Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
Blood Testing System and Method
TECHNICAL FIELD
This document relates to systems and methods for testing characteristics of a
blood sample,
such as an automated thromboelastometry system for point-of-care whole blood
coagulation analysis.
BACKGROUND
Hemostasis is the human body's response to blood vessel injury and bleeding.
Hemostasis
involves a coordinated effort between platelets and numerous blood clotting
proteins (or clotting
factors), resulting in the formation of a blood clot and the subsequent
stoppage of bleeding.
Various methods have been introduced to assess the potential of blood to form
an adequate clot
and to determine the blood clot's stability. Common laboratory tests such as
thrombocyte counts or the
determination of fibrin concentration provide information on whether the
tested component is available
in sufficient amount, but some of those tests might not determine whether the
tested component works
properly under physiological conditions. Other laboratory tests work on blood
plasma, which may
impose additional preparation steps and additional time beyond what is
preferred, for example, in the
point-of-care context (e.g., in a surgical theater during a surgical
operation).
Another group of tests to assess the potential of blood to form an adequate
clot is known as
"viscoelastic methods." In at least some viscoelastic methods, the blood clot
firmness (or other parameters
dependent thereon) is determined over a period of time, for example, from the
formation of the first fibrin
fibers until the dissolution of the blood clot by fibrinolysis. Blood clot
firmness is a functional parameter
which contributes to hemostasis in vivo, as a clot must resist blood pressure
and shear stress
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at the site of vascular injury or incision. In many cases, clot firmness may
result from
multiple interlinked processes including coagulation activation, thrombin
formation,
fibrin formation and polymerization, platelet activation, and fibrin-platelet
interaction.
To isolate and test particular functions of thrombocytes, fibrinogen, and
other factors
in a blood sample, reagent compounds can be mixed with the blood sample to
activate
or inhibit certain components in the blood sample.
SUMMARY
Some embodiments of a system for testing characteristics of a blood sample
(which, as used herein, should be understood to include blood or derivatives
of blood
lo such as plasma) include a control console configured for testing a blood
sample to
provide a point-of-care whole blood coagulation analysis. For example, the
system
can serve as an automated thromboelastometry system for providing detailed and
prompt results of blood coagulation characteristics in response to receiving
one or
more samples of blood that have been mixed with various types of reagents.
In some embodiments, the thromboelastometry system includes a reusable
analyzer console and one or more single-use components configured to mate with
the
console. In one example, to operate the thromboelastometry system, a user is
prompted by a user interface of the analyzer console to initiate a number of
blood and
reagent transfer and mixing operations. Thereafter, the analyzer console
automatically performs (without requiring further user interaction with the
analyzer
console or the blood sample) the testing and displays the results on a
graphical display
using qualitative graphical representations and quantitative parameters. Such
assays
provide information on the whole kinetics of hemostasis, such as clotting
time, clot
formation, clot stability, and lysis; moreover, such information can be
promptly output
from a user interface of the system to provide reliable and prompt results
indicative of
a patient's blood characteristics at the point-of-care (e.g., while the
patient is in a
surgical room undergoing surgery).
In one implementation, a control console for measuring coagulation
characteristics of a blood sample includes: (i) a control unit housing, (ii) a
user
interface coupled to the control unit housing for displaying coagulation
characteristics
of a 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
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configured to receive a probe for testing the blood sample using a probe and
cup
arrangement. Each individual measurement module of the plurality of individual
thromboelastometry measurement modules includes a dedicated actuation unit
that
drives rotation of a respective shaft of the individual measurement module
independently from rotation of shafts of all other individual measurement
modules of
the plurality of individual thromboelastometry measurement modules.
Such a control console for measuring coagulation 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 driveshaft. In various embodiments, the
actuation unit
also includes a slider unit. The slider unit may have a threaded collar that
is
threadably engaged with the threaded drive shaft of the motor such that the
motor can
drive the slider unit to translate linearly. In particular embodiments, the
actuation unit
also includes a spring wire. In some such embodiments, a linear translation of
the
slider unit may cause a pivoting of the shaft because of the spring wire
extending
between the slider unit and the shaft.
In various embodiments of the control console for measuring coagulation
characteristics of a blood sample, the actuation unit further comprises a
magnet that
attracts the spring wire to the slider unit. The spring wire may be
magnetically
attracted to a curved surface of the slider unit. Optionally, the actuation
unit may
include a sensor that is configured to detect a position of the slider unit.
In some
embodiments, the sensor includes a Hall effect sensor. In various embodiments,
the
actuation unit may include one or more end-of-travel sensors that are
configured to
detect travel limits of the slider unit. The control console may also 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 particular embodiments of the control console for measuring coagulation
characteristics of a blood sample, each individual measurement module of the
plurality of individual thromboclastometry measurement modules includes an
evaluation unit for evaluating a charge-coupled device (CCD) component. In
some
embodiments, the evaluation unit may be configured to: (i) receive brightness
distribution data from the CCD, (ii) generate CCD calibration data based on
the
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brightness distribution data, and (iii) compare the CCD calibration data to
real-time-
measured CCD brightness distribution data. 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 of the probe and
cup
arrangement.
In another implementation. a method for evaluating a CCD component of a
thromboelastometry analysis system is performed by one or more processors of
the
thromboelastometry analysis system, or by one or more processors of an
individual
AD-module. The method includes receiving brightness distribution data from the
CCD, generating CCD calibration data (wherein the CCD calibration data is
generated
based on the brightness distribution data from the CCD), and comparing (while
the
thromboelastometry analysis system is performing a thromboelastometry
analysis) the
CCD calibration data to real-time-measured CCD brightness distribution data.
In
some embodiments, the brightness distribution data from the CCD represents
individual brightness 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 an individual AD-module may
optionally include one or more of the follow features. In some embodiments,
the
method further includes determining, a position of a falling or rising edge of
the
brightness distribution data from the CCD.
