Pre-processing for fluid transfer quality assessment

Abstract

A system for assessing a quality of a fluid process performed on a fluid including one of a fluid aspiration and a fluid dispense is provided. The system includes a pump; a probe; a connection, wherein a fluid path is formed between the pump and the probe at least in part by the connection; a pressure sensor in fluid communication with the fluid path and configured to sense pressures of the pump during the fluid process, wherein a pressure measurement data comprises the sensed pressures of the pump during the fluid process; and a processor; and a memory comprising instructions that are executed by the processor.

Description

PRE-PROCESSING FOR FLUID TRANSFER QUALITY ASSESSMENTCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 517,861 , entitled “PRE-PROCESSING FOR FLUID TRANSFER QUALITY ASSESSMENT’’ filed August 4, 2023, the disclosure of which is hereby incorporated by reference in its entirety for all purposes.TECHNICAL FIELD

[0002] The present disclosure relates generally to a method for pre-processing before quality assessment of a fluid process, and in particular to quality assessment of a fluid aspiration or a fluid dispense in laboratory' diagnostic instruments.BACKGROUND

[0003] In laboratory diagnostic instruments, a human sample is mixed with chemical reagents and the chemical reaction is studied / measured to predict the analyte or the health condition of the patient. The reagents are stored in small plastic reagent packs whereas the sample is stored in test tubes. A probe connected to a pump is used to aspirate or “draw” the required volume of reagent from the reagent pack or the sample from the test tube. Since the volume of the reagent or sample draw n is critical for a successful diagnostic test, a pressure sensor is used to prepare a pressure vs. time curve, hereby referred to as a “pressure trace.” The shape of the pressure trace is used to predict if the full volume was aspirated or whether only a part of the volume was aspirated with this condition being called a “short” aspiration. This monitoring of the pressure is used to reduce the risk of reporting an incorrect patient result due to incorrect reaction volumes.

[0004] The thresholds-based approach for aspiration volume check is based on studying the pressure traces and comparing calculated slopes, plateaus, or other features of the pressure trace at certain points on the pressure value vs. time curve to thresholds to determine the quality of the aspiration.

[0005] Various inflection points, slopes and height of the plateaus are used to make inferences on the aspiration quality'. Different volumes cause these points on the pressure trace to shift. Meaning, the same point along the x-y axis cannot be used to collect data to beused to compare to a threshold on different aspiration volumes. This problem is currently solved on various instrument platforms either by storing the inflection points for every volume aspirated (Immuno- Assay Module approach) or writing a function where the inflection points is the dependent variable and time or volume is the independent variable (Clinical Chemistry' Module approach). These solutions either creates a lifelong need to maintain different sets of points along the x-y axis at to collect data to be used to compare to a threshold for different aspiration volumes or increases the complexity of the algorithm.

[0006] For different assays, the reagent or sample volume aspirated can be different (e.g., 0 to lOOOuL). As a result, the pressure traces have different lengths due to, in part, differing aspiration durations. Further, for larger aspiration volumes, the pump needs to be operated at higher speed to meet the instrument time cycle requirement. Apart from the fluid characteristics and the diameter / lengths of the probe / tubing, the shape of the pressure trace is affected by aspiration time (larger time duration along x-axis for larger volumes) and aspiration speed (lower depth of the bathtub for higher speeds). Because pressure traces can differ, it is necessary to use different points along the x-y axis to collect data to be used to compare to a threshold for different volumes. Whether traditional thresholds-based algorithms, as described above, or futuristic machine learning algorithms are used for aspiration quality assessment, the pressure traces can create additional lifelong work to maintain different points along the x-y axis to collect data to be used to compare to a threshold for different volumes.

[0007] The present disclosure is directed to overcoming these and other problems of the prior art.SUMMARY

[0008] Embodiments of the present invention address and overcome one or more of the above shortcomings and drawbacks, by providing systems, methods, and computer program products for quality assessment of a fluid process. Additional features and advantages of the invention will be made apparent from the following detailed description of illustrative embodiments that proceeds with reference to the accompanying drawings.

[0009] In an exemplary embodiment, a system for assessing a quality' of a fluid process performed on a fluid including one of a fluid aspiration and a fluid dispense is provided. The system includes a pump; a probe; a connection, wherein a fluid path is formed between the pump and the probe at least in part by the connection; a pressure sensor in fluidcommunication with the fluid path and configured to sense pressures of the pump during the fluid process, wherein a pressure measurement data comprises the sensed pressures of the pump during the fluid process; and a processor; and a memory. The memory comprising instructions that are executed by the processor to cause the processor to receive, from the pressure sensor, pressure measurement data during the fluid process, wherein the pressure measurement data comprises pressure data and time data; modify, by the processor, the pressure measurement data to conform to a common domain; identify a datum at a common relevant plot area of the modified pressure measurement data, wherein the common relevant plot area comprises a relevant plot area that can be used to determine fluid process qualities of the fluid performed on a plurality of volumes of fluids that conform to the common domain; calculate, using the datum, a quality value; compare the quality value to a threshold, and determine, by the processor, the quality of the fluid process based on the comparison.

[0010] In some embodiments, the system further comprises an analyzer configured to analyze a mixture comprising the fluid when the quality of the fluid process is satisfactory. In some embodiments, the instructions further cause the processor to cause the pump to operate such that a subsequent fluid process is performed in response to determining that the quality of the fluid process is abnormal. In some embodiments, the common relevant plot area comprises a subset of the modified pressure measurement data associated with a pump phase. In some embodiments, the time data comprises one of duration and time stamps. In some embodiments, modifying the pressure measurement data comprises compressing the pressure measurement data in one of a time domain and a pressure domain. In some embodiments, modifying the pressure measurement data comprises reducing a number of data points. In some embodiments, modifying the pressure measurement data comprises converting the time data to integers; and interpolating new pressure data. In some embodiments, interpolating new pressure data comprising one of linear interpolation and nonlinear interpolation. In some embodiments, modifying the pressure measurement data comprises converting the pressure data to integers; and interpolating new time data. In some embodiments, the quality of the fluid process indicates one or more of an actual aspirated volume is less than an intended aspiration volume, the actual aspirated volume is equal to the intended aspiration volume, presence of air in the actual aspirated volume, and presence of a clog in the actual aspirated volume.

