System and method of increasing sample throughput
First Claim
1. A system for increasing sample throughput, comprising:
- a sensor configured to generate data signals in response to being exposed to an analyte within a sample; and
a processor configured to record data points associated with the data signals, select a series of data points corresponding to a portion of a kinetic region time range from the recorded data points, determine a curve fitting equation that fits the series of data as a logarithmic scale of time wherein the curve fitting equation is of the form s(t)=a*(log(t))^2−
2 aV(log(t))+c, and V is a log of a time which extremum occurs, wherein t represents time and a and c are fit parameters for a second order polynomial, extrapolate an end point response of the sensor using the curve fitting equation, and calculate, using the extrapolated end point response, a value corresponding to the analyte, thereby increasing said sample throughput, wherein the processor is configured to determine and improve usefulness of the curve fitting equation corresponding to the analyte by removing numerically distant data points, thereby constituting an analyzed set of data points, and determining another curve fitting equation that fits the analyzed series of data points as a logarithmic scale of time.
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Abstract
Technologies for increasing sample throughput by predicting the end point response time of a sensor for the analysis of an analyte in a sample are disclosed. In one aspect, a system includes a sensor that generates data signals associated with the measurement of an analyte within the sample. A processor records appropriate data points corresponding to the signals, converts them to a logarithmic function of time scale, and plots the converted data points. The processor then determines a curve that fits the plotted data points and determines a curve fitting equation for the curve. Once the equation is determined, the processor extrapolates an end point response of the sensor using the equation. A value, such as analyte concentration, is then calculated using the extrapolated end point response.
34 Citations
10 Claims
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1. A system for increasing sample throughput, comprising:
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a sensor configured to generate data signals in response to being exposed to an analyte within a sample; and a processor configured to record data points associated with the data signals, select a series of data points corresponding to a portion of a kinetic region time range from the recorded data points, determine a curve fitting equation that fits the series of data as a logarithmic scale of time wherein the curve fitting equation is of the form s(t)=a*(log(t))^2−
2 aV(log(t))+c, and V is a log of a time which extremum occurs, wherein t represents time and a and c are fit parameters for a second order polynomial, extrapolate an end point response of the sensor using the curve fitting equation, and calculate, using the extrapolated end point response, a value corresponding to the analyte, thereby increasing said sample throughput, wherein the processor is configured to determine and improve usefulness of the curve fitting equation corresponding to the analyte by removing numerically distant data points, thereby constituting an analyzed set of data points, and determining another curve fitting equation that fits the analyzed series of data points as a logarithmic scale of time. - View Dependent Claims (2, 3, 4, 5)
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6. A system for analyzing samples, comprising:
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a sensor configured to generate data signals in response to being exposed to an analyte within a sample; and a processor configured to; record data points associated with the data signals, select a series of data points corresponding to a portion of a kinetic region time range from the recorded data points, determine a curve fitting equation that fits the series of data points as a logarithmic scale of time, wherein the curve fitting equation is of the form s(t)=a*(log(t))^2−
2 aV(log(t))+c, and V is a log of a time which extremum occurs, wherein t represents time and a and c are fit parameters for a second order polynomial; anddetermine and improve usefulness of the curve fitting equation corresponding to the analyte by removing numerically distant data points, thereby constituting an analyzed set of data points, and determining another curve fitting equation that fits the analyzed series of data points as a logarithmic scale of time, thereby increasing sample throughput. - View Dependent Claims (7, 8, 9, 10)
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Specification