In another implementation, a method of controlling 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 an
individual
AD-module. The method includes receiving vibration data indicative of a
detected
level of vibration of the thromboelastometry analysis system, comparing the
received
vibration data to a threshold limit value, and generating a vibration error
indication in
response to the received vibration data being greater than the threshold limit
value.
Such a method of controlling accuracy of a thromboelastometry analysis
system may optionally include one or more of the following features. In some
embodiments, the method also includes receiving, at one or more processors of
the
thromboelastometry analysis system, positional indication data indicative of a
detected position of a slider unit in relation to an actuation unit of the
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thromboelastometry analysis system. In particular embodiments, the method also
includes comparing, by the one or more processors of the thromboelastometry
analysis system, the received positional indication data to one or more
threshold limit
values. In various embodiments, the method also includes generating, by the
one or
more processors of the thromboelastometry analysis system and based on the
comparison of the received positional indication data to the one or more
threshold
limit values, a position error indication in response to the received
positional
indication data being greater than the one or more threshold limit values.
In another implementations, a method of controlling 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 an
individual
AD-module. The method includes receiving positional indication data indicative
of a
detected position of a slider unit in relation to a actuation unit of the
thromboelastometry analysis system, comparing the received positional
indication
data to one or more threshold limit values, and generating (based on the
comparison
of the received positional indication data to the one or more threshold limit
values) a
position error indication in response to the received positional indication
data being
greater than the one or more threshold limit values.
Such a method of controlling accuracy of a thromboclastometry analysis
system may optionally include one or more of the following features. In some
embodiments, the positional indication data includes one or more signals from
one or
more end-of-travel sensors that indicate whether the slider unit is positioned
at a
targeted travel limit position. In particular embodiments, the positional
indication
data includes one or more signals from one or more sensors that indicate a
real-time
position of the slider unit as the slider unit linearly translates back and
forth along a
linear path.
Some or all of the embodiments described herein may provide one or more of
the following advantages. First, some embodiments of a thromboelastometry
system
described herein are configured with independent actuation units for
individual
modules or channels of multiple testing and measurement channels. For example,
in
some embodiments the thromboelastometry system includes four modules or
channels, each of which has an independent actuation unit. Accordingly, the
actuation
of each testing and measurement module can be controlled independently of the
other
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testing and measurement module. In addition, the use of independent actuation
units
for each module of multiple testing and measurement modules provides a modular
design that affords advantages for the performance of maintenance on the
system in
some scenarios.
Second, the actuation units of some embodiments of the thromboelastometry
system are driven using a rotary actuator that is positionally controllable
(e.g., a
stepper motor coupled to a programmable stepper motor control system, or
another
type of suitable rotary actuator with encoder feedback coupled to a control
system).
The use of positionally controllable actuators (e.g., motors) advantageously
allows for
programmable actuation patterns. In addition, in some embodiments stepper
motors
allow for greater precision of rotary thromboelastometry system actuation, as
compared to some other types of motors. Further, in some embodiments the
stepper
motors provide enhanced isolation from some external en-or influences, 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)
portion of the thromboelastometry detection system. Accordingly, measurement
inaccuracies can be reduced or eliminated in some cases. In some such
embodiments,
the functionality of each individual pixel of the CCD is verified prior to
operation of
thromboelastometry tests. In result, the consistency of the performance of the
thromboelastometry system is enhanced.
Fourth, some embodiments of the thromboelastometry system are configured
with additional firmware for supervising and evaluating functional aspects of
the
rotary thromboelastometry actuation and detection systems. For example, in
some
embodiments vibrations that might distort the measurement signals are detected
and
used to manage the thromboelastometry system. Further, in some embodiments
sensors are included that detect the movement and end-of-travel positions of
the
rotary thromboelastometry actuation systems. These systems for supervising and
evaluating functional aspects of the rotary thromboelastometry actuation and
detection systems provide a robust measurement system and facilitate enhanced
measurement quality (e.g., enhanced accuracy and/or precision of the
thromboelastometry measurements).
6
In accordance with an aspect of the invention is a control console for
measuring
coagulation characteristics of a blood sample, the control console comprising:
a control unit housing;
a user interface coupled to the control unit housing for displaying
coagulation
characteristics of the blood sample; and
a plurality of individual thromboelastometry measurement modules housed in the
control
unit housing, each individual thromboelastometry measurement module of the
plurality of
individual thromboelastometry measurement modules having a shaft configured to
receive a probe
for testing the blood sample using a probe and cup arrangement,
wherein said each individual thromboelastometry measurement module of the
plurality of
individual thromboelastometry measurement modules includes an actuation unit
comprising a
magnet that magnetically couples a spring wire to a slider unit and is
configured to provide liner
translation of the slider unit that drives rotation of the shaft of the
individual thromboelastometry
measurement module independently from rotation of the shafts of all other
individual
thromboelastometry measurement modules of the plurality of individual
thromboelastometry
measurement modules.
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The details of one or more embodiments of the invention are set forth in the
accompanying drawings and the description below. Other features, objects, and
advantages of the invention will be apparent from the description and
drawings.
DESCRIPTION OF DRAWINGS
FIG. 1 is a perspective view of an example thromboelastometry system, in
accordance with some embodiments.
FIG. 2 is an example of a graphic that quantifies the firmness of a blood clot
during clot formation, as calculated and displayed by the thromboelastometry
system of
FIG. 1.
FIG. 3 is a schematic diagram depicting an example rotary thromboelastometry
detection system portion of the thromboelastometry system of FIG. 1.
FIG. 4 is a perspective view of an example actuation and detection module
(also
referred to herein as an "AD-module" or "ADM") for an individual
thromboelastometry
measurement channel of the thromboelastometry system of FIG. I.
FIG. 5 is a perspective exploded view of the example AD-module of FIG. 4.
FIG. 6 is a perspective exploded view of an actuation unit of the example AD-
module of FIG. 4.
FIG. 7 is a perspective exploded view of a slider portion of the actuation
unit of
FIG. 6.