[0011] In another exemplary embodiment, a method of quality assessment of a fluid process is provided. The method includes performing, by a fluid processing system, the fluid process on a fluid, wherein the fluid process comprises one of a fluid aspiration and a fluid dispense; measuring, by the fluid processing system, pressure measurement data during the fluid process, wherein the pressure measurement data comprises pressure data and time data; modifying the pressure measurement data to conform to a common domain; identifying a datum at a common relevant plot area of the modified pressure measurement data, wherein the common relevant plot area comprises a relevant plot area that can be used to determine fluid process qualities of the fluid process performed on a plurality of volumes of fluids that conform to the common domain; calculating, using the datum, a quality' value; comparing the quality value to a threshold; and determining the quality assessment of the fluid process based on the comparison.

[0012] In some embodiments, the method further includes analyzing a mixture comprising the fluid in response to determining that the quality assessment of the fluid process is satisfactory. In some embodiments, the method further includes aspirating, by the fluid processing system, an additional fluid process in response to determining the quality assessment of the fluid process is abnormal. In some embodiments, the common relevant plot area comprises a subset of the modified pressure measurement data associated with a pump phase. In some embodiments, time compnses one of duration and time stamps. In some embodiments, wherein modifying the pressure measurement data comprises compressing the pressure measurement data in one of a time domain and a pressure domain. In some embodiments, modifying the pressure measurement data comprises reducing a number of data points. In some embodiments, the common domain comprises a common time domain and modifying the pressure measurement data comprises compressing the time data to the common time domain; and interpolating new pressure data.

[0013] In yet another exemplary embodiment, a computer program product embodied in a computer readable storage medium is provided. The computer readable storage medium includes software that when executed by a processor performs a method comprising receiving, from a pressure sensor, pressure measurement data during a fluid process performed on a fluid, wherein the pressure measurement data comprises pressure data and time data; modifying, by the processor, the pressure measurement data to conform to a predetermined value; identifying a datum at a common relevant plot area of the modifiedpressure measurement data, wherein the common relevant plot area comprises a relevant plot area that can be used to determine fluid process qualities of the fluid performed on a plurality of volumes of fluids that conform to the common domain; calculating, using the datum, a quality value; comparing the quality value to a threshold; and determining, by the processor, a quality7of the fluid process based on the comparison.

[0014] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Additional features and advantages of the disclosed technology will be made apparent from the following detailed description of illustrative embodiments that proceeds with reference to the accompanying drawings.BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The foregoing and other aspects of the present invention are best understood from the following detailed description when read in connection with the accompanying drawings. For the purpose of illustrating the invention, there are shown in the drawings embodiments that are presently preferred, it being understood, however, that the invention is not limited to the specific instrumentalities disclosed. Included in the drawings are the following Figures:

[0016] FIG. 1 is a graph of representative pressure traces for various aspiration volumes and at different aspiration speeds, according to an embodiment of the disclosure;

[0017] FIG. 2 is an aspiration system with pressure monitoring, according to an embodiment of the disclosure;

[0018] FIG. 3 is an example of short aspiration detection, according to an embodiment of the disclosure;

[0019] FIG. 4 is a method of aspiration quality assessment, according to an embodiment of the disclosure;

[0020] FIGS. 5A-5C are graphs showing unmodified pressure vs. time data and pressure vs. time data modified using linear interpolation, according to embodiments of the disclosure;

[0021] FIG. 6 is a table of linear interpolation modifying pressure vs. time data, according to an embodiment of the disclosure;

[0022] FIG. 7 is a graph of the unmodified pressure vs. time data and modified pressure vs. time data from FIG. 6, according to an embodiment of the disclosure.

[0023] FIGS. 8A-8D are pressure traces annotated to with relevant plot areas, according to embodiments of the disclosure;

[0024] FIG. 9 is pressure trace annotated with examples of using data from the pressure trace to calculate aspiration quality values and using them to assess aspiration quality', according to an embodiment of the disclosure; and

[0025] FIG. 10 illustrates an exemplary computing environment, according to an embodiment of the disclosure.DETAILED DESCRIPTION

[0026] Independent of the grammatical term usage, individuals with male, female or other gender identities are included with this term.

[0027] The present disclosure describes systems, methods, and computer program products for quality assessment of a fluid process. In some embodiments, the systems, methods, and computer program products described herein can be used, for example, in an IVD environment, using IVD equipment, or as part of IVD methods. For example, in some embodiments, the systems, methods, and computer program products described herein can be used with diagnostic or chemistry analyzers like automated clinical diagnostic analyzers and automated clinical chemistry analyzers. These analyzers can process hundreds of thousands of human sample diagnostic tests per year. These tests can be prescribed to a patient by a Primary Care Physician (e.g., general health checkup), a specialist (e.g., heart, cancer), and in a hospital setting (e.g., prior to treatment or surgery).

[0028] The presently disclosed subject matter is described in the context of being used during a fluid aspiration. The present disclosure, however, is not so limited, and can be applicable to other processes. The present disclosure, for example and not limitation, can be used during a fluid dispense. Such implementation and application are contemplated within the scope of the present disclosure. Accordingly, when the present disclosure is described in the context of being used during a fluid aspiration, it will be understood that other implementations, like fluid dispense, can take the place of those referred to.

[0029] Further, the presently disclosed subject matter is primarily described in the context of pressure traces the shape of which change depending on the volume of fluid aspirated. However, as one of ordinary skill in the art will appreciate, a pressure trace’s shape can also change depending on a variety of other variables, for example, including, for example, aspiration duration, aspiration speed, and geometry7of the probe and tubing. It is to be understood that the systems, methods, and computer program products described herein are functional for all aspiration quality7assessment of all pressure traces, regardless of the variable that drives their change in shape.

[0030] Furthermore, the presently disclosed subject matter is primarily described in the context plotted modified or unmodified pressure vs. time data. However, as one of ordinary skill in the art will appreciate, the data itself, rather than a graph or a plot of the data, can be analyzed according to the systems, methods, and computer program products disclosed herein. In other words, in some embodiments, the data is not plotted at all.

[0031] Determining the quality of a metered sample or reagent transfer is an important function of a clinical diagnostic instrument, for example, in an IVD environment. Typical failure modes that are desirable to detect include probe clogs and insufficient sample or reagent in the liquid vessel, among others. A common method for determining the quality of an aspiration (or dispense) is monitoring the pressure in the aspiration system during the event (such as illustrated in FIG. 2), analyzing that pressure, and making a determination of the quality7of the aspiration / dispense. FIG. 2 is an aspiration system with pressure monitoring, according to an embodiment of the disclosure. In some embodiments, the aspiration system 100 can include a pump 101, tubing 102, a pressure transducer 103, a probe 104, and a liquid vessel 105.

[0032] One method of detecting aspiration quality is to compare the aspiration pressure signal with that of a predetermined value of air or other liquid or gas. such as disclosed in U.S. Patent No. 7,867,769, which is hereby incorporated by reference herein in its entirety7. Another is to analyze the pressure signal to detect abnormalities, such as disclosed in U.S. Patent Nos. 6,370,942 and 7,634,378, which are hereby incorporated by reference herein in their entireties.

