Biomedical Engineering Reference
In-Depth Information
Table 3.4
Comparison of overall velocity error averaged among eight channels
Datasets
No feedback/forward (cm/s)
Feedback/forward (cm/s)
Chest_1
0.415
0.292
Chest_2
0.335
0.211
Chest_3
0.605
0.514
Head_1
1.527
1.168
Head_2
1.386
1.014
Head_3
1.517
1.201
Upper Body_1
2.012
1.550
Upper Body_2
3.162
2.572
Upper Body_3
3.999
3.404
Fig. 3.18 Prediction
overshoot comparison
between IMME and MC-
IMME, The prediction
overshoot error can be
improved with MC-IMME
32
IMME
MC-IMME
Measurement
Upper Bound
Lower Bound
31.5
31
30.5
30
29.5
29
28.5
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.1
Data Time Index (sec)
The prediction overshoot error can be improved with MC-IMME.
Figure 3.18 shows the prediction overshoot comparison between IMME and
MC-IMME. We can notice that the prediction overshoot error with distributed
sensory data was improved in the average of 10.84 % with slow motion, 12.43 %
with moderate motion, and 34.66 % with violent motion. Moreover, the total error
of MC-IMME was decreased by 23.63 % in comparison with that of IMME.
Table 3.5 shows the comparison of overshoot dataset sample numbers between
IMME and MC-IMME, where the second column represents the average number
of overshoot dataset samples listed in Table 3.2 . The overall improvement in the
benign motion is around 10 %, whereas the overall improvement in the aggressive
motion is over 20 %. That means distributed sensory data can reduce the pre-
diction estimate error at the beginning of target tracking. We may expect this
prediction accuracy to decrease for different datasets (e.g., including head and
chest motions) due to the lack of interactive relationships. For our experimental
tests, however, we have focused on the human body motion including head and
chest. That means our experimental results can be generalized to the upper body.
3.5.6 Computational Time
Regarding CPU experimental time, we have evaluated the overall performance of
average CPU time used for the datasets listed in Table 3.2 . We have collected the
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