Analysis and Design of an Optical Biosensor Using …
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the quality factor value. Based on the material and waveguide properties, we get the
different structures, designs, and results.
2 Mathematical Modeling
The main aspect of this paper is mathematical modeling using sensitivity. This factor
has to be considered both with respect to instrument as well as with respect refractive
index of the sample being placed in an optical sensor. The sensitivity is nothing but
a small change in an output to the input being considered or measured. Sensitivity
[10] is very closely related to resolution [3]. It is always a good practice to design
an instrument with high sensitivity and low specificity. Both sensitivity as well as
specificity are applied so as to find whether a person has a disease or not by checking
the factor true positive and false negative.
It is calculated as follows:
Sensitivity = (TP)/(TP + FN)
Also Sensitivity = (TN)/(TP + TN)
If specificity value becomes lesser, then it means a person may said to have a
disease means he may be prone to disease. Positive predictive value (PPV) [8] shows
that a person is said to have a disease. If negative predictive value occurs, then the
person is not prone to have a disease. This means that we have to check a positive or
a negative outcome [5] from the test being carried out.
In the same way, we can calculate specificity by using the following equation
Specificity = (TN)/(TN + FP)
From this even, we can predict positive predictive value (PPV) by using the
following equation from Table 1.
Positive Predictive Value = (TP)/(TP + FP)
Negative predictive value (NPV) is calculated by using the equation given below:
Negative Predictive Value = (TN)/(TN + FN)
Table 1 Determination of sensitivity
Disease
No disease
Test
True positive (TP)
False positive (FP)
Test
False negative (FN)
True negative (TN)
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the quality factor value. Based on the material and waveguide properties, we get the
different structures, designs, and results.
2 Mathematical Modeling
The main aspect of this paper is mathematical modeling using sensitivity. This factor
has to be considered both with respect to instrument as well as with respect refractive
index of the sample being placed in an optical sensor. The sensitivity is nothing but
a small change in an output to the input being considered or measured. Sensitivity
[10] is very closely related to resolution [3]. It is always a good practice to design
an instrument with high sensitivity and low specificity. Both sensitivity as well as
specificity are applied so as to find whether a person has a disease or not by checking
the factor true positive and false negative.
It is calculated as follows:
Sensitivity = (TP)/(TP + FN)
Also Sensitivity = (TN)/(TP + TN)
If specificity value becomes lesser, then it means a person may said to have a
disease means he may be prone to disease. Positive predictive value (PPV) [8] shows
that a person is said to have a disease. If negative predictive value occurs, then the
person is not prone to have a disease. This means that we have to check a positive or
a negative outcome [5] from the test being carried out.
In the same way, we can calculate specificity by using the following equation
Specificity = (TN)/(TN + FP)
From this even, we can predict positive predictive value (PPV) by using the
following equation from Table 1.
Positive Predictive Value = (TP)/(TP + FP)
Negative predictive value (NPV) is calculated by using the equation given below:
Negative Predictive Value = (TN)/(TN + FN)
Table 1 Determination of sensitivity
Disease
No disease
Test
True positive (TP)
False positive (FP)
Test
False negative (FN)
True negative (TN)