[0033] Factors impacting the pressure signal may be, for example, the pressure drop during an aspiration and probe and tubing diameters and lengths. The pressure drop duringan aspiration can be dictated by the following factors: (1) liquid or gas properties (e.g., density, dynamic viscosity, etc.) (2) flow rate, and (3) probe and tubing diameters and lengths. In one embodiment, this can be demonstrated with an analysis using the Bernoulli equation for the steady state portion of the aspiration as follows:P = Pressure p = Density / g = Gravitational constant a = Energy correction v = Velocity’ h = Height factorwhere: is the effect of fluid density is the effect of tubing and pipettor geometry is the effect of height of liquid column is the effect of flow resistance

[0034] Further analysis can provide more details about the effects of probe diameters, fluid viscosities. In the equation below, which shows main influencers on the pressure drop, it can be seen that viscosity directly influences the pressure drop during aspiration, and that probe diameter has a very significant effect.

[0035] The effect of aspiration flow rate can be seen in FIG. 1, which is a graph of representative pressure traces for various aspiration volumes and at different aspiration speeds, according to an embodiment of the disclosure. As one of ordinary skill in the art would expect, as flow rate increases, pressure decreases, whether aspirating liquid or air. The difference between an air or liquid aspiration increases proportionately as well. Note that aspirations of varying volumes but using the same flow rate have the same pressure drop.

[0036] Conventional algorithms typically identify key points or regions on the pressure curve, referred to herein as “relevant plot areas” or RPAs ’ Values of data within those RPAs may then be directly compared to a threshold value (such as a minimum pressure), or used in a calculation to determine a value that can then also be compared to a threshold value(s). For example, a best-fit slope may be calculated across a region of the curve, or a comparison of a difference between points (or averages of points) at two or more regions of the pressure curve. Often each curve is evaluated against multiple criteria, each of which is optimized to find a specific feature or failure mode.

[0037] For example, as illustrated in FIG. 3. the pressure value at the RPA labeled “evaluation point” of each line can be compared to a threshold to determine the quality of the aspiration. FIG. 3 illustrates numerous aspirations of air and liquid. During two of those liquid aspirations, insufficient liquid was available, resulting in a “short” aspiration.Photometric analysis of the transferred material revealed that these to aspirations were 40% and 16% short, respectively. While the 40% short aspiration is clearly separated from the norm at the end of the steady-state aspiration (-140ms), the 16% short aspiration is somewhat more difficult to distinguish.

[0038] As described above, pressure traces have different lengths (i.e., along the x-axis) and heights (i.e., along the y-axis) for a variety of reasons including, for example, the volume of fluid aspirated. Because the length and / or height of the pressure trace can differ for each volume aspirated, the RPA at which to collect data to be used to compare to a threshold can be different for each volume aspirated. For example, while in FIG. 3 the RPA to determine whether or not a 50uL aspiration was short is located at T = 140 ms, this RPA will not be accurate for a different volume of aspiration, for example lOOuL. Therefore, one must determine, store, and maintain RPAs for each volume aspirated or, alternatively or additionally, use a complex inflection-point-dependent algorithm.

[0039] However, the slopes, plateaus, and other features of a pressure trace, regardless of the volume of fluid aspirated, will substantially align when the pressure trace is compressed (or expanded) to a fixed length in the time domain. The method disclosed herein leverages this discovery by providing a method of determining aspiration quality that includes compressing pressure traces to a fixed length in the time domain.

[0040] One of ordinary skill in the art might be dissuaded from compressing a pressure trace prior to analysis for fear that the compression would negatively affect the results of the subsequent analysis. However, when a high enough sampling frequency is used during the aspiration / dispense, the pressure trace’s shape is maintained after compression and the results are therefore not negatively affected by the compression.

[0041] A pressure trace of a fixed length in the time domain or a fixed height in the pressure domain could also be achieved by adjusting the sampling rate for each aspiration / dispense so that a fixed number of datapoints is output. However, this approach is not practical because the total duration of the aspiration / dispense is not always known ahead of time. Compressing the pressure trace after aspiration / dispense effectively provides a variable sampling rate without having to adjust the sampling rate for each aspiration / dispense.

[0042] Compressing the pressure trace and analyzing the compressed pressure trace has several advantages. First, maintenance of the RPAs and algorithm can be simple. Second, the amount of data needed for algorithm development can be significantly reduced. Third, it can be used to accurately analyze pressure traces for which there is insufficient data to generate accurate RPAs. Fourth, it reduces the reliance on the experience of the technician interpreting the pressure trace.

[0043] Compressing the pressure trace and analyzing the compressed pressure trace makes maintenance of the RPAs and algorithm simple; it permits the use of one set of RPAs for any volume of fluid aspirated, as long as that volume’s pressure trace is compressed, rather than having one set of RPAs for each volume. Thus, there is no longer a need to use a complex inflection-point-dependent function or to develop, store, and maintain a set of RPAs for multiple volumes; only one set of RPAs needed.

[0044] In addition, compressing the pressure trace and analyzing the compressed pressure trace significantly reduces the amount of data, which is expensive, needed for machine learning algorithm development. Instead of having to train, and retrain, a machine learning algorithm for each volume of fluid to be aspirated, only one machine learning algorithm is needed for a pressure trace compressed to a predetermined width. This greatly reduces the amount of data needed for training and retraining purposes.

[0045] Even more, compressing the pressure trace and analyzing the compressed pressure trace permits accurate analysis of pressure traces for which there is insufficient data to generate accurate RPAs. For less common volumes (e.g., 38uL), there may not be sufficient data to accurately determine RPAs. But, with this solution, the RPAs work for all volumes (provided that they are compressed), including volumes that for which insufficient data exists to determine accurate RPAs. Said another way, compressing the pressure trace and analyzing the compressed pressure trace makes analysis of certain volumes possible that were previously impossible.

[0046] Moreover, compressing the pressure trace and analyzing the compressed pressure trace reduces reliance on the experience of the technician interpreting a pressure trace. As one of ordinary skill in the art will appreciate, a technician gains experience in interpreting pressure traces for a variety of volumes. For example, a technical expert who has viewed hundreds of pressure traces may have the experience to know that certain events on a pressure trace are normal for one volume of aspiration but abnormal for another. But, with the method of aspiration quality assessment disclosed herein, a technician need only gain experience viewing one plot, not one plot per volume.

