Research Article
A New Approach to Noninvasive-Prolonged Fatigue Identification Based on Surface EMG Time-Frequency and Wavelet Features
Table 4
Statistical analysis on the four muscle features.
| | Features (mean ± SD) | | Muscles | ΔFmean | ΔFmed | ΔMAV | ΔRMS | Δ WIRM1551 | Δ WIRM1M51 | Δ WIRM1522 | Δ WIRE51 | ΔWIRW51 |
| | Biceps femoris | NF | −2.04 (10.4) | −0.45 (9.74) | −0.00034 (0.003) | −0.00043 (0.004) | 0.80 (2.36) | 0.75 (2.33) | 0.09 (0.82) | 0.24 (0.78) | 0.22 (0.80) | | PF | 7.55 (8.23) | 5.11 (6.46) | −0.00033 (0.0028) | −0.00049 (0.0037) | −0.70 (2.69) | −0.80 (2.30) | −0.22 (0.85) | −0.27 (0.92) | −0.34 (0.98) |
| | Rectus femoris | NF | −4.67 (9.91) | −2.37 (6.67) | −0.00061 (0.0018) | −0.00066 (0.0024) | 1.02 (2.60) | 1.03 (2.64) | 0.36 (1.11) | 0.10 (1.02) | 0.10 (1.13) | | PF | 5.77 (10.22) | 6.43 (8.56) | 0.001388 (0.0020) | 0.0017 (0.0024) | −2.29 (2.51) | −2.36 (2.61) | −0.75 (0.76) | −0.66 (1.01) | −0.74 (1.14) |
| | Vastus lateralis | NF | −2.07 (8.45) | −2.15 (9.00) | −0.00038 (0.0022) | −0.00054 (0.0029) | 0.40 (2.74) | 0.66 (2.66) | 0.17 (0.94) | 0.13 (0.87) | 0.11 (0.88) | | PF | 6.34 (7.85) | 4.64 (7.58) | −0.00052 (0.0024) | −0.00064 (0.0031) | −0.59 (2.38) | −0.60 (2.41) | −0.21 (0.83) | −0.26 (0.85) | −0.25 (0.92) |
| | Vastus medialis | NF | −0.75 (7.59) | −0.30 (7.42) | 0.0001 (0.002) | 0.0001 (0.003) | 0.58 (2.74) | 0.54 (3.17) | 0.24 (1.02) | 0.12 (0.96) | 0.11 (0.95) | | PF | 4.06 (4.81) | 4.28 (5.77) | 0.00022 (0.0024) | 0.000246 (0.0032) | −0.330 (1.75) | −0.38 (1.73) | −0.10 (0.96) | −0.02 (0.66) | −0.01 (0.58) |
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The differences differ significantly tested using the t-test at < 0.05. |
