includes a cover 410a, a substrate 410b, and a back cover 410c. The housing 410 contains other parts of the AD module 400 except for a portion of the shaft 420 that projects beyond the substrate 410b so that the shaft 420 can engage a single use probe. Thus, in some embodiments, AD module 400 is a discrete module that can be removed and replaced as a unit.

  The rotary thromboelastometry AD module 400 also includes a shaft 420. In the illustrated embodiment, the shaft 420 includes a bearing 422 and a mirror 424. When the AD module 400 is assembled, the bearing 422 is fixedly coupled to the substrate 410b. For this reason, the shaft 420 can freely rotate with respect to the substrate 410b. The mirror 424 is attached to the shaft 420 and is configured to reflect the light from the LED 450 toward the CCD 460. As the shaft 420 swings during the rotary thromboelastometry examination, the orientation of the mirror 424 also swings accordingly (by attaching the mirror 424 to the shaft 420). Thus, during the rotating thromboelastometry examination, light from the LED 450 is reflected from the mirror 424 (and toward the CCD 460) at an angle that changes as the shaft 420 swings.

  The rotary thromboelastometry AD module 400 also includes an actuation unit 430. Actuating unit 430 (described in more detail below with reference to FIG. 6) provides a propulsive force that causes shaft 420 to rotate and oscillate.

  In the illustrated embodiment, the spring wire 440 couples between the actuation unit 430 and the shaft 420. In other words, the operating unit 430 drives the spring wire 440, and the spring wire 440 transmits the propulsive force from the operating unit 430 to the shaft 420.

  The rotary thromboelastometry AD module 400 also includes an LED 450. In some embodiments, the LED 450 is fixedly mounted to the PCB assembly 470, and the PCB assembly is fixedly mounted to the housing 410. The LED 450 emits light that is steerably directed in the direction of the mirror 424. In some embodiments, one or more lenses are used with the LED 450.

  Light from the LED 450 is reflected from the mirror 424 toward the CCD 460. The CCD 460 includes a plurality of pixels arranged along the surface of the CCD 460 (for example, arranged approximately linearly). Thus, as the shaft 420 rotates, the light reflected from the mirror 424 scans across the plane of the CCD 460. By detecting the position of a particular pixel of the CCD 460 that receives the LED light, other characteristics related to the angular position and the rotation angle of the shaft 420 can be measured. In some embodiments, other types of photodetectors (other than CCD type detectors) are used in place of or in addition to CCD 460.

  The rotary thromboelastometry AD module 400 also includes a PCB assembly 470. The PCB assembly 470 includes electronic devices and circuit elements that are used for operation of the rotating thromboelastometry AD module 400. In certain embodiments, a PCB assembly 470 (which includes executable code stored therein) receives luminance distribution data from the CCD, generates CCD calibration data based on the luminance distribution data, An evaluation unit configured to compare the CCD calibration data with real-time measured CCD calibration data; In some embodiments, the PCB assembly 470 includes a microprocessor, motor driver, fuse, integrated circuit, and the like. The PCB assembly 470 includes one or more types of sensors such as, but not limited to, vibration sensors, acceleration sensors, Hall effect sensors, moving end detectors, proximity sensors, optical sensors, microswitches, and the like. May be included.

  Referring to FIG. 6, an exemplary actuation unit 430 of a rotary thromboelastometry AD module 400 is shown in an enlarged view to facilitate viewing of the actuation unit components. In the illustrated embodiment, the actuation unit 430 includes a motor 432, a sliding unit 434, and a sliding guide member 438. The motor 432 is installed on the sliding guide member 438. The sliding unit 434 is slidably engaged with the sliding guide member 438. The motor 432 is engaged with the sliding unit 434 so that the motor 432 can provide propulsive force to the sliding unit 434, as will be described further below.

  The exemplary actuation unit 430 is designed to provide a number of operational benefits. For example, as will become more apparent from the following description, the actuation unit 430 is small, lightweight, resistant to external vibrations, mechanically precise, electronically attached, and highly controllable, It can be positioned repeatedly and has durability.