[0047] FIG. 4 is a flow chart of an embodiment of a method of determining aspiration quality, according to an embodiment. At step 401, the method 400 can include aspirating a fluid. The fluid can be anything that creates a pressure profile, for example, a biological sample, a liquid reagent, or air. At step 402, the method 400 can include measuring pressure over time while the fluid is aspirated. In some embodiments, pressure can be measured by a pressure sensor connected to tubing between a pump and a probe. Pressure can be measured in time stamps or duration.

[0048] In some embodiments, the raw pressure vs. time data can be filtered to reduce or eliminate noise. In some embodiments, an outlier electrical noise prefilter can be applied to raw data points (i.e., datapoints with a delta of more than 2,500 can be replaced with the moving average of the preceding three datapoints). This can be limited to 10% of raw datapoints. In some embodiments, the Butterworth low pass filter can also be applied to raw data in each of the three motion phases with different coefficients (i.e., for cutoff frequency) for each phase. For example, for the acceleration delay phase, the filtering can be undamped with a cutoff of 0.05; for the slew phase, the filtering can be critically damped with a cutoffof 0.04; and for the deceleration delay phase the filtering can be underdamped with a cutoff of 0.075. In some embodiments, the pressure over time data, filtered or raw, can be plotted.

[0049] At step 403, the method can include modifying the pressure vs. time data such that it conforms to a common scheme. In some embodiments, the common scheme is defined by a maximum time value. For example, the maximum time value can be no values over 100 ms in duration. In some embodiments, the common scheme is defined by a period of time, 3:00 pm to 3:05 pm, for example. In other embodiments, the common scheme is defined by a minimum pressure value. For example, the minimum pressure value can be no values less than -400 counts.

[0050] In some embodiments, the common scheme is defined by a number of data points. For example, a common scheme may include 100 data points. FIGS. 5A-5C illustrate an example of this embodiment. FIGS. 5A-5C are graphs showing unmodified pressure vs. time data and pressure vs. time data modified using linear interpolation, according to an embodiment of the disclosure. FIG. 5A is a graph of unmodified pressure vs. time data for 38uL, 50uL, and lOOuL pressure traces, according to an embodiment of the disclosure. FIG. 5B is a graph with the pressure vs. time data plotted in FIG. 5A modified to conform to common time scheme that includes 100 data points from 1 to 100. FIG. 5C is a graph with both the unmodified and modified pressure vs. time data in FIGS. 5A and 5B, respectively.

[0051] The pressure vs. time data can be conformed to a common time scheme by any method known in the art. In some embodiments, the pressure vs. time data can be compressed or expanded to the common time scheme. For example, this can be visualized as stretching, or compressing, as applicable, the pressure trace along the x-axis (or the y-axis, or both the x-axis and the y-axis) and stopping when the desired pressure trace length is achieved.

[0052] In some embodiments, datapoints can be removed from or added to the pressure vs. time data. For example, if the common time scheme 100 datapoints and the unmodified pressure vs. time data has 200 datapoints, modifying the pressure vs. time data can include removing every other datapoint to reduce the pressure vs. time data to 100 datapoints. For another example, if the common time scheme is 100 datapoints and the pressure vs. time data has 50 datapoints, modifying the pressure vs. time data can include adding a datapoint between each raw' datapoint to increase the pressure vs. time data to 100 datapoints. Theadditional datapoints can be determined, for example, using interpolation, as one of ordinary skill in the art will appreciate.

[0053] In some embodiments, interpolation can be used to generate new pressure vs. time data based on the raw pressure vs. time data. For filtered data, interpolation can be performed before or after filtering. Interpolation can help maintain the shape of the pressure trace. Interpolation can be linear or non-linear. FIG. 6 is a table of linear interpolation modifying pressure vs. time data, according to an embodiment of the disclosure. In FIG. 6, column “38-xl” includes the raw time data and column “38-yl'’ includes the raw pressure data. Column “38-xnew” includes the modified time data. In the embodiment illustrated in FIG. 6. the new time data are integers beginning with zero and ending with seventeen. Column “38-ynew” includes the modified pressure data. The modified pressure data is calculated using linear interpolation. Columns “slope-m,” “yintercept-c,” and “ycomp” include values helpful to calculate the modified pressure data, as one of ordinary skill in the art will appreciate. FIG. 7 is a graph of the unmodified pressure vs. time data and modified pressure vs. time data from FIG. 6, according to an embodiment of the disclosure.

[0054] In some embodiments, generating new pressure vs. time data can be done using the interpolate. interp ld(x, y) function in the Python SciPy library. However, the same can be achieved using any other software program. To generate new pressure vs time data using, for example, Python SciPy’s interpolate.interpld(x, y), the following steps can be performed: The pressure trace values y are mapped to the unmodified time interval x. Next, the x is scaled to the required length (e.g., 100). Y values are interpolated to the integers on this new compressed x-scale, yielding a uniform number of points for every pressure trace.

[0055] To illustrate, consider the following example. Consider the following inputs: aspiration volume 38uL, Original_Trace_Length = 334, Compressed_Trace_Size = 100. Y array holds the original unmodified pressure trace. Length of y depends on the volume aspirated. Y array = row[0: Original_Trace_Length -1] = row[0:334-l ] = (-86, -94, -102, ...) = 334 data points.

[0056] Step Size is the difference between adjacent x values on the compressed scale onto which the original uncompressed x scale is mapped. The step size depends on the scaling ratio of compressed to uncompressed pressure trace. Step_Size = Compressed_Trace_Size / Original_Trace_Length = 100 / 334 = 0.299.

[0057] x array holds ascending fractional numbers from zero through Compressed Trace Size. Length of x depends on the volume aspirated. X array = np.arange(O, Compressed_Trace_Size, Step_Size) = (0, 0.299, 0.598, ... , 99.701) = 334 data points.

[0058] xcomp array holds the integer x values of final compressed length specified by Comp_Trace_Size. Xcomp Array = np.arange(0, Compressed_Trace_Size) = (0, 1, 2, ...., 99) = 100 data points.

[0059] The following functions interpolate y -values that are at fractional x-values in the mapped x-array to the integers on the new compressed x-scale:

[0060] f is the interpolate Id function from the Python SciPy library. Linear interpolation has been used. But non-linear interpolation can also be used in this application, f = interpolate. interp ld(x. y).

[0061] Ycomp array contains the compressed pressure trace after applying function f on xcomp. Ycomp = f(xcomp) = (-86, -103.333 -80, ... ) = 100 data points.

[0062] FIGS. 5 and 6 show the first 18 points of the unmodified pressure trace for 38uL are reproduced. Adjacent points are joined by straight lines and slope m and y intercept of these individual lines are calculated using the formulae below. This calculation is only being done for the explanation of linear interpolation. All of this can be automatically done by the interpol ate.interpl d() function of the SciPy library.

