Abstract: An approach for detecting a transient error in a body fluid sample based on the shape of a response curve of a sensor is provided. The response curve is represented by an equation including at least one coefficient describing a curvature or slope of the response curve. The approach includes comparing the coefficient to a range of coefficients which includes coefficients of response curves corresponding to known analyte concentrations. The approach further includes detecting a transient error based on the comparison. In some examples of the approach, the comparison and detection are performed by a processing transient error detector executing computer readable instructions embodied in a non-transitory computer-readable medium. Other examples of the approach determine a concentration of the analyte based on the equation. Advantageously, various examples of the approach can expedite detection of transient errors at the time of measuring and before reporting sample result.

Abstract: An approach for detecting a transient error in a body fluid sample based on the shape of a response curve of a sensor is provided. The response curve is represented by an equation including at least one coefficient describing a curvature or slope of the response curve. The approach includes comparing the coefficient to a range of coefficients which includes coefficients of response curves corresponding to known analyte concentrations. The approach further includes detecting a transient error based on the comparison. In some examples of the approach, the comparison and detection are performed by a processing transient error detector executing computer readable instructions embodied in a non-transitory computer-readable medium. Other examples of the approach determine a concentration of the analyte based on the equation. Advantageously, various examples of the approach can expedite detection of transient errors at the time of measuring and before reporting sample result.

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.

Abstract: An approach for detecting a transient error in a body fluid sample based on the shape of a response curve of a sensor is provided. The response curve is represented by an equation including at least one coefficient describing a curvature or slope of the response curve. The approach includes comparing the coefficient to a range of coefficients which includes coefficients of response curves corresponding to known analyte concentrations. The approach further includes detecting a transient error based on the comparison. In some examples of the approach, the comparison and detection are performed by a processing transient error detector executing computer readable instructions embodied in a non-transitory computer-readable medium. Other examples of the approach determine a concentration of the analyte based on the equation. Advantageously, various examples of the approach can expedite detection of transient errors at the time of measuring and before reporting sample result.

Abstract: An approach for detecting a transient error in a body fluid sample based on the shape of a response curve of a sensor is provided. The response curve is represented by an equation including at least one coefficient describing a curvature or slope of the response curve. The approach includes comparing the coefficient to a range of coefficients which includes coefficients of response curves corresponding to known analyte concentrations. The approach further includes detecting a transient error based on the comparison. In some examples of the approach, the comparison and detection are performed by a processing transient error detector executing computer readable instructions embodied in a non-transitory computer-readable medium. Other examples of the approach determine a concentration of the analyte based on the equation. Advantageously, various examples of the approach can expedite detection of transient errors at the time of measuring and before reporting sample result.

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.

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.

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.

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.

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.

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.

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.