  In some embodiments, the motor 432 is a stepper motor. Thus, in some such embodiments, the motor 432 can be programmed and controlled to rotate and operate in a predetermined manner. That is, in some embodiments, the motor 432 is operated in response to selected parameters including, but not limited to, parameters such as rotational speed, rotational speed, acceleration, deceleration, direction, and the like. Can be programmed as follows. Such factors may be programmed into the memory of the rotary thromboelastometry AD module 400 or analyzer console 110. Accordingly, various operating curves for the motor 432 can be easily selected and / or adjusted as desired. In some embodiments, all rotary thromboelastometry AD modules 400 are programmed to operate using the same operating curve. In other embodiments, one or more rotary thromboelastometry AD modules 400 operate using different operating curves compared to one or more other rotary thromboelastometry AD modules 400. To be programmed.

  The motor 432 includes a drive shaft 433. In some embodiments, the drive shaft 433 is a lead screw. The male screw of the feed screw may be screwed into a position where the inside of the sliding unit 434 is threaded. In some such embodiments, the drive shaft 433 is a precision threaded lead screw that facilitates accurate and smooth control of the sliding unit 434. When the drive shaft 433 and the sliding unit 434 are screwed together, the rotation of the motor 432 becomes a linear movement of the sliding unit 434. That is, as the drive shaft 433 of the motor 432 rotates, the sliding unit 434 moves slidably in the sliding guide member 438. When the rotation direction of the motor 432 is reversed (for example, clockwise with respect to the counterclockwise direction), the linear direction of the sliding unit 434 with respect to the sliding guide member 438 is reversed accordingly.

  Referring also to FIG. 7, an example of the sliding unit 434 is shown in an enlarged perspective view to facilitate viewing of the sliding unit components. The sliding unit 434 includes a bending member 435, a threaded collar 436, a spring wire holding magnet 437, a sliding unit holding magnet 439, a spring wire mounting member 452, and a sliding body 454. The threaded collar 436 and the curved member 435 are attached to the sliding body 454. The spring wire holding magnet 437 is attached to the bending member 435. The spring wire attaching member 452 is engaged with the bending member 435 and the sliding body 454. The sliding unit holding magnet 439 is attached to the sliding guide member 438 and is coupled to the sliding body 454 by magnetic force.

  The bending member 435 has a lateral surface formed in a curved shape with which the spring wire 440 (see FIG. 5) contacts. When the bending member 435 linearly moves back and forth within the sliding guide member 438, the position of the contact region between the spring wire 440 and the lateral surface formed on the curved surface of the bending member 435 is adjusted. This configuration changes the linear motion of the bending member 435 into a smooth rotational motion of the spring wire 440 (with the shaft 420 functioning as the rotational axis).

  The spring wire holding magnet 437 attracts the spring wire 440, so that the spring wire 440 continues to come into contact with the curved surface of the bending member 435 while the sliding unit 434 moves back and forth. . Further, in some embodiments, the spring wire retaining magnet 437 is used with a Hall effect sensor mounted on the PCB assembly 470 (see FIG. 5) so that the position of the sliding unit 434 can be electronically monitored. .

  The threaded collar 436 has a female thread that is complementary to the male thread of the drive shaft 433 of the motor 432. Accordingly, the threaded collar 436 is constrained to rotate due to engagement with the sliding body 454, and when the drive shaft 433 rotates, it moves linearly along the longitudinal direction of the drive shaft 433 of the motor 432. To do. When the threaded collar 436 moves straight, the sliding body 454 and the bending member 435 also move linearly (by attaching the threaded collar 436 to the sliding body 454). Since the sliding unit holding magnet 439 is attached to the sliding guide member 438 and is magnetically coupled to the sliding body 454, the sliding guide member 438 is moved when the sliding body 454 moves back and forth with respect to the sliding guide member 438. In contrast, it helps to accurately maintain the sliding body 454 in close operating relationship.