[0063] Slope m = (y2-yl) / (x2-xl)

[0064] Y intercept c = y2 — m.x2

[0065] Ycomp is calculated manually below and it closely matches the compressed 38- ynew done by the function f

[0066] ycomp = m.38-xnew + c

[0067] In some embodiments, the method 400 can include plotting the modified pressure vs. time data. With the modified pressure vs. time data plotted, common RPAs can be applied to the plot. An RPA is an area of the plot defined by x and y coordinates. The data located within the RPA be used to calculate an aspiration quality value. An RPA can be assmall as one datapoint. An aspiration quality value is a value that can be compared to a threshold to determine the quality of an aspiration.

[0068] Examples of aspiration quality values include, for example and not limitation, slope, viscosity delta, residual, and clog delta. The linear regression slope in the slew phase is an aspiration quality value that can be indicative of the fluid’s material density. Accordingly, it can be important to know when the slew phase begins and ends. An RPA 801a can be applied to the area of the graph associated with the slew phase, as illustrated in FIG. 8A, and the linear regression slope of the pressure trace within that RPA can be calculated. That slope can be compared to a threshold to make a determination regarding the fluid’s material density.

[0069] Viscosity7delta is an aspiration quality7value that can be indicative of the fluid’s material viscosity. Viscosity delta can be calculated by subtracting the last pressure value in the slew phase from the last pressure of the post aspiration delay phase. Accordingly, it is important to know when the slew phase and the post aspiration delay phase begin and end. An RPA 801b can be applied to the area of the graph associated with the slew phase, and another RPA 801c can be applied to the area of the graph associated with the post aspiration delay phase, as illustrated in FIG. 8B. The last pressure value in each of those RPAs could be used to calculate the viscosity delta. The viscosity delta can be compared to a threshold to make a determination regarding the fluid’s material density.

[0070] Residual is an aspiration quality value that can be indicative of an abnormal aspiration profile, e.g., a short. Residual can be calculated using the following equation with data from the slew phase: Residual = [Slope(m) X Xn+ intercept(b ] — yn. Accordingly, it can be important to know when the slew phase begins and ends. An RPA 801 d can be applied to the area of the graph associated with the slew phase, as illustrated in FIG. 8C. The inputs required for calculation of residual can be pulled from within the area of the plot identified as RPA 801 d. The residual can be compared to a threshold to make a determination regarding the aspiration’s profile.

[0071] Clog delta is an aspiration quality value that can be indicative of a major obstruction. Clog delta can be calculated by subtracting the pressure trace’s first pressure value and from its last pressure value. Accordingly, it can be important to know when the first and last pressure values are. When the common time scheme is integers from, forexample, zero to 100, the first pressure value will be the pressure value at x=0 and the last pressure value will be the pressure value at x=100. Exemplary’ RPAs are illustrated in FIG. 8D as 801e and 801 f. The clog delta can be compared to a threshold to make a determination regarding the presence of a probe obstruction.

[0072] Returning to FIG. 4, in some embodiments, the method 700 can optionally include shifting or offsetting the pressure trace so its starting value is zero. This can be done, for example, by subtracting the difference between the pressure trace’s starting value and zero for every' datapoint in the pressure trace, either before or after it is conformed to a common domain. This can have the effect of removing pressure sensor offset differences, thus removing one source of input "noise" that the algorithm would otherwise need to resolve.

[0073] At step 404, the method 400 can include calculating an aspiration quality’ value. At step 405, the method can include comparing the aspiration quality value to a threshold. Each aspiration quality value can be compared to its own threshold. For example, there may be a slope threshold, a viscosity delta threshold, a residual threshold, and a clog delta threshold. In some embodiments, the thresholds used for comparison to evaluate a pressure curve to yield a pass / fail result are determined empirically. In other words, a large number (hundreds to thousands) of pressure curves can be generated at each condition, and a statistical distribution of the calculated values can be established. These distributions can be used to determine a pass / fail limit (i.e., the threshold) that has an appropriate level of consumer / producer risk. This determination must be performed for each set of conditions (e.g., flow rate, volume, sample type, etc.).

[0074] FIG. 9 is pressure trace annotated with examples of using data from the pressure trace to calculate aspiration quality’ values and using them to assess aspiration quality', according to an embodiment of the disclosure.

[0075] FIG. 10 illustrates an exemplary computing environment 1000 within which embodiments of the invention may be implemented. For example, this computing environment 1000 may be configured to execute a method of placing an item having irregular dimensions. The computing environment 1000 may include computer system 1010, which is one example of a computing system upon which embodiments of the invention may be implemented. Computers and computing environments, such as computer system 1010 andcomputing environment 1000, are known to those of skill in the art and thus are described briefly here.

[0076] As shown in FIG. 10, the computer system 1010 may include a communication mechanism such as a bus 1005 or other communication mechanism for communicating information within the computer system 1010. The computer system 1010 further includes one or more processors 1020 coupled with the bus 1005 for processing the information. The processors 1020 may include one or more central processing units (CPUs), graphical processing units (GPUs), or any other processor known in the art.

[0077] The computer system 1010 also includes a system memory 1030 coupled to the bus 1005 for storing information and instructions to be executed by processors 1020. The system memory71030 may include computer readable storage media in the form of volatile and / or nonvolatile memory, such as read only memory7(ROM) 1031 and / or random access memory (RAM) 1032. The system memory RAM 1032 may include other dynamic storage device(s) (e g., dynamic RAM, static RAM, and synchronous DRAM). The system memory ROM 1031 may include other static storage device(s) (e.g., programmable ROM, erasable PROM, and electrically erasable PROM). In addition, the system memory 1030 may be used for storing temporary7variables or other intermediate information during the execution of instructions by the processors 1020. A basic input / output system (BIOS) 1033 containing the basic routines that help to transfer information between elements within computer system 1010, such as during start-up, may be stored in ROM 1031. RAM 1032 may contain data and / or program modules that are immediately accessible to and / or presently being operated on by the processors 1020. System memory 1030 may additionally include, for example, operating system 1034, application programs 1035, other program modules 1036 and program data 1037.

[0078] The computer system 1010 also includes a disk controller 1040 coupled to the bus 1005 to control one or more storage devices for storing information and instructions, such as a hard disk 1041 and a removable media drive 1042 (e.g., floppy disk drive, compact disc drive, tape drive, and / or solid state drive). The storage devices may be added to the computer system 1010 using an appropriate device interface (e.g.. a small computer system interface (SCSI), integrated device electronics (IDE), Universal Serial Bus (USB), or FireWire).