FIG. 8 is a flowchart of an example CCD evaluation process that can be used in
conjunction with the thromboelastometry system of FIG. 1.
FIG. 9 is a flowchart of another CCD evaluation process that can be used in
conjunction with the thromboelastometry system of FIG. 1.
FIG. 10 is a flowchart of a thromboelastometry measurement quality control
process that can be used in conjunction with the thromboelastometry system of
FIG. 1.
FIG. 11 is a flowchart of another thromboelastometry measurement quality
control process that can be used in conjunction with the thromboelastometry
system of
FIG. 1.
Like reference symbols in the various drawings indicate like elements.
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DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS
Referring to FIG. 1, some embodiments of an example blood testing system
100 include a blood analyzer console 110 along with a graphical user interface
120
that is coupled with the analyzer console 110. In the depicted embodiment, the
blood
testing system 100 is a thromboelastometry system that is configured to
determine a
number of blood coagulation characteristics of a blood sample. One 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 are based on the measurement of the
elasticity of blood by continuous graphic logging of the firmness of a blood
clot
during clot formation (e.g., pertaining to coagulation factors and inhibitors,
platelets
and fibrin) and subsequent fibrinolysis.
The example thromboelastometry system 100 performs in vitro blood
diagnostics, and is particularly advantageous at a point-of-care site (e.g.,
in a surgical
theater while a patient is undergoing or preparing for surgery, or the like).
Additionally, the thromboelastometry system 100 can be used as a whole blood
coagulation analysis system in a laboratory setting. The thromboelastometry
system
100 provides a quantitative and qualitative indication of the coagulation
state of a
blood sample.
In some embodiments, a graphical presentation displayed on the graphical user
interface 120 reflects the various blood diagnostic results (e.g., one or more
plots,
such as those sometimes refer to as a TEMogram, numeric data or measurements,
or a
combination thereof), which may describe the interaction between components
like
coagulation factors and inhibitors, fibrinogen, thrombocytes, and the
fibrinolysis
system. For example, referring also to FIG 2, in some embodiments the
graphical
user interface 120 provides a continuous graphic logging of the firmness of a
blood
clot during clot formation as a graphical presentation 200. FIG. 2 is an
example of a
graphic 200 that quantifies the firmness of a blood clot during clot
formation, as
calculated and displayed by the thromboelastometry system 100 during the
performance of an assay, for example. In some embodiments, multiple such
graphical
presentations 200 pertaining to the firmness of a blood clot during clot
formation are
concurrently displayed on the graphical user interface 120.
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Still referring to FIG. 1, in some embodiments the analyzer console 110 houses
the hardware devices and sub-systems that control the operations of the
thromboelastometry system 100. For example, the analyzer console 110 houses
one
or more processors and memory devices that can store an operating system and
other
.. executable instructions. In some embodiments, the executable instructions,
when
executed by the one or more processors, are configured to cause the system 100
to
perform operations such as analyzing of the blood test result data indicative
of the
blood coagulation characteristics, and outputting via the user interface 120.
In some embodiments, the analyzer console 110 also houses various internal
sub-systems, includes various electronic connection receptacles (not shown),
and
includes a cartridge port (not shown). The various electronic connection
receptacles
can include network and device connectors such as, but not limited to, one or
more
USB ports, Ethernet ports (e.g., RI45), VGA connectors, Sub-D9 connectors
(RS232),
and the like. Such connection receptacles can be located on the rear of the
analyzer
console 110, or at other convenient locations on the analyzer console 110. For
example, in some embodiments one or more USB ports may be located on or near
the
front of the analyzer console 110. A USB port, so located, may provide user
convenience for recording data onto a memory stick, for example. In some
embodiments, the thromboelastometry system 100 is configured to operate using
.. wireless communication modalities such as, but not limited to, Wi-Fi,
Bluetooth,
NFC, RF, IR, and the like.
Still referring to FIG. 1, in some embodiments, the graphical user interface
120
is also used to convey graphical and/or textual user instructions to assist a
user during
the preparation of a blood sample for testing by the thromboelastometry system
100.
Optionally, the graphical user interface 120 is coupled to the analyzer
console 110 and
is a touchscreen display whereby the user can, for example, input information
and
make menu item selections. In some embodiments, the graphical user interface
120 is
rigidly attached to the analyzer console 110. In particular embodiments, the
graphical
user interface 120 is pivotable and/or is otherwise positionally adjustable or
removable in relation to the analyzer console 110.
The blood testing system 100 may also 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
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barcode reader. Such an external barcode reader can facilitate convenient one-
dimensional or two-dimensional barcode entry of data such as, but not limited
to,
blood sample data, user identification, patient identification, normal values,
and the
like. Alternatively or additionally, the thromboelastometry system 100 can be
equipped with a reader configured to read near-field communication tags, RFID
tags,
or the like. In some embodiments, a computer data network (e.g., intranet,
internet,
LAN, etc.) may be used to allow for remote devices to receive and/or input
information from the thromboelastometry system 100.
The depicted thromboelastometry system 100 also includes an electronic
system pipette 160. Using the system pipette 160, a user can conveniently
dispense
volumetrically measured amounts of liquids (such as blood or reagents) during
the
process of preparing a blood sample prior to testing. In some embodiments, the
system pipette 160 is a semi-automatic, software controlled device. For
example, in
some embodiments the system pipette 160 automatically extracts a targeted
amount of
.. liquid from one container, and then the user can dispense the targeted
amount of
liquid into another container.
In some embodiments, operation of the blood testing system 100 includes the
use one or more reagents 170 that are mixed with a blood sample prior to
performance
of thromboelastometry. For example, the reagents 170 can comprise compounds
such
as, but not limited to, CaCl2, ellagic acid/phospholipids, tissue factor,
heparinase,
polybrene, cytochalasin D, tranexamic acid, and the like, and combinations
thereof.
In some embodiments, the thromboelastometry system 100 will provide user
instructions (e.g., via the graphical user interface 120) to mix particular
reagents 170
with the blood sample using the system pipette 160.
