融合多域特征的VAE模型在肌肉疲劳分析中的应用

董博,吕东澔,喻大华,杜晓炜

VAE model combined with multi-domain feature for muscle fatigue analysis

Bo DONG,Donghao LV,Dahua YU,Xiaowei DU

表 2 各受试者肌肉疲劳的量化结果

Tab.2 Quantification result of muscle fatigue in each subject

受试者 VAE SSR-VAE MSE r $\mu_{\mathrm{d}} $ $ {\sigma _{\mathrm{d}}}$ p MSE r $\mu_{\mathrm{d}} $ $ {\sigma _{\mathrm{d}}} $ p 1 15.0840 0.9475 1.0687 0.3410 < 0.001 0.3424 0.9989 1.2364 0.3727 < 0.001 2 2.5907 0.9319 1.0627 0.3362 < 0.001 0.0682 0.9987 1.2166 0.3761 < 0.001 3 4.9414 0.9211 1.0938 0.3937 < 0.001 0.1028 0.9991 1.2209 0.4352 < 0.001 4 1.3268 0.9615 1.0940 0.3390 < 0.001 0.0414 0.9988 1.2056 0.3878 < 0.001 5 3.3584 0.9310 1.1223 0.3826 < 0.001 0.0800 0.9986 1.2562 0.4256 < 0.001 6 9.5695 0.9162 1.1540 0.3985 < 0.001 0.2311 0.9985 1.2150 0.4208 < 0.001 7 22.821 0.9301 1.1141 0.4305 < 0.001 0.6580 0.9986 1.1668 0.4583 < 0.001 8 7.9533 0.9458 1.0805 0.3609 < 0.001 0.2970 0.9986 1.2341 0.4084 < 0.001 9 5.0211 0.9219 1.1581 0.4060 < 0.001 0.2289 0.9976 1.2788 0.4470 < 0.001 10 3.4747 0.9327 1.0859 0.3461 < 0.001 0.1174 0.9983 1.2380 0.4002 < 0.001 11 3.2592 0.9672 0.9895 0.3272 < 0.001 0.1318 0.9989 1.2168 0.4249 < 0.001 12 12.829 0.9398 1.1946 0.4034 < 0.001 3.6246 0.9900 1.3562 0.4462 < 0.001 13 4.7678 0.9582 1.1174 0.3610 < 0.001 0.1431 0.9989 1.2591 0.4188 < 0.001 14 2.2649 0.9559 1.0921 0.3773 < 0.001 0.0425 0.9990 1.2124 0.4109 < 0.001 15 3.0766 0.9490 1.0290 0.3372 < 0.001 0.0955 0.9987 1.1403 0.4050 < 0.001 mean 6.8227 0.9407 1.0970 0.3694 < 0.001 0.4136 0.9981 1.2300 0.4158 < 0.001 std 5.9698 0.0158 0.0510 0.0319 — 0.9024 0.0023 0.0489 0.0253 —