Biomedical Engineering Reference
In-Depth Information
In this study, for the evaluation of the proposed classifier of abnormality, we define
all the breathing patterns that are smaller than half the size of the average
breathing amplitude as irregular patterns, shown with dotted lines in Fig. 6.4 .
Figure 6.9 shows the frequency distribution of the number of irregular patterns.
The numbers of irregular patterns are distributed with a minimum number of 0 and
a maximum number of 3,737 of irregular patterns. The average number of irregular
patterns for the breathing datasets is 188. Accordingly, we can calculate the true
positive/negative ranges
R T i R TN
and the ratio c ðÞ for the patients after sum-
i
marizing all the irregular patterns.
Figure 6.10 shows the frequency distribution of the ratio c ðÞ . Here c i i is the
ratio of the true negative range (R i TN ) to the period of observation (T i ), thus it is
dimensionless. The ratio c ðÞ for each breathing dataset is distributed from 0.02 to
1 with 0.92 as the average ratio value. In Fig. 6.10 we can see that the frequency
number of the regular breathing patterns is much higher than that of the irregular
breathing patterns in the given datasets. But we can also see that it is not a simple
binary classification to decide which breathing patterns are regular or irregular
because the frequency distribution of the ratio is analog. We define the vague
breathing patterns with the ratio 0.8-0.87 as the gray-level breathing pattern. We
have shown the regular/irregular gray-level breathing patterns among the entire
dataset in the following figures.
Figure 6.11 shows regular breathing patterns in the given datasets. There exist
several irregular points depicted with green spots. But most of breathing cycles
have the regular patterns of breathing curve. Note that the regular breathing pat-
terns have a higher ratio c ðÞ in comparison to the irregular breathing patterns.
45
40
Min of Σ j ψ ij = 0
Max of Σ j ψ ij = 3737
Mean of Σ j ψ ij = 188
35
30
25
20
15
10
5
0
0
500
1000
1500
2000
2500
3000
3500
Number of Irregular Patterns ( Σ j ψ ij )
. The numbers of
irregular patterns of each breathing dataset are distributed from 0 to 3,737 with 188 as the average
number
Fig. 6.9 Frequency distribution of the number of irregular patterns P j w ij
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