The thromboelastometry analyzer console 110 also includes one or more
individual thromboelastometry measurement stations 180 (which may also be
referred
herein to as "channels" or "measurement modules"). The depicted embodiment of
thromboelastometry system 100 includes four individual thromboelastometry
measurement stations 180 (i.e., four channels or four measurement modules).
As described further below, each thromboelastometry measurement station
180 includes a cup holder into which a user places a sample cup containing
blood and
reagents in preparation for thromboelastometry testing. In some embodiments,
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cup holders are equipped with a heating system so that the samples can be
warmed to
and held approximately at body temperature (e.g., 37 +/- 1.0 C).
As described further below, in some embodiments each thromboelastometry
measurement station 180 includes a pin or probe that can be removably
positioned
within the cup containing the sample to be tested. A clearance space exists
between
the probe and cup. In some embodiments, the shaft and probe is oscillated or
otherwise rotated, back and forth, by about less than 100 (in both rotational
directions), and preferably about 3' to about 6' (in both rotational
directions). In some
embodiments, such oscillations of the shaft and probe can be equal in
magnitude in
both rotational directions. The oscillations are measured, and as the
blood/reagent
mixture begins to become firmer because of thrombolysis, the oscillations are
reduced. The measurements, by the thromboelastometry measurement station 180,
of
such oscillations over a period of time thereby generates thromboelastometry
results.
Referring also to FIG. 3, an example rotary thromboelastometry actuation and
detection system 300 that can be present in each thromboelastometry
measurement
station 180 (measurement module) is schematically depicted. In some
implementations, a shaft 310 of the actuation and detection system 300 can
engage
with a single-use probe 138 to perform rotary thromboelastometry on a blood
sample
contained in a single-use cup 136. In FIG. 3, the probe 138 and the cup 136
are
shown in longitudinal cross-sections to allow for enhanced visibility and
understanding of the example rotary thromboelastometry actuation and detection
system 300 as a whole. 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 made suitably larger or
smaller.
In this particular embodiment, the schematically depicted example rotary
thromboelastometry actuation and detection system 300 includes a baseplate
302, a
shaft 310, a bearing 312, a mirror 314, a counterforce spring wire 320, a
light source
330, and a detector 340 (e.g., a charge-coupled device (CCD) or the like). The
single-
use cup 136 can be raised (e.g., by a user), as represented by arrows 318,
such that a
tip portion of the shaft 310 enters the bore 139 of the probe 138 to become
releasably
coupled with the probe 138. The bearing 312 is engaged with the baseplate 302
and
the shaft 310 to facilitate rotational movement of the shaft 310 in relation
to the
baseplate 302. The spring wire 320 is coupled to the shaft 310 and an induced
motion
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of the spring wire 320 (as driven by a motor described further below) can
induce the
shaft 310 to oscillate back and forth by less than 10 (in both rotational
directions),
and preferably about 30 to about 6 (in both rotational directions) as
represented by
arrow 316. The mirror 314 is coupled to the shaft 310. The light source 330 is
configured to project light towards the mirror 314, and light can be reflected
from the
mirror 314 towards the detector 340 (in a direction that is dependent on the
rotational
orientation of the shaft 310). Accordingly, the motion of the probe 138 is
detected by
an optical detection system (e.g., the detector 340). It should be understood
that other
configurations of the rotary thromboelastometry actuation and detection system
300
are also envisioned within the scope of this disclosure.
As the blood in the cup 136 begins to coagulate, the motion amplitude of the
shaft 310 starts to decrease (as detected by the reflection of the light beam
from
mirror 314 towards the detector 340). During coagulation, the blood's fibrin
backbone (together with platelets) creates a mechanical elastic linkage
between the
surfaces of the cup 136 and the probe 138. A proceeding coagulation process
induced
by adding one or more of the aforementioned activating factors (e.g.,
reagents) can
thus be observed and quantified.
The detected motion data from the detector 340 is analyzed by an algorithm
running on the analyzer console 110 to process and determine the
thromboelastometry
results. This system facilitates various thromboelastometry parameters such
as, but
not limited to, clotting time, clot formation time, alpha angle, amplitude,
maximum
clot firmness, lysis onset time, lysis time, lysis index (%), and maximum
lysis (%). In
this way, various deficiencies of a patient's hemostatic status can be
revealed and can
be interpreted for proper medical intervention. At the end of the test
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 can house one or more
rotary
thromboelastometry actuation and detection modules (AD-modules) 400
corresponding (e.g., one-to-one) with the one or more individual
thromboelastometry
measurement stations 180. Such rotary thromboelastometry AD-modules 400 can
operate, for example, like the example rotary thromboelastometry actuation and
detection system 300 described above in reference to FIG. 3.
Referring to FIG. 4, an individual rotary thromboelastometry AD-module 400,
broadly speaking, can include a housing 410 and a shaft 420. The shaft 420 can
be
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configured to releasably couple with a single-use probe (e.g., probe 138 of
FIG. 3) for
the performance of thromboelastometry and/or thromboelastography as described
above. That is, the shaft 420 can be rotationally oscillated back and forth,
for
example by less than 100 (in both rotational directions), and preferably about
3 to
.. about 6 (in both rotational directions) as described above.
Referring also to FIG. 5. an exploded view of the rotary thromboelastometry
AD-module 400 provides a greater visibility of the primary components of the
AD-
module 400. For example, the rotary thromboelastometry AD-module 400 includes
the housing 410 (including three housing portions 410a, 410b, and 410c), the
shaft
420, an actuation unit 430, a spring wire 440, an LED 450, a CCD 460, and a
printed
circuit board (PCB) assembly 470.
In some embodiments, the housing 410 includes a cover 410a, a base plate
410b, and a back-cover 410c. The housing 410 contains the other components of
the
AD-module 400, except for a portion of the shaft 420 which protrudes beyond
the
base plate 410b so that the shaft 420 can engage with a single-use probe.
