Research Article
An Efficient Automatic Gait Anomaly Detection Method Based on Semisupervised Clustering
Table 5
The CPU timing of the test case I by the AGD-SSC, AGD-SSC-NBC, IF, and LOF.
| Seq no. | AGD-SSC mean (st. dev.) | AGD-SSC-NBC mean (st. dev.) | IF mean (st. dev.) | LOF mean (st. dev.) |
| Seq. 1 | 2.0163 (0.0356) | 2.2827 (0.0387) | 11.1441 (0.0641) | 0.9372 (0.0103) | Seq. 2 | 1.2471 (0.0282) | 3.1222 (0.0534) | 11.1497 (0.0683) | 0.9472 (0.0283) | Seq. 3 | 1.3787 (0.0307) | 2.4007 (0.0165) | 11.1502 (0.0742) | 0.9482 (0.0293) | Seq. 4 | 1.8787 (0.00353) | 2.2930 (0.0243) | 11.1385 (0.0365) | 0.9398 (0.0079) | Seq. 5 | 1.3027 (0.0282) | 2.3197 (0.0859) | 11.1385 (0.0150) | 0.9437 (0.0127) | Seq. 6 | 1.2168 (0.0328) | 2.3275 (0.0376) | 11.2123 (0.2133) | 0.9451 (0.0282) | Seq. 7 | 1.5393 (0.0502) | 2.3225 (0.0255) | 11.1698 (0.0941) | 0.9481 (0.0285) | Seq. 8 | 1.2986 (0.0387) | 2.0971 (0.0265) | 11.1423 (0.0682) | 0.9442 (0.234) | Seq. 9 | 1.4610 (0.0360) | 2.2503 (0.0253) | 11.1374 (0.0165) | 0.9509 (0.0376) | Seq. 10 | 1.4347 (0.0544) | 2.2272 (0.0250) | 11.2059 (0.2808) | 0.9484 (0.0359) |
| Average | 1.4774 | 2.364 | 11.1589 | 0.9453 |
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