Table 1 |
|||||
|
Performance of the proposed mouth opening detection algorithm |
|||||
|
Participant |
Video length (sec) |
Total Video frames |
Actual # of mouth openings |
Sensitivity |
Specificity |
|
|
|||||
|
1 |
256 |
7662 |
50 |
88% |
100% |
|
2 |
252 |
7546 |
50 |
96% |
100% |
|
3 |
254 |
7621 |
50 |
96% |
100% |
|
4 |
252 |
7481 |
50 |
98% |
100% |
|
5 |
244 |
7424 |
50 |
88% |
99% |
|
6 |
243 |
7594 |
50 |
92% |
98% |
|
7 |
245 |
7664 |
50 |
94% |
99% |
|
8 |
243 |
7613 |
50 |
80% |
100% |
|
9* |
153 |
4592 |
30 |
93% |
99% |
|
10* |
272 |
8160 |
15 |
60% |
99% |
|
|
|||||
|
*Participant with severe disability. |
|||||
|
Memarian et al. Journal of NeuroEngineering and Rehabilitation 2009 6:11 doi:10.1186/1743-0003-6-11 |
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