Accordingly, in some embodiments the AD-module 400 is a discrete module that
can
be removed and replaced as a unit.
The rotary thromboelastometry AD-module 400 also includes the shaft 420.
In the depicted embodiment, the shaft 420 includes a bearing 422 and a mirror
424.
.. When the AD-module 400 is assembled, the bearing 422 is rigidly coupled
with the
base plate 410b. Hence, the shaft 420 can freely rotate in relation to the
base plate
410b. The mirror 424, which is affixed to the shaft 420, is configured to
reflect light
from the LED 450 towards the CCD 460. As the shaft 420 oscillates during
rotary
thromboelastometry testing, the direction of the mirror 424 also oscillates
correspondingly (because the mirror 424 is affixed to the shaft 420).
Therefore,
during rotary thromboelastometry testing, light from the LED 450 will be
reflected off
of the mirror 424 (and towards the CCD 460) at changing angles as the shaft
420
oscillates.
The rotary thromboelastometry AD-module 400 also includes the actuation
unit 430. The actuation unit 430 (which will be described in more detail in
reference
to FIG. 6 below) provides the motive force that causes the shaft 420 to
rotationally
oscillate.
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In the depicted embodiment, a spring wire 440 provides the linkage between
the actuation unit 430 and the shaft 420. In other words, the actuation unit
430 drives
the spring wire 440, and the spring wire 440 transmits the driving force from
the
actuation unit 430 to the shaft 420.
The rotary thromboelastometry AD-module 400 also includes the LED 450.
In some embodiments, the LED 450 is rigidly mounted to the PCB assembly 470,
and
the PCB assembly is rigidly mounted to the housing 410. The LED 450 emits
light
that is steadily directed toward the mirror 424. In some embodiments, one or
more
lenses are used in conjunction with the LED 450.
Light from the LED 450 reflects off of the mirror 424 in the direction of the
CCD 460. The CCD 460 includes multiple pixels that are arranged along the face
of
the CCD 460 (e.g., arranged generally linearly). Accordingly, the light
reflected from
the mirror 424 scans across the face of the CCD 460 as the shaft 420 pivots.
By
detecting the positions of the particular pixels of the CCD 460 that receive
the LED
light, the angular position and other characteristics pertaining to the
angular rotation
of the shaft 420 can be determined. In some embodiments, other types of light
detectors (other than a CCD type of detector) are used instead of, or in
addition to the
CCD 460.
The rotary thromboclastometry AD-module 400 also includes the PCB
assembly 470. The PCB assembly 470 includes electronic devices and circuitry
that
are used for the operation of the rotary thromboelastometry AD-module 400. In
particular embodiments, the PCB assembly 470 (including executable code stored
therein) comprises an evaluation unit configured for receiving brightness
distribution
data from the CCD, generating CCD calibration data based on the brightness
distribution data, and comparing the CCD calibration data to real-time-
measured CCD
calibration data. In some embodiments, the PCB assembly 470 includes a
microprocessor, motor driver, fuses, integrated circuits, and the like. The
PCB
assembly 470 can also include one or more types of sensors such as, but not
limited
to, vibration sensors, accelerometers, Hall-effect sensors, end-of-travel
detectors,
proximity sensors, optical sensors, micro-switches, and the like.
Referring to FIG. 6, an example actuation unit 430 of the rotary
thromboelastometry AD-module 400 is shown in an exploded perspective view for
greater visibility of the actuation unit's components. In the depicted
embodiment, the
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actuation unit 430 includes a motor 432, a slider unit 434, and a slider
guidance
member 438. The motor 432 is mounted to the slider guidance member 438. The
slider unit 434 is slidably engaged with the slider guidance member 438. The
motor
432 is engaged with the slider unit 434 so that the motor 432 can provide a
motive
force to the slider unit 434, as described further below.
The example actuation unit 430 is designed so as to provide a number of
operational advantages. For example, as will become more evident from the
description below, the actuation unit 430 is compact, lightweight, resistant
to external
vibrations, mechanically precise, electronically instrumented, highly
controllable,
.. repeatably positionable, durable, and so on.
In some embodiments, the motor 432 is a stepper motor. Accordingly, in some
such embodiments the motor 432 can be programmed and controlled to rotate and
operate in a prescribed fashion. That is, in some embodiments the motor 432
can be
programmed to operate in accord with selected parameters including
parameters
such as, but not limited to, rotational speed, number of revolutions,
acceleration,
deceleration, direction, and the like. Such factors can be programmed into the
memory of the rotary thromboelastometry AD-module 400 or the analyzer console
110. Therefore, various actuation curves for the motor 432 can be readily
selected
and/or adjusted as desired. In some implementations, all rotary
thromboelastometry
AD-modules 400 are programmed to operate using the same actuation curve. In
other
implementations, one or more rotary thromboelastometry AD-module 400 are
programmed to operate using a different actuation curve in comparison to one
or more
other rotary thromboelastometry AD-modules 400.
The motor 432 includes a drive shaft 433. In some embodiments, the drive
shaft 433 is a lead screw. The external threads of the lead screw can be
threadably
engaged with an internally-threaded portion of the slider unit 434. In some
such
embodiments, the drive shaft 433 is finely-threaded lead screw to facilitate
precise
and smooth control of the slider unit 434. When the drive shaft 433 and the
slider unit
434 are threadably engaged, a rotation of the motor 432 will result in a
linear
.. translation of the slider unit 434. That is, as the drive shaft 433 of the
motor 432
rotates, the slider unit 434 will slidably translate within the slider
guidance member
438. When the motor 432 reverses its direction of rotation (e.g., clockwise
versus
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counter-clockwise), the linear direction of the slider unit 434 in relation to
the slider
guidance member 438 will be reversed correspondingly.