  Since the spring wire attachment member 452 is coupled to the sliding body 454, it serves to mechanically engage the spring wire 440 (see FIG. 5) with the sliding unit 434. For this reason, the spring wire attachment member 452 facilitates mechanical connection between the spring wire 440 and the sliding unit 434 (in addition to the above-described magnetic coupling between the spring wire 440 and the spring wire holding magnet 437). To. Further, in some embodiments, the spring wire attachment member 452 includes external features that are used for movement of the sliding unit 434 or detection of the moving end. For example, in some embodiments, the spring wire attachment member 452 includes one or more protrusions detectable by a sensor attached to the PCB assembly 470. An optical sensor, a proximal sensor, a mechanical sensor, etc. may be used to detect the position of the spring wire attachment member 452 in a defined manner.

  Referring to FIG. 8, in some embodiments, one or more processors of the thromboelastometry system 100 (see FIG. 1) are configured to perform a CCD evaluation process 800. In certain embodiments, such CCD evaluation process 800 is performed in one or more processors of an individual AD module (eg, in one or more processors of PCB assembly 470 of exemplary AD module 400; 4 and 5) can be performed. In some such embodiments, each individual measurement module of the thromboelastometry system 100 may include one or more processors configured to perform the CCD evaluation process 800. Using the CCD evaluation process 800, in some cases, inaccuracies in thromboelastometry measurements can be reduced or eliminated. As a result, consistency in performance (eg, accuracy and precision) of the thromboelastometry system 100 may be enhanced.

  In step 810, one or more processors of the thromboelastometry system or AD module receive the CCD brightness distribution data. In some embodiments, multiple pixels of the AD module CCD are activated using a light source (eg, an exemplary AD module LED 450; see FIG. 5). Data obtained by a plurality of pixels is received by the one or more processors.

  In step 820, one or more processors of the thromboelastometry system or AD module generate CCD calibration data using the CCD brightness distribution data received in step 810. In some embodiments, this is done by evaluating the position of the falling or rising edge of the luminance distribution data from the CCD. The falling edge or rising edge of the luminance distribution data may be referred to as “side surface” in the present specification.

  In step 830, one or more processors of the thromboelastometry system or AD module compare the calibration data generated in step 820 with real-time measured CCD brightness data. In some embodiments, the real-time CCD evaluation process of step 830 is repeatedly performed (circulated) while the thromboelastometry system is operating. For example, in some embodiments, the cycle time of the running real-time CCD evaluation process 830 is less than about 200 millimeters per second. In some embodiments, a running real-time CCD evaluation process 830 is used to adapt the sample from the calibration to the currently measured position of the falling edge or rising edge (or luminance distribution side) of the luminance distribution data. It is an optimization process.

  Referring to FIG. 9, in some embodiments, the thromboelastometry system 100 (see FIG. 1) or one or more processors of the AD module are configured to perform a two-stage CCD evaluation process 900. . The two-stage CCD evaluation process 900 includes a startup CCD evaluation process 910 and a running real-time CCD evaluation process 920. With the two-stage CCD evaluation process 900, inaccuracies in thromboelastometry measurements can in some cases be reduced or eliminated. As a result, the consistency of the performance (eg, accuracy and precision) of the individual AD modules and the thromboelastometry system 100 may be increased overall.

  In some embodiments, the first stage of the two-stage CCD evaluation process 900 is to generate calibration data in the form of samples (data points) to be matched. This is performed by starting with step 911 and evaluating the highest luminance distribution profile upon activation of the thromboelastometry system 100. At each inspection position of the CCD, each light signal distribution is analyzed to determine whether the pixel is OK (not) or not (ok). As an example, some pixels of the CCD may be considered problematic due to lack of performance due to CCD contamination.

  In some embodiments, the state of the CCD pixel is analyzed by performing a binomial moving average over the entire light dispersion curve and comparing the resulting value with measured data. For each pixel, if the difference between the binomial moving average over the entire dispersion curve and the measured value of the pixel is greater than a threshold, in some embodiments the pixel is considered problematic. Conversely, if the difference between the binomial moving average over the entire dispersion curve and the measured value of the pixel is less than a threshold, the pixel is considered to be fine.

