1. A computer-implemented method, comprising:
storing a baseline data point in a memory wherein the baseline data point is representative of a first point on a glucose control grid;
storing an evaluation data point in the memory wherein the evaluation data point is representative of a second point on the glucose control grid;
computing a magnitude of a vector that would extend between the baseline data point and the evaluation data point if plotted on the glucose control grid;
defining a gradient function over an area of the glucose control grid and determining gradient contour lines around the baseline data point and the evaluation data point;
computing a component of the magnitude of the vector between the baseline data point and the evaluation data point that is parallel to a contour line of the defined gradient function;
comparing the component of the magnitude of the vector to a predefined threshold value; and
displaying, on a system display, an indication that a sensor fault has been detected if the component of the magnitude of the vector is greater than a first predefined threshold value.
2. The computer-implemented method of claim 1, wherein the baseline data point is determined based on using a baseline median glucose value and a baseline glucose variability value as coordinates for the baseline data point, and further
wherein the baseline median glucose value and the baseline glucose variability value are computed by a processor based on a first dataset of glucose values received from a first data communication from sensor electronics operatively coupled to a transcutaneously positioned glucose sensor.
3. The computer-implemented method of claim 2, wherein the evaluation data point is determined based on using an evaluation median glucose value and an evaluation glucose variability value as coordinates for the evaluation data point, and further
wherein the evaluation median glucose value and the evaluation glucose variability value are computed using the processor based on a second dataset of glucose values received from a second data communication from the sensor electronics operatively coupled to the transcutaneously positioned glucose sensor, where the second dataset of glucose values includes glucose values that are not in the first dataset of glucose values.
4. The computer-implemented method of claim 1, further comprising displaying, on the system display, the indication that the sensor fault has not been detected if the component of the magnitude of the vector is less than the first predefined threshold value.
5. The computer-implemented method of claim 1, wherein displaying, on the system display, the indication that the sensor fault has been detected further includes prompting a user to indicate whether to maintain use of a glucose sensor.
6. The computer-implemented method of claim 5, wherein displaying, on the system display, the indication that the sensor fault has been detected further includes requesting a reference glucose measurement for validation.
7. The computer-implemented method of claim 6, wherein displaying, on the system display, the indication that the sensor fault has been detected further includes comparing sensor output to the reference glucose measurement relative to a second predefined threshold value.
8. The computer-implemented method of claim 6, wherein displaying, on the system display, the indication that the sensor fault has been detected further includes displaying, on the system display, an indication to remove the glucose sensor if the component of the magnitude of the vector is greater than a second predefined threshold value.
9. A system for determining analyte concentration in blood based on analyte concentration measured in interstitial fluid, the system comprising:
a processor; and
a memory coupled to the processor, the memory storing processor executable instructions to:
store a baseline data point in the memory wherein the baseline data point is representative of a first point on an analyte control grid;
store an evaluation data point in the memory wherein the evaluation data point is representative of a second point on the analyte control grid;
compute a magnitude of a vector that would extend between the baseline data point and the evaluation data point if plotted on the analyte control grid;
define a gradient function over an area of the analyte control grid and determine gradient contour lines around the baseline data point and the evaluation data point;
compute a component of the magnitude of the vector between the baseline data point and the evaluation data point that is parallel to a contour line of the defined gradient function;
compare the component of the magnitude of the vector to a predefined threshold value; and
display, on a system display, an indication that a sensor fault has been detected if the component of the magnitude of the vector is greater than a first predefined threshold value.
10. The system of claim 9, wherein the memory is further configured to store processor executable instructions to:
receive a first dataset of analyte values from sensor electronics operatively coupled to a transcutaneously positioned analyte sensor;
compute a baseline median analyte value based on the first dataset of analyte values;
compute a baseline analyte variability value based on the first dataset of analyte values; and
determine the baseline data point based on using the baseline median analyte value and the baseline analyte variability value as coordinates for the baseline data point on the analyte control grid.