Referring also to FIG. 7, an example of the slider unit 434 is shown in an
exploded perspective view for greater visibility of the slider unit's
components. The
slider unit 434 includes a curved member 435, a threaded collar 436, a spring
wire
retention magnet 437, a slider unit retention magnet 439, a spring wire
attachment
member 452, and a slider body 454. The threaded collar 436 and the curved
member
435 arc affixed to the slider body 454. The spring wire retention magnet 437
is
affixed to the curved member 435. The spring wire attachment member 452 is
engaged with the curved member 435 and the slider body 454. The slider unit
retention magnet 439 is affixed to the slider guidance member 438 and
magnetically
couples with the slider body 454.
The curved member 435 has a contoured lateral face with which the spring
wire 440 (refer to FIG 5) makes contact. As the curved member 435 linearly
translates back and forth within the slider guidance member 438, the contact
area
between the spring wire 440 and the contoured lateral face of the curved
member 435
positionally adjusts. That arrangement converts the linear motion of the
curved
member 435 into a smooth pivoting motion of the spring wire 440 (with the
shaft 420
acting as the pivot point).
The spring wire retention magnet 437 attracts the spring wire 440 so that the
spring wire 440 remains in contact with the contoured lateral face of the
curved
member 435 while the back and forth motion of the slider unit 434 takes place.
Additionally, in some embodiments the spring wire retention magnet 437 is used
in
conjunction with a Hall effect sensor mounted on the PCB assembly 470 (refer
to FIG.
5) so that the position of the slider unit 434 can be electronically
monitored.
The threaded collar 436 has internal threads that are complementary with the
external threads of the drive shaft 433 of the motor 432. Accordingly, the
threaded
collar 436, being constrained from rotating because of engagement with the
slider
body 454, linearly translates along the length of the drive shaft 433 of the
motor 432
as the drive shaft 433 turns. As the threaded collar 436 linearly translates,
the slider
body 454 and the curved member 435 also linearly translate (because the
threaded
collar 436 is affixed to the slider body 454). The slider unit retention
magnet 439,
being affixed to the slider guidance member 438 and magnetically coupled with
the
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slider body 454, serves to precisely maintain the slider body 454 in a close
running
relationship with the slider guidance member 438 as the slider body 454
translates
back and forth in relation to the slider guidance member 438.
The spring wire attachment member 452, which is coupled with the slider
body 454, serves to mechanically engage the spring wire 440 (refer to FIG. 5)
with the
slider unit 434. The spring wire attachment member 452 thereby facilitates a
mechanical connection between the spring wire 440 and the slider unit 434 (in
addition to the aforementioned magnetic coupling between the spring wire 440
and
the spring wire retention magnet 437). Moreover, in some embodiments the
spring
wire attachment member 452 includes physical features that are used for travel
or
end-of-travel detection of the slider unit 434. For example, in some
embodiments the
spring wire attachment member 452 includes one or more projections that are
detectable by sensor(s) mounted on the PCB assembly 470. Photo-sensors,
proximity
sensors, mechanical sensors, and the like, can be used to detect the position
of the
spring wire attachment member 452 in that fashion.
Referring to FIG. 8, in some embodiments one or more processors of the
thromboelastometry system 100 (refer to FIG 1) is configured to perform a CCD
evaluation process 800. In particular embodiments, such a CCD evaluation
process
800 can be implemented in one or more processors of an individual AD-module
(e.g.,
in one or more processors of PCB assembly 470 of example AD-module 400; refer
to
FIGS. 4 and 5). In some such embodiments, each individual measurement module
of
a thromboelastometry system 100 can include one or more processors that are
configured to perform the CCD evaluation process 800. Using the CCD evaluation
process 800, thromboelastometry measurement inaccuracies can be reduced or
eliminated in some cases. In result, the consistency of the performance (e.g.,
precision and accuracy) of the thromboelastometry system 100 can be enhanced.
At step 810, one or more processors of the thromboelastometry system or AD-
module receives CCD brightness distribution data. In some embodiments,
multiple
pixels of the CCD of an AD-module are activated using a light source (e.g.,
LED 450
of the example AD-module 400; refer to FIG. 5). The resulting data generated
by the
multiple pixels is received by the one or more processors.
At step 820, the one or more processors of the thromboelastometry system or
AD-module generates CCD calibration data using the CCD brightness distribution
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data received in step 810. In some embodiments, this is performed by making an
evaluation of the position of a falling or rising edge of the brightness
distribution data
from the CCD. The falling or rising edge of the brightness distribution data
may also
be referred to herein as a "flank."
At step 830, the one or more processors of the thromboelastometry system or
AD-module compare the calibration data generated in step 820 to real-time-
measured
CCD brightness data. In some embodiments, the real-time CCD evaluation process
of
step 830 is run (cycled) repeatedly while the thromboelastometry system is in
operation. For example, in some embodiments the cycle time of the ongoing real-
.. time CCD evaluation process 830 is less than about every 200 milliseconds.
In some
embodiments, the ongoing real-time CCD evaluation process 830 is an
optimization
process to fit the samples from calibration to the currently measured position
of a
falling or rising edge of the brightness distribution data (or brightness
distribution
flank).
Referring to FIG. 9, in some embodiments one or more processors of the
thromboelastometry system 100 (refer to FIG. 1) or AD-module is configured to
perform a two-phase CCD evaluation process 900. The two-phase CCD evaluation
process 900 includes a startup CCD evaluation process 910 and an ongoing real-
time
CCD evaluation process 920. Using the two-phase CCD evaluation process 900,
thromboelastometry measurement inaccuracies can be reduced or eliminated in
some
cases. In result, the consistency of the performance (e.g., precision and
accuracy) of
the individual AD-modules and of the thromboelastometry system 100 as a whole
can
be enhanced.
In some embodiments, the first stage of the two-phase CCD evaluation process
900 is to generate calibration data in form of samples (data points) to fit
on. This is
done, starting at step 911, by making an evaluation of the best possible
brightness
distribution flank at startup of the thromboelastometry system 100. At each
test
position on the CCD, each light signal distribution is analyzed to decide
whether the
pixel is OK or not OK. As an example, some pixels of the CCD may be deemed to
be
not OK due to performance deficiencies caused by contamination on the CCD.