  In step 912, data associated with each pixel is stored in a buffer. That is, since all CCDs are analyzed in step 911, a map of disturbed pixels may be calculated by storing the positions of all disturbed pixels in a buffer. The data is also used as input data to a running real-time CCD evaluation process 920.

  In step 913, the position of the CCD with the least concentration of problematic pixels is determined as the optimal position for calculating the CCD evaluation algorithm. Thereafter, the shaft mirror (see FIG. 4) is rotatably arranged so that the LED light reflected from the mirror is directed to the optimal position of the CCD.

In step 914, the brightness distribution curve measured at the optimal location is then filtered to remove outlier errors of the brightness distribution curve measured at the optimal location. In some embodiments, a filtering process is applied to linearly approximate the outlier portion of the luminance distribution curve. This stage is configured to solve the problem caused by some dirt that darkens the CCD part, for example. Most of these stains are generally conspicuous as wide, conspicuous areas (outlier errors) with significantly less illumination than normal. In some embodiments, this step uses an algorithm that includes two stages. In the first stage, the curve is sampled using a fixed step width to search for an abnormal outlier to be corrected. In the second stage, the start point of the outlier is acquired and the end point of the outlier is searched. This step is performed by approximating the slope of the luminance distribution curve. The algorithm estimates that the closest problematic point is within the region of this slope extension. Observing the typical CCD brightness distribution curve shape and the error resulting from contamination on the CCD, the outlier should only increase the value of the point. This algorithm has a low memory footprint and some more complex filter kernels and FFs
It moves faster than the T approach.

  In step 915, an accurate falling edge or a part of the rising edge (side surface) of the luminance distribution data is extracted from the filtered data in step 914. The algorithm is designed to robustly detect the exact end of a filtered outlier with a predetermined luminance distribution.

  In some embodiments, starting from a minimum value, the search algorithm is designed to find the latest possible event that suitably matches the searched value. Since the brightness distribution data curve is rising, the latest possible event is at the desired position with high probability. This custom algorithm is extremely fast and reliable for a low memory footprint.

  In step 916, the extracted luminance distribution profile is then smoothed and sampled. In some embodiments, this is done by applying very little noise to the side and bringing the result closer to the curve fit model. A cubic spline with sufficient interpolation points is better than a typical polynomial or linear interpolation, which can approximate a non-linear curve sufficiently well, so that it performs well only when the curve is of a normal shape.

  In steps 917 and 918, a sample with a fixed step width is extracted as the final calibration step and stored in the buffer. This substantially reduces the memory footprint and facilitates real-time evaluation since fewer comparison operations are performed.

  When the buffer containing the location of the problematic pixel is nearly full (step 912) and the buffer containing the sample for real-time ray position assessment is almost full (step 918), the activation CCD evaluation process 910 is complete.

  While the thromboelastometry system 100 is operating, the running real-time CCD evaluation process 920 is performed repeatedly (cyclically). For example, in some embodiments, the running real-time CCD evaluation process 920 has a cycle time of about 50 milliseconds per second. The running real-time CCD evaluation process 920 is an optimization process for fitting a calibration-derived sample to the currently measured luminance distribution aspect.

  In step 921, the sample from step 918 is compared and matched to the target position by an interval based algorithm. The algorithm evaluates the sample in the middle of the interval. The section includes feasible target positions on the left side. In some embodiments, the first interval (space) is the entire CCD pixel range. The algorithm then determines whether the desired position is to the right or left of the desired position (it is feasible because the luminance distribution is monotone) ). That is, if any pixel is larger than the central right side, a new right side boundary is determined. The currently evaluated position then serves as the new right or left boundary of the new section that equally divides the searched CCD pixel range. This scheme is repeated until the interval (space) is of a length that means that the goal is achieved. This first quick fitting algorithm further reduces the total time required to fit the sample to the measured curve. The algorithm requires only about 10 iterations to accurately find the target location within a range of about 10 pixels. The algorithm is superior in speed compared to the more common minimum average method used after this quick fit.