[0079] The computer system 1010 may also include a display controller 1065 coupled to the bus 1005 to control a display 1066, such as a cathode ray tube (CRT) or liquid crystal display (LCD), for displaying information to a computer user. The computer system 1010 includes an input interface 1060 and one or more input devices, such as a keyboard 1062 and a pointing device 1061, for interacting with a computer user and providing information to the processor 1020. The pointing device 1061, for example, may be a mouse, a trackball, or a pointing stick for communicating direction information and command selections to the processor 1020 and for controlling cursor movement on the display 1066. The display 1066 may provide a touch screen interface which allows input to supplement or replace the communication of direction information and command selections by the pointing device 1061.

[0080] The computer system 1010 may perform a portion or all of the processing steps of embodiments of the invention in response to the processors 1020 executing one or more sequences of one or more instructions contained in a memory, such as the system memory 1030. Such instructions may be read into the system memory 1030 from another computer readable medium, such as a hard disk 1041 or a removable media drive 1042. The hard disk 1041 may contain one or more datastores and data files used by embodiments of the present invention. Datastore contents and data files may be encrypted to improve security. The processors 1020 may also be employed in a multi-processing arrangement to execute the one or more sequences of instructions contained in system memory 1030. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions. Thus, embodiments are not limited to any specific combination of hardware circuitry and software.

[0081] As stated above, the computer system 1010 may include at least one computer readable medium or memory for holding instructions programmed according to embodiments of the invention and for containing data structures, tables, records, or other data described herein. The term “computer readable medium” as used herein refers to any medium that participates in providing instructions to the processor 1020 for execution. A computer readable medium may take many forms including, but not limited to, non-volatile media, volatile media, and transmission media. Non-limiting examples of non-volatile media include optical disks, solid state drives, magnetic disks, and magneto-optical disks, such as hard disk 1041 or removable media drive 1042. Non-limiting examples of volatile mediainclude dynamic memory', such as system memory 1030. Non-limiting examples of transmission media include coaxial cables, copper wire, and fiber optics, including the wires that make up the bus 1005. Transmission media may also take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications.

[0082] The computing environment 1000 may further include the computer system 1010 operating in a networked environment using logical connections to one or more remote computers, such as remote computer 1080. Remote computer 1080 may be a personal computer (laptop or desktop), a mobile device, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to computer system 1010. When used in a networking environment, computer system 1010 may include modem 1072 for establishing communications over a network 1071, such as the Internet. Modem 1072 may be connected to bus 1005 via user network interface 1070, or via another appropriate mechanism.

[0083] Network 1071 may be any network or system generally known in the art, including the Internet, an intranet, a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a direct connection or series of connections, a cellular telephone network, or any other network or medium capable of facilitating communication between computer system 1010 and other computers (e.g., remote computer 1080). The network 1071 may be wired, wireless or a combination thereof. Wired connections may be implemented using Ethernet, Universal Serial Bus (USB), RJ-11 or any other wired connection generally known in the art. Wireless connections may be implemented using WiFi, WiMAX, and Bluetooth, infrared, cellular networks, satellite or any other wireless connection methodology generally known in the art. Additionally, several networks may work alone or in communication with each other to facilitate communication in the network 1071.

[0084] The embodiments of the present disclosure may be implemented with any combination of hardware and software. In addition, the embodiments of the present disclosure may be included in an article of manufacture (e.g., one or more computer program products) having, for example, computer-readable, non-transitory media. The media has embodied therein, for instance, computer readable program code for providing and facilitating the mechanisms of the embodiments of the present disclosure. The article of manufacture can be included as part of a computer system or sold separately.

[0085] While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

[0086] An executable application, as used herein, comprises code or machine readable instructions for conditioning the processor to implement predetermined functions, such as those of an operating system, a context data acquisition system or other information processing system, for example, in response to user command or input. An executable procedure is a segment of code or machine readable instruction, sub-routine, or other distinct section of code or portion of an executable application for performing one or more particular processes. These processes may include receiving input data and / or parameters, performing operations on received input data and / or performing functions in response to received input parameters, and providing resulting output data and / or parameters.

[0087] A graphical user interface (GUI), as used herein, comprises one or more display images, generated by a display processor and enabling user interaction with a processor or other device and associated data acquisition and processing functions. The GUI also includes an executable procedure or executable application. The executable procedure or executable application conditions the display processor to generate signals representing the GUI display images. These signals are supplied to a display device which displays the image for viewing by the user. The processor, under control of an executable procedure or executable application, manipulates the GUI display images in response to signals received from the input devices. In this way. the user may interact with the display image using the input devices, enabling user interaction with the processor or other device.

[0088] The functions and process steps herein may be performed automatically or wholly or partially in response to user command. An activity (including a step) performed automatically is performed in response to one or more executable instructions or device operation without user direct initiation of the activity.

[0089] While various illustrative embodiments incorporating the principles of the present teachings have been disclosed, the present teachings are not limited to the disclosed embodiments. Instead, this application is intended to cover any variations, uses, or adaptations of the present teachings and use its general principles. Further, this application isintended to cover such departures from the present disclosure that are within known or customary practice in the art to which these teachings pertain. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.

[0090] In the above detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, similar symbols typical ly identify similar components, unless context dictates otherwise. The illustrative embodiments described in the present disclosure are not meant to be limiting. Other embodiments may be used, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein. It will be readily understood that various features of the present disclosure, as generally described herein, and illustrated in the Figures, can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein.

[0091] Aspects of the present technical solutions are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the technical solutions. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer readable program instructions.

[0092] These computer readable program instructions can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions can also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function / act specified in the flowchart and / or block diagram block or blocks.

[0093] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0094] The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present technical solutions. In this regard, each block in the flowchart or block diagrams can represent a module, segment, or portion of instructions, which includes one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession can, in fact, be executed substantially concurrently, or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustration, and combinations of blocks in the block diagrams and / or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

[0095] A second action can be said to be "in response to” a first action independent of whether the second action results directly or indirectly from the first action. The second action can occur at a substantially later time than the first action and still be in response to the first action. Similarly, the second action can be said to be in response to the first action even if intervening actions take place between the first action and the second action, and even if one or more of the intervening actions directly cause the second action to be performed. For example, a second action can be in response to a first action if the first action sets a flag and a third action later initiates the second action whenever the flag is set.

[0096] With respect to the use of substantially any plural and / or singular terms herein, those having skill in the art can translate from the plural to the singular and / or from the singular to the plural as is appropriate to the context and / or application. The various singular / plural permutations may be expressly set forth herein for sake of clarity.