In some embodiments, the condition of the CCD pixels are analyzed by
running a moving binomial average over the whole light distribution curve and
comparing the resulting values to the measured data. For each pixel, if the
difference
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between the moving binomial average over the whole distribution curve and the
pixel's measured value is greater than a threshold value, in some embodiments
the
pixel is deemed to be not OK. Conversely, if the difference between the moving
binomial average over the whole distribution curve and the pixel's measured
value is
less than a threshold value, the pixel is deemed to be OK.
In step 912, data regarding each pixel is stored in a buffer. That is, because
the
whole CCD is analyzed in step 911, a map of the disrupted pixels can be
calculated by
storing the position of all disrupted pixels in a buffer. The data is also
used as an
input to the ongoing real-time CCD evaluation process 920.
In step 913, the position of the CCD with the least concentration of not OK
pixels is determined as the best position to calibrate the CCD evaluation
algorithm at.
The mirror on the shaft (refer to FIG 4) is then rotationally positioned so
that the LED
light reflecting from the mirror is directed to the best position on the CCD.
In step 914, the measured brightness distribution curve at the best position
is
then filtered to remove outlier errors of the measured brightness distribution
curve at
the best position. In some embodiments, a filtering process is applied to
linearly
approximate outlier parts of the brightness distribution curve. This stage is
configured to resolve problems caused, for example, by any dirt that shades
parts of
the CCD. These dirty parts are mostly noticeable as wide and distinct areas of
significantly less illumination than usual (outlier errors). In some
embodiments, this
step uses an algorithm that includes two stages. The first stage is to sample
the curve
using a fixed step width and looking for unnatural outliers to be corrected.
The
second stage takes the start point of the outlier and searches for the end of
the outlier.
It does so by approximating a slope of the brightness distribution curve. The
algorithm assumes that the closest OK point is in the area of the extended
line of this
slope. Looking at the shape of a typical CCD brightness distribution curve and
the
resulting errors from dirt on the CCD, outliers should only increase point
values. This
algorithm has a low memory footprint and runs fast in comparison to some more
complicated filter kernels and FFT approaches.
In step 915, from the filtered data of step 914, a part of the right falling
or
rising edge of the brightness distribution data (flank) is extracted. The
algorithm is
designed to perform a robust detection of the right edge of the outlier
filtered
brightness distribution given.
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In some embodiments, starting from the minimum, the search algorithm is
designed to find the latest possible occurrence of a good match to the
searched value.
Because the brightness distribution data curve is rising, the latest possible
occurrence
has a high probability of being the wanted position. This custom made
algorithm is
very fast and reliable with low memory footprint.
In step 916, the extracted brightness distribution flank is then smoothed and
sampled. In some embodiments, this is done by applying very little noise to
the flank
and approximating the result with a curve fit model. Cubic B-splincs with
sufficient
interpolation points can approximate a nonlinear curve very well and hence are
superior to typical polynomial or linear interpolation that show only good
performance if the curve has the right shape.
In steps 917 and 918, samples with fixed step width are extracted as the final
calibration step and stored in a buffer. This substantially reduces the memory
footprint and speeds up the real-time evaluation, since less comparison
operations
need to be done.
The startup CCD evaluation process 910 is complete once the buffer
containing the positions of the not OK pixels (step 912) and the buffer
containing the
samples for the real time light beam position evaluation (step 918) are
appropriately
populated.
The ongoing real-time CCD evaluation process 920 is run (cycled) repeatedly
while the thromboelastometry system 100 is in operation. For example, in some
embodiments the cycle time of the ongoing real-time CCD evaluation process 920
is
about every 50 milliseconds. The ongoing real-time CCD evaluation process 920
is
an optimization process to fit the samples from calibration to the currently
measured
brightness distribution flank.
In step 921, the samples from step 918 are fit in comparison to a target
position by an interval based algorithm. The algorithm evaluates the samples
in the
middle of an interval, which contains the possible target positions on the
left side. In
some embodiments, the first interval (space) is the whole CCD pixel range. The
algorithm then decides if the wanted position is on right or left side of the
desired
position (which is possible because the brightness distribution is monotone).
That is,
if any pixel to the right of the middle is bigger, a new right border is
determined. The
current evaluated position now acts as the new right or left border of the new
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which halves the searched CCD pixel range. This scheme is repeatedly executed
until
the interval (space) has a length of one which means the destination is
reached. This
first fast fit algorithm greatly reduces the overall time needed to fit the
samples to the
measured curve. The algorithm only needs about 10 iterations to find the
target
position within about 10 pixel accuracy. The algorithm is superior in terms of
speed
in comparison to the more common least average approach used after this fast
fit.
In step 922, a precise weighted convergence to fit the samples as good as
possible is performed. This is done by calculating the average of the absolute
distances between all samples and their counterparts in the brightness
distribution
curve. Since for every pixel, information about their status (OK or not OK) is
in the
memory, one can ignore samples that compare to not OK pixels. This greatly
enhances robustness in comparison to a typical approach without ignoring known
bad
pixels.
In step 923, the location of the samples on the X-Axis (CCD Pixel Position,
.. buffer position) of the light beam position is determined and sent to
software.
Referring to FIG. 10, an AD-module error detection process 1000 is a loop
process that can be performed by a processor of a thromboelastometry
measurement
system. The AD-module error detection process 1000 can be performed to
evaluate
parameters that may be indicative of thromboclastometry actuation and
detection
system error causes.
At step 1 0 1 0, the AD-module error detection process 1 000 begins. The AD-
module error detection process 1000 can be performed in parallel with a
thromboelastometry measurement process.
At step 1020, a processor of the thromboelastometry measurement system
receives data that pertains to a detected amount of vibration that may affect
the
accuracy or precision of thromboelastometry measurement data from an AD-
module.