  In step 922, accurate weighted convergence is performed to fit the samples as best as possible. This is done by calculating the average of the absolute distances between all samples and the part corresponding to the absolute distance in the luminance distribution curve. Because information about the state of the pixel (no problem or problematic) is in the memory for each pixel, the samples to compare with the problematic pixel can be ignored. This makes it more robust compared to typical approaches that do not ignore known bad pixels.

  In step 923, the position of the sample (CCD pixel position, buffer position) on the X axis of the ray position is determined and sent to the software.

  Referring to FIG. 10, the AD module error detection process 1000 is a cyclic process that may be performed by the processor of the thromboelastometry measurement system. The AD module error detection process 1000 may be performed to evaluate parameters that may indicate the cause of the thromboelastometry operation and detection system errors.

  In step 1010, the AD module error detection process 1000 begins. The AD module error detection process 1000 may be performed concurrently with the thromboelastometry measurement process.

  In step 1020, the processor of the thromboelastometry measurement system receives data related to the detected amount of vibration that may affect the accuracy and precision of the thromboelastometry measurement data from the AD module. In some embodiments, the vibration is measured by a ball-based sensor (eg, disposed on a PCB in the AD module housing) that is part of the AD module. In some embodiments, other types of sensors such as one or more accelerometers, piezoelectric sensors, displacement sensors, velocity sensors, etc. are used for vibration detection.

  In step 1030, the processor compares the received vibration data to one or more thresholds. If the received vibration data is greater than a threshold, the processor generates an error indication associated with vibration at step 1040.

At step 1050, the processor of the thromboelastometry measurement system relates to the detected position of the moving part of the AD module that may affect the accuracy or precision of the thromboelastometry measurement data from the AD module. Receive data to be processed. For example, the position indication data may include, but is not limited to, moving end data, rotational position data, linear transformation position data, and combinations thereof. In some embodiments, a mobile end switch (eg, located on a PCB in the AD module housing) that is part of the AD module is used to detect the absolute position of the AD module actuation unit. . In some embodiments, the mobile end switch is in the form of an optical sensor or proximity sensor, a limit switch, or the like. In some embodiments, a Hall Effect sensor that is part of the AD module (eg, disposed on a PCB in the AD module housing) is used to generate position indication data. Other types of sensors that provide position indication data may be used.

  In step 1060, the processor compares the received data associated with the detected position of the moving part of the AD module with one or more thresholds. If the received data is greater than the threshold, the processor generates a position error indication at step 1070. The process 1000 loops back to step 1020 and the process 1000 is repeated.

  Referring to FIG. 11, a process flow chart describes the AD module measurement loop 1100 and the thromboelastometry measurement and evaluation loop 1150 in considerable detail. The processes 1100 and 1150 include steps for managing the operation of the thromboelastometry system 100 (see FIG. 1) to enhance error detection and accuracy of the thromboelastometry system.

  During thromboelastometry measurements, important items are managed and evaluated in real time using processes 1100 and 1150. For example, vibrations that can distort the measurement signal are managed and evaluated. Also, the quality of movement of the rotary thromboelastometry operation and detection system is managed and evaluated using Hall effect sensors. In addition, the accuracy of movement of the rotary thromboelastometry operation and detection system is managed and evaluated using one or more moving end sensors. Furthermore, the quality of the measurement signal is evaluated. By combining the vibration, motion quality, and motion accuracy with the ray position, the processor of the thromboelastometry system can determine the current quality of the measurement signal, analyze the cause of the distortion, High measurement can be adopted.

  In some embodiments, the AD module measurement loop 1100 is executed at about 50 millimeters per second. In certain embodiments, the AD module measurement loop 1100 is part of the normal measurement routine in the AD module.

  Steps 1104 and 1106 relate to the position of the LED light of the AD module. For example, in some embodiments, the ray position is detected and evaluated.