11. The system of claim 10, wherein the memory is further configured to store processor executable instructions to:
receive a second dataset of analyte values from the sensor electronics where the second dataset of analyte values includes analyte values that are not in the first dataset of analyte values;
compute an evaluation median analyte value based on the second dataset of analyte values;
compute an evaluation analyte variability value based on the second dataset of analyte values; and
determine the evaluation data point based on using the evaluation median analyte value and the evaluation analyte variability value as coordinates for the evaluation data point on the analyte control grid.
12. The system of claim 9, wherein the memory is further configured to store processor executable instructions to display, on the system display, the indication that the sensor fault has not been detected if the component of the magnitude of the vector is less than the first predefined threshold value.
13. The system of claim 9, wherein the memory is further configured to store processor executable instructions to display, on the system display, the indication that the sensor fault has been detected further includes an instruction to prompt a user to indicate whether to maintain use of a sensor.
14. The system of claim 13, wherein the instruction to display, on the system display, the indication that the sensor fault has been detected further includes an instruction to request a reference glucose measurement for validation.
15. The system of claim 14, wherein the instruction to display, on the system display, the indication that the sensor fault has been detected further includes an instruction to compare sensor output to the reference glucose measurement relative to a second predefined threshold value.
16. The system of claim 15, wherein the instruction to display, on the system display, the indication that the sensor fault has been detected further includes an instruction to display, on the system display, an indication to remove the sensor if the component of the magnitude of the vector is greater than the second predefined threshold value.
17. A computer-implemented method, comprising:
storing an evaluation data point representative of a first point on a glucose control grid;
storing a baseline data point representative of a second point on the glucose control grid;
computing a magnitude of a vector that extends between the baseline data point and the evaluation data point;
defining a gradient function over an area of the glucose control grid including determining at least one gradient contour line around the baseline data point and the evaluation data point;
computing a component of the magnitude of the vector between the baseline data point and the evaluation data point that is parallel to a contour line of the defined gradient function;
comparing the component of the magnitude of the vector to a predefined threshold value; and
displaying, on a system display, an indication that an early signal attenuation (ESA) fault has been detected if the component of the magnitude of the vector is greater than a first predefined threshold value.
18. The computer-implemented method of claim 17, further comprising:
receiving during an early wear period, a first dataset of glucose values from sensor electronics operatively coupled to a transcutaneously positioned glucose sensor;
computing an evaluation median glucose value based on the first dataset of glucose values;
computing an evaluation glucose variability value based on the first dataset of glucose values; and
determining the evaluation data point based on using the evaluation median glucose value and the evaluation glucose variability value as coordinates for the evaluation data point on the glucose control grid.
19. The computer-implemented method of claim 18, further comprising:
receiving after the early wear period a second dataset of glucose values from the sensor electronics where the second dataset of glucose values does not include glucose values that are also in the first dataset of glucose values;
computing a baseline median glucose value based on the second dataset of glucose values;
computing a baseline glucose variability value based on the second dataset of glucose values; and
determining the baseline data point based on using the baseline median glucose value and the baseline glucose variability value as coordinates for the baseline data point on the glucose control grid.
20. The computer-implemented method of claim 17, further comprising displaying, on the system display, the indication that the early signal attenuation (ESA) fault has not been detected if the component of the magnitude of the vector is less than the first predefined threshold value.
21. The computer-implemented method of claim 17, wherein displaying, on the system display, the indication that the early signal attenuation (ESA) fault has been detected further includes prompting a user whether to maintain use of a glucose sensor.
22. The computer-implemented method of claim 21, wherein displaying, on the system display, the indication that the early signal attenuation (ESA) fault has been detected further includes requesting a reference glucose measurement for validation.
23. The computer-implemented method of claim 22, wherein displaying, on the system display, the indication that the early signal attenuation (ESA) fault has been detected further includes comparing sensor output to the reference glucose measurement relative to a second predefined threshold value.