[0097] It will be understood by those within the art that, in general, terms used herein are generally intended as ’open" terms (for example, the term ‘"including” should be interpreted as ‘"including but not limited to,” the term "‘having” should be interpreted as ‘"having at least,” the term “includes” should be interpreted as “includes but is not limited to,” et cetera). While various compositions, methods, and devices are described in terms of “comprising"’ various components or steps (interpreted as meaning “including, but not limited to”), the compositions, methods, and devices can also “consist essentially of’ or “consist of’ the various components and steps, and such terminology should be interpreted as defining essentially closed-member groups.

[0098] As used in this document, the singular forms “a.” “an.” and “the” include plural references unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art. Nothing in this disclosure is to be construed as an admission that the embodiments described in this disclosure are not entitled to antedate such disclosure by virtue of prior invention.

[0099] In addition, even if a specific number is explicitly recited, those skilled in the art will recognize that such recitation should be interpreted to mean at least the recited number (for example, the bare recitation of “two recitations,” without other modifiers, means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, et cetera” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (for example, “a system having at least one of A, B. and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together, et cetera). In those instances where a convention analogous to “at least one of A, B, or C, et cetera"’ is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (for example, “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together, et cetera). It will be further understood by those within the art that virtually any disjunctive word and / or phrase presenting two or more alternative terms, whether in the description, sample embodiments, or drawings, should be understood to contemplate the possibilities of including one of the terms,either of the terms, or both terms. For example, the phrase "A or B’’ will be understood to include the possibilities of “A” or “B” or "A and B.”

[0100] In addition, where features of the disclosure are described in terms of Markush groups, those skilled in the art will recognize that the disclosure is also thereby described in terms of any individual member or subgroup of members of the Markush group.

[0101] As will be understood by one skilled in the art, for any and all purposes, such as in terms of providing a written description, all ranges disclosed herein also encompass any and all possible subranges and combinations of subranges thereof. Any listed range can be easily recognized as sufficiently describing and enabling the same range being broken down into at least equal halves, thirds, quarters, fifths, tenths, et cetera. As a non-limiting example, each range discussed herein can be readily broken down into a lower third, middle third and upper third, et cetera. As will also be understood by one skilled in the art all language such as "up to." "at least / ’ and the like include the number recited and refer to ranges that can be subsequently broken down into subranges as discussed above. Finally, as will be understood by one skilled in the art, a range includes each individual member. Thus, for example, a group having 1-3 components refers to groups having 1, 2, or 3 components. Similarly, a group having 1-5 components refers to groups having 1, 2, 3, 4. or 5 components, and so forth.NON-LIMITING ILLUSTRATIVE EMBODIMENTS

[0102] The following is a number list of non-limiting illustrative embodiments of the inventive concept disclosed herein:

[0103] Illustrative embodiment 1. A system for assessing a quality of a fluid process performed on a fluid including one of a fluid aspiration and a fluid dispense, the system comprising: a pump; a probe; a connection, wherein a fluid path is formed between the pump and the probe at least in part by the connection; a pressure sensor in fluid communication with the fluid path and configured to sense pressures of the pump during the fluid process, wherein a pressure measurement data comprises the sensed pressures of the pump during the fluid process; and a processor; and a memory comprising instructions that are executed by the processor to cause the processor to: receive, from the pressure sensor, pressure measurement data during the fluid process, wherein the pressure measurement data comprises pressure data and time data, modify, by the processor, the pressure measurement data to conform to acommon domain, identify a datum at a common relevant plot area of the modified pressure measurement data, wherein the common relevant plot area comprises a relevant plot area that can be used to determine fluid process qualities of the fluid performed on a plurality of volumes of fluids that conform to the common domain, calculate, using the datum, a quality value, compare the quality value to a threshold, and determine, by the processor, the qualify of the fluid process based on the comparison.

[0104] Illustrative embodiment 2. The system according to the preceding embodiment, wherein the system further comprises: an analyzer configured to analyze a mixture comprising the fluid when the qualify of the fluid process is satisfactory.

[0105] Illustrative embodiment 3. The system according to one of the preceding embodiments, wherein the instructions further cause the processor to: cause the pump to operate such that a subsequent fluid process is performed in response to determining that the qualify of the fluid process is abnormal.

[0106] Illustrative embodiment 4. The system according to one of the preceding embodiments, wherein the common relevant plot area comprises a subset of the modified pressure measurement data associated with a pump phase.

[0107] Illustrative embodiment 5. The system according to one of the preceding embodiments, wherein the time data comprises one of duration and time stamps.

[0108] Illustrative embodiment 6. The system according to one of the preceding embodiments, wherein modifying the pressure measurement data comprises compressing the pressure measurement data in one of a time domain and a pressure domain.

[0109] Illustrative embodiment 7. The system according to one of the preceding embodiments, wherein modifying the pressure measurement data comprises reducing a number of data points.

[0110] Illustrative embodiment 8. The system according to one of the preceding embodiments, wherein modifying the pressure measurement data comprises: converting the time data to integers; and interpolating new pressure data.[OHl] Illustrative embodiment 9. The system according to one of the preceding embodiments, wherein interpolating new pressure data comprising one of linear interpolation and non-linear interpolation.

[0112] Illustrative embodiment 10. The system according to one of the preceding embodiments, wherein modifying the pressure measurement data comprises: converting the pressure data to integers; and interpolating new time data.

[0113] Illustrative embodiment 11. The system according to one of the preceding embodiments, wherein the quality of the fluid process indicates one or more of an actual aspirated volume is less than an intended aspiration volume, the actual aspirated volume is equal to the intended aspiration volume, presence of air in the actual aspirated volume, and presence of a clog in the actual aspirated volume.

[0114] Illustrative embodiment 12. A method of quality assessment of a fluid process, the method comprising: performing, by a fluid processing system, the fluid process on a fluid, wherein the fluid process comprises one of a fluid aspiration and a fluid dispense; measuring, by the fluid processing system, pressure measurement data during the fluid process, wherein the pressure measurement data comprises pressure data and time data; modifying the pressure measurement data to conform to a common domain; identifying a datum at a common relevant plot area of the modified pressure measurement data, wherein the common relevant plot area comprises a relevant plot area that can be used to determine fluid process qualities of the fluid process performed on a plurality of volumes of fluids that conform to the common domain; calculating, using the datum, a quality value; comparing the quality value to a threshold; and determining the qualify assessment of the fluid process based on the comparison.

[0115] Illustrative embodiment 13. The method according to one of the preceding embodiments, further comprising: analyzing a mixture comprising the fluid in response to determining that the qualify assessment of the fluid process is satisfactory.