  Steps 1108 to 1114 relate to the evaluation of the vibration. In some embodiments, the vibration is measured by a ball-based sensor (eg, located on a PCB in the AD module housing) that is part of the AD module. In some embodiments, other types of sensors such as one or more accelerometers, piezoelectric sensors, displacement sensors, velocity sensors, etc. are used for vibration detection. The data obtained that needs to be evaluated are vibration events over time. A typical evaluation algorithm may be limited to allow only a predetermined amount of vibration events during a predetermined time. If the limit is exceeded, an error message is sent to the processor running the thromboelastometry measurement software.

  Steps 116-1120 evaluate a rotary thromboelastometry actuation and detection system that is monitored using a Hall Effect sensor (eg, located on a PCB in the AD module housing) that is part of the AD module. including. The measured data provides the actual motion characteristics of the system. In some embodiments, an evaluation algorithm may be implemented to compare the measured motion with a theoretical motion to be performed by the rotating thromboelastometry actuation and detection system. For example, a suitable algorithm when the sum of absolute difference or square difference between theory and reality is appropriately optimized. If a threshold amount of difference is detected, an error message is sent to the processor executing the thromboelastometry measurement software (step 1122).

  Steps 1124 and 1126 include an evaluation of the absolute movement position of the rotary thromboelastometry actuation and detection system. An end switch (eg, located on a PCB in the AD module housing) that is part of the AD module is used to detect the absolute position of the actuation unit with sub-step (stepper motor) accuracy. . In some embodiments, the end switch is in the form of an optical sensor, or proximity sensor, limit switch, and the like. Statistical data collecting the deviation from the optimal position is used to determine whether it is operating as expected. If the actual position is significantly different from the target position for the time threshold amount, an error message is sent to the processor running the thromboelastometry measurement software (step 1122).

  In step 1122, the quality of operation of the rotary thromboelastometry operation and detection system can be fully evaluated by the data collected on the operation quality from step 1116 to 1126. In some embodiments, for example, the evaluation can be realized at a low cost and in a small space compared to using an external encoder that monitors the stepper motor.

  Now turn to the description of the thromboelastometry measurement and evaluation loop 1150. Steps 1154 to 1158 relate to a thromboelastometry measurement process as performed by a processor executing the thromboelastometry measurement software.

  Steps 1160 and 1162 describe the evaluation of errors sent from the process 1100 by the AD module. After the position has been evaluated, further errors sent by the AD module may be used by a processor executing the thromboelastometry measurement software to interpret currently known errors. The type and frequency of the error is evaluated by the software and an error message is shown to the user if it is frequent enough to be communicated to the user or important enough to be communicated to the user. In some embodiments, the AD is executed by a processor that executes thromboelastometry measurement software that conveys further information that causes an error and facilitates further improvements in hardware, electronics, and firmware. Module errors may be associated with measurement errors.

  A number of embodiments of the invention have been described. Nevertheless, it will be understood that various modifications may be made without departing from the scope of the invention. Accordingly, other embodiments are within the scope of the following claims.

Claims (17)