24. The computer-implemented method of claim 23, wherein displaying, on the system display, the indication that the early signal attenuation (ESA) fault has been detected further includes displaying, on the system display, an indication that a first dataset of glucose values are invalid.
25. The computer-implemented method of claim 17, further comprising storing the evaluation data point as the baseline data point if no fault is detected for the evaluation data point.
26. The computer-implemented method of claim 25, further comprising comparing the evaluation data point against multiple baseline data points.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. In a color management system including a processor, a user interface, and memory storing color profiles with mathematical transforms to perform a color transformation of an image, a method of image editing including the steps of:
providing natural language commands at the user interface for image editing,
converting the natural language commands to mathematical transforms and storing the transforms in a color profile for color transformation, and
storing the natural language commands in the same color profile with the corresponding mathematical transforms.
2. The method of claim 1 wherein the natural language commands are stored in a tag associated with the color profile including the steps of:
reading the private tag, and
responsive to reading the private tag, displaying the natural language based commands in a user interface.
3. The method of claim 1 wherein the step of providing natural language commands at the user interface enables a user to determine the effect of a color profile on an image without processing the image.
4. The method of claim 2 further comprising the steps of selectively editing the natural language commands, and storing the edited natural language commands in a tag of a color profile.
5. The method of claim 4 further comprising the steps of:
using the edited natural language commands to create corresponding mathematical transforms, and
storing the mathematical transforms within the color profile.
6. In a color management imaging system with memory and a user interface having a color profile to perform a color transformation of an image, a method of editing an image including the steps of:
providing the color profile with a private tag, the private tag capable of being interpreted by an exclusive color management module, the private tag including natural language commands,
loading a profile into an exclusive color management module,
reading the private tag,
editing the natural language commands within the private tag to provide an edited set of natural language commands, and
storing the edited natural language commands in a private tag of a color profile.
7. The method of claim 6 including the step of deriving a set of mathematical transforms based from said edited natural language based commands and including these in the private tag of the profile along with the adjusted set of natural language commands.
8. In a natural language based color management system including color profiles in memory and a user interface, a method of providing editing of the color profiles including the steps of:
storing a first set of natural language commands in a first color profile for providing a first color modification of a document,
storing mathematical transforms of the first set of natural language commands in the color profile,
accessing the color profile to display the first set of natural language commands, and
selectively changing the first set of natural language commands to a second set of natural language commands.
9. The method of claim 8 wherein the step of accessing the profile includes the step of displaying the first sequence of natural language commands for selective editing.
10. The method of claim 9 including the step of providing a first tag to the profile wherein the tag restricts access of the natural language commands to a specific natural language based system.
11. The method of claim 8 including the steps of changing the first sequence of natural language commands to a second sequence of natural language commands and storing the second sequence of natural language commands in a new profile.
12. The method of claim 8 including the steps of providing new mathematical transforms in relation to the second set of natural language commands and storing the new mathematical transforms in the second color profile.
13. In a natural language based color editing system including user interface and memory having a plurality of color editing profiles, each of the profiles including a tag, the tag providing access to a natural language command sequence, a method of editing the profiles including the steps of:
loading color editing profiles into the user interface,
reading the tags of the color editing profiles to display the natural language command sequences,
providing a composite sequence from the displayed natural language command sequences, and
saving the composite sequence in a new profile.
14. The method of claim 13 further comprising selectively modifying the composite sequence.
15. The method of claim 13 including the step of providing a private tag for the composite sequence, the private tag identifying an exclusive color management module.
16. The method of claim 13 wherein the step of providing a composite sequence includes the options of combining selected natural language command sequences and portions of natural language command sequences.
17. In an imaging system having a user interface, method of providing a natural language color editing system including the steps of:
providing a set of natural language commands,
relating each of the natural language commands with a mathematical transform in color space,
storing the natural language commands in a tag within a profile,
accessing the tag on the user interface to display the natural language commands, and
modifying selected natural language commands to provide a second set of natural language commands.
18. The method of claim 17 including the steps of providing a tag to contain the second set of natural language commands and storing the tag in a profile.