In some embodiments, the vibration is measured via a ball-based sensor that is
a
component of the AD-module (e.g., located on a PCB within the AD-module
housing). In some embodiments, other types of sensors are used for vibration
detection, such as one or more accelerometers, piezoelectric sensors,
displacement
sensors, velocity sensors, and the like.
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At step 1030, the processor compares the received vibration data to one or
more threshold values. If the received vibration data is greater than the
threshold
values, the processor generates a vibration-related error indication in step
1040.
At step 1050, a processor of the thromboelastometry measurement system
receives data that pertains to a detected position of moving components of an
AD-
module that may affect the accuracy or precision of thromboelastometry
measurement
data from the AD-module. For example, the positional indication data may
include,
but is not limited to, end-of-travel data, rotational position data, linear
translation
position data, and the like, and combinations thereof. In some embodiments, an
end-
switch that is a component of the AD-module (e.g., located on a PCB within
the AD-module housing) is used to detect the absolute position of the AD-
module
actuation unit. In some embodiments, the end-of-travel switch is in form of a
photo
optic sensor, or a proximity sensor, limit switch, and the like. In some
embodiments,
a Hall effect sensor that is a component of the AD-module (e.g., located on a
PCB
within the AD-module housing) is used to generate positional indication data.
Other
types of sensors that provide positional indication data may also be utilized.
At step 1060, the processor compares the received data that pertains to a
detected position of moving components of an AD-module to one or more
threshold
values. If the received positional data is greater than the threshold values,
the
processor generates a position error indication in step 1070. The process 1000
loops
back to step 1020 and repeats the process 1000.
Referring to FIG. 11, a process flowchart describes an AD-module
measurement loop 1100 and a thromboelastometry measurement and evaluation loop
1150 in substantial detail. The processes 1100 and 1150 include steps for
supervising
the operations of a thromboelastometry system 100 (refer to FIG. 1) to enhance
error
detection and the accuracy of the thromboelastometry system.
During thromboelastometry measurement, key aspects are supervised and
evaluated in real-time using processes 1100 and 1150. For example, vibrations
that
might distort the measurement signal are supervised and evaluated. Also, the
movement quality of the rotary thromboelastometry actuation and detection
system is
supervised and evaluated with a Hall effect sensor. In addition, the movement
precision of the rotary thromboelastometry actuation and detection system is
supervised and evaluated using one or more end-of-travel sensors. Further, the
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quality of the measurement signal is evaluated. The vibration, movement
quality, and
movement precision, in combination with the light beam position, allow the
processor
of the thromboelastometry system to determine the current quality of the
measurement signal, analyze the cause of distortions, and take responsive
measures.
In some embodiments, the AD-module measurement loop 1100 is executed
about every 50 milliseconds. In particular embodiments, the AD-module
measurement loop 1100 is part of the normal measurement routine on the AD-
module.
Steps 1104 and 1106 pertain to the position of the LED light beam of the AD-
module. For example, in some embodiments the light beam position is detected
and
evaluated.
Steps 1108 to 1114 pertain to the evaluation of the vibration. In some
embodiments, the vibration is measured via a ball-based sensor that is a
component of
the AD-module (e.g., located on a PCB within the AD-module housing). In some
embodiments, other types of sensors are used for vibration detection, such as
one or
more accelerometers, piezoelectric sensors, displacement sensors, velocity
sensors,
and the like. The resulting data that needs to be evaluated are vibration
events over
time. A typical evaluation algorithm could be a limit only allowing a certain
amount
of vibration events over a certain amount of time. If the limit is exceeded,
an error
message is sent to the processor running the thromboelastometry measurement
software.
Steps 1116 to 1120 include the evaluation of the rotary thromboelastometry
actuation and detection system by supervision with a Hall effect sensor that
is a
component of the AD-module (e.g., located on a PCB within the AD-module
housing). The measured data provides a characterization of the actual movement
of
the system. In some embodiments, an evaluation algorithm could be run to
compare
the measured movement with the theoretical movement the rotary
thromboelastometry actuation and detection system should execute. For example,
a
sum of absolute/squared difference between theory and reality are suitable
algorithms
when optimized properly. If a threshold amount of differences are detected, an
error
message is sent to the processor running the thromboelastometry measurement
software (at step 1122).
Steps 1124 and 1126 include the evaluation of the absolute movement position
of the rotary thromboelastometry actuation and detection system. An end switch
that
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is a component of the AD-module (e.g., located on a PCB within the AD-module
housing)
is used to detect the absolute position of the actuation unit with sub step
(stepper motor)
precision. In some embodiments, the end switch is in form of a photo optic
sensor, or a
proximity sensor, limit switch, and the like. The gathered statistical data of
the deviation
from the optimal position is used to determine if the actuation is operating
as expected. If
the actual position is differing enough from the target position for a
threshold amount of
time, an error message is sent to the processor running the thromboelastometry
measurement software (at step 1122).
At step 1122, the data gathered regarding the actuation quality from steps
1116
through 1126 allows a complete evaluation of the motion quality of the rotary
thromboelastometry actuation and detection system. In some embodiments, the
evaluation is attainable at low cost and small space in comparison, for
example, to using
an extra encoder for monitoring the stepper motor.
Turning now to a description of the thromboelastometry measurement and
evaluation loop 1150. Steps 1154 through 1158 pertain to the
thromboelastometry
measurement process as performed by the processor running the
thromboelastometry
measurement software.
Steps 1160 and 1162 describe the evaluation of the errors sent by the AD-
module
from process 1100. After the position is evaluated, the additional errors sent
by the AD-
module can be used to interpret the currently known errors by the processor
running the
thromboelastometry measurement software. The error type and frequency are
evaluated
by the software, and error messages are shown to the user if they are
significant enough
in frequency or if they are critical enough. In some embodiments, the AD-
module errors
can be correlated to measurement errors by the processor running the
thromboelastometry
measurement software, delivering additional information on what caused the
errors and
assisting further improvements on hardware, electronics, and firmware.
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.
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