[0116] Illustrative embodiment 14. The method according to one of the preceding embodiments, further comprising: aspirating, by the fluid processing system, an additional fluid process in response to determining the qualify assessment of the fluid process is abnormal.

[0117] Illustrative embodiment 15. The method according to one of the preceding embodiments, wherein the common relevant plot area comprises a subset of the modified pressure measurement data associated with a pump phase.

[0118] Illustrative embodiment 16. The method according to one of the preceding embodiments, wherein time comprises one of duration and time stamps.

[0119] Illustrative embodiment 17. The method according to one of the preceding embodiments, wherein modifying the pressure measurement data comprises compressing the pressure measurement data in one of a time domain and a pressure domain.

[0120] Illustrative embodiment 18. The method according to one of the preceding embodiments, wherein modifying the pressure measurement data comprises reducing a number of data points.

[0121] Illustrative embodiment 19. The method according to one of the preceding embodiments, wherein the common domain comprises a common time domain and modifying the pressure measurement data comprises: compressing the time data to the common time domain; and interpolating new pressure data.

[0122] Illustrative embodiment 20. A computer program product embodied in a computer readable storage medium comprising software that when executed by a processor performs a method comprising: receiving, from a pressure sensor, pressure measurement data during a fluid process performed on a fluid, wherein the pressure measurement data comprises pressure data and time data; modify ing, by the processor, the pressure measurement data to conform to a predetermined value; identify ing a datum at a common relevant plot area of the modified pressure measurement data, wherein the common relevant plot area comprises a relevant plot area that can be used to determine fluid process qualities of the fluid performed on a plurality of volumes of fluids that conform to the common domain; calculating, using the datum, a qualify value; comparing the qualify value to a threshold; and determining, by the processor, a qualify of the fluid process based on the comparison.

[0123] Various of the above-disclosed and other features and functions, or alternatives thereof, may be combined into many other different systems or applications. Various presently unforeseen or unanticipated alternatives, modifications, variations or improvementstherein may be subsequently made by those skilled in the art, each of which is also intended to be encompassed by the disclosed embodiments.

Claims

CLAIMSWe claim:1 . A system for assessing a quality of a fluid process performed on a fluid including one of a fluid aspiration and a fluid dispense, the system comprising: a pump; a probe; a connection, wherein a fluid path is formed between the pump and the probe at least in part by the connection; a pressure sensor in fluid communication with the fluid path and configured to sense pressures of the pump during the fluid process, wherein a pressure measurement data comprises the sensed pressures of the pump during the fluid process; and a processor; and a memory comprising instructions that are executed by the processor to cause the processor to: receive, from the pressure sensor, pressure measurement data during the fluid process, wherein the pressure measurement data comprises pressure data and time data, modify, by the processor, the pressure measurement data to conform to a common domain, identify a datum at a common relevant plot area of the modified pressure measurement data, wherein the common relevant plot area comprises a relevant plot area that can be used to determine fluid process qualities of the fluid performed on a plurality of volumes of fluids that conform to the common domain, calculate, using the datum, a quality value. compare the quality' value to a threshold, and determine, by the processor, the quality of the fluid process based on the comparison.

2. The system of claim 1, wherein the system further comprises: an analyzer configured to analyze a mixture comprising the fluid when the quality' of the fluid process is satisfactory.

3. The system of claim 1, wherein the instructions further cause the processor to:cause the pump to operate such that a subsequent fluid process is performed in response to determining that the quality of the fluid process is abnormal.

4. The system of claim 1, wherein the common relevant plot area comprises a subset of the modified pressure measurement data associated with a pump phase.

5. The system of claim 1, wherein the time data comprises one of duration and time stamps.

6. The system of claim 1, wherein modifying the pressure measurement data comprises compressing the pressure measurement data in one of a time domain and a pressure domain.

7. The system of claim 1, wherein modify ing the pressure measurement data comprises reducing a number of data points.

8. The system of claim 1, wherein modifying the pressure measurement data comprises: converting the time data to integers; and interpolating new pressure data.

9. The system of claim 8, wherein interpolating new pressure data comprising one of linear interpolation and non-linear interpolation.

10. The system of claim 1, wherein modifying the pressure measurement data comprises: converting the pressure data to integers; and interpolating new time data.

11. The system of claim 1 , wherein the quality of the fluid process indicates one or more of an actual aspirated volume is less than an intended aspiration volume, the actual aspirated volume is equal to the intended aspiration volume, presence of air in the actual aspirated volume, and presence of a clog in the actual aspirated volume.

12. A method of quality assessment of a fluid process, the method comprising: performing, by a fluid processing system, the fluid process on a fluid, wherein the fluid process comprises one of a fluid aspiration and a fluid dispense; measuring, by the fluid processing system, pressure measurement data during the fluid process, wherein the pressure measurement data comprises pressure data and time data; modifying the pressure measurement data to conform to a common domain;identifying a datum at a common relevant plot area of the modified pressure measurement data, wherein the common relevant plot area comprises a relevant plot area that can be used to determine fluid process qualities of the fluid process performed on a plurality of volumes of fluids that conform to the common domain; calculating, using the datum, a quality value; comparing the quality value to a threshold; and determining the quality assessment of the fluid process based on the comparison.

13. The method of claim 12, further comprising: analyzing a mixture comprising the fluid in response to determining that the quality assessment of the fluid process is satisfactory.

14. The method of claim 12, further comprising: aspirating, by the fluid processing system, an additional fluid process in response to determining the quality assessment of the fluid process is abnormal.

15. The method of claim 12, wherein the common relevant plot area comprises a subset of the modified pressure measurement data associated with a pump phase.

16. The method of claim 12, wherein time comprises one of duration and time stamps.

17. The method of claim 12, wherein modifying the pressure measurement data comprises compressing the pressure measurement data in one of a time domain and a pressure domain.

18. The method of claim 12, wherein modifying the pressure measurement data comprises reducing a number of data points.

19. The method of claim 12, wherein the common domain comprises a common time domain and modifying the pressure measurement data comprises: compressing the time data to the common time domain; and interpolating new pressure data.

20. A computer program product embodied in a computer readable storage medium comprising software that when executed by a processor performs a method comprising:receiving, from a pressure sensor, pressure measurement data during a fluid process performed on a fluid, wherein the pressure measurement data comprises pressure data and time data; modifying, by the processor, the pressure measurement data to conform to a predetermined value; identifying a datum at a common relevant plot area of the modified pressure measurement data, wherein the common relevant plot area comprises a relevant plot area that can be used to determine fluid process qualities of the fluid performed on a plurality of volumes of fluids that conform to the common domain; calculating, using the datum, a quality value; comparing the quality value to a threshold; and determining, by the processor, a quality of the fluid process based on the comparison.

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