A control console for measuring a coagulation characteristic of a blood sample, the control console comprising:
A control unit housing;
A user interface coupled to the control unit housing for displaying the coagulation characteristics of the blood sample;
A plurality of individual thromboelastometry measurement modules housed in a housing of the control unit, each of the plurality of individual thromboelastometry measurement modules being a probe for testing the blood sample A plurality of individual thromboelastometry measurement modules including a shaft configured to receive using a probe cup device,
Each individual measurement module of the plurality of individual thromboelastometry measurement modules is
A dedicated actuating unit that rotates each shaft of the individual measurement modules independently of rotation of the shafts of all other individual measurement modules of the plurality of individual thromboelastometry measurement modules;
Control console. The actuating unit comprises a stepper motor, the stepper motor comprising a threaded drive shaft;
The actuating unit further comprises a sliding unit;
The sliding unit comprises a threaded collar that is threadedly engaged with the threaded drive shaft so that the stepper motor can drive the sliding unit to move linearly.
The control console according to claim 1. The operating unit further comprises a spring wire,
The linear movement of the sliding unit causes rotation of the shaft by a spring wire extending between the sliding unit and the shaft.
The control console according to claim 1 or 2. The operating unit further includes a magnet that attracts the spring wire to the sliding unit.
The control console according to claim 3. The spring wire is magnetically attracted to the curved surface of the sliding unit;
The control console according to claim 3 or 4. The actuating unit further comprises a sensor configured to detect a position of the sliding unit;
For example, the sensor comprises a Hall effect sensor,
The control console according to any one of claims 1 to 5. The actuation unit further comprises one or more moving end sensors configured to detect a movement limit of the sliding unit;
The control console according to any one of claims 2 to 6. One or more vibration sensors housed in the housing of the control unit;
In particular, each individual measurement module of the plurality of individual thromboelastometry measurement modules comprises one or more vibration sensors.
The control console according to claim 1. Each individual measurement module of the plurality of individual thromboelastometry measurement modules includes an evaluation unit for detecting a charge coupled device (CCD) component;
The evaluation unit (i) receives luminance distribution data from the CCD, (ii) generates CCD calibration data based on the luminance distribution data, and (iii) CCD luminance distribution obtained by measuring the CCD calibration data in real time. Configured to compare with data,
The control console according to claim 1. Each individual measurement module of the plurality of individual thromboelastometry measurement modules further includes a heater configured to heat a cup of the probe cup device.
The control console according to claim 1. A method for evaluating a charge coupled device (CCD) component of a thromboelastometry analysis system, the method comprising:
One or more processors of the thromboelastometry analysis system receiving luminance distribution data from the CCD, the luminance distribution data representing individual luminance data from a plurality of individual pixels of the CCD; ,
CCD calibration data, which is generated based on the luminance distribution data from the CCD, is generated by the one or more processors of the thromboelastometry analysis system;
The one or more processors of the thromboelastometry analysis system compare the CCD calibration data with real-time measured CCD luminance distribution data while the thromboelastometry analysis system is performing thromboelastometry analysis. And comprising,
Method. Further comprising measuring a position of a falling edge or a rising edge of the luminance distribution data from the CCD by the one or more processors of the thromboelastometry analysis system;
The method of claim 11. A method of controlling the accuracy of the thromboelastometry analysis system, the method comprising:
Receiving vibration data indicative of a vibration detection level of the thromboelastometry analysis system at one or more processors of the thromboelastometry analysis system;
Comparing the received vibration data with an acceptable threshold by the one or more processors of the thromboelastometry analysis system;
Responsive to the received vibration data greater than the tolerance threshold by the one or more processors of the thromboelastometry analysis system and based on a comparison of the received vibration data with the tolerance threshold; Generating a vibration error indication;
Method. Receiving at one or more processors of the thromboelastometry analysis system position indicating data indicating a detected position of the sliding unit relative to an operating unit of the thromboelastometry analysis system;
Comparing the received position indication data with one or more tolerance thresholds by the one or more processors of the thromboelastometry analysis system;
More than the one or more tolerance thresholds by the one or more processors of the thromboelastometry analysis system and based on a comparison of the received position indication data with the one or more tolerance thresholds. Generating a position error indication in response to the received location indication data being large,
The method of claim 13. A method for controlling the accuracy of a thromboelastometry analysis system, the method comprising:
Receiving at one or more processors of the thromboelastometry analysis system position indicating data indicating a detected position of the sliding unit relative to an operating unit of the thromboelastometry analysis system;
Comparing the received position indication data with one or more tolerance thresholds by the one or more processors of the thromboelastometry analysis system;
More than the one or more tolerance thresholds by the one or more processors of the thromboelastometry analysis system and based on a comparison of the received position indication data with the one or more tolerance thresholds. Generating a position error indication in response to the received location indication data being large,
Method. The position indication data comprises one or more signals from one or more moving end sensors that indicate whether the sliding unit is located at a target movement limit position.
The method of claim 15. The position indication data comprises one or more signals from one or more sensors that indicate the real time position of the sliding unit as the sliding unit moves back and forth along a straight path.
The method according to claim 15 or 16.