Table 2.
Examples of feature extraction methods employed in myoelectric control.
| Ref | Feature Extraction Method | Name | Ref | Feature Extraction Method | Name |
|---|---|---|---|---|---|
| [52] | Amplitude of the First Burst | AFB | [53,62] | Sample Entropy | SampEn |
| [63,64,65] | Difference Absolute Mean Value | DAMV | [53,62] | Approximate Entropy | ApEn |
| [63,65] | Difference Absolute Standard Deviation Value | DASDV | [51,52] | Willison’s Amplitude | WAMP |
| [51,52,63] | Difference Log Detector | DLD | [52,53] | Myopulse Percentage Rate | MYOP |
| [52,63] | Difference Temporal Moment | DTM | [53,66] | Box-Counting Fractal Dimension | BC |
| [51,52,63] | Difference Variance Value | DVARV | [67,68] | Higuchi Fractal Dimension | HG |
| [51,52,63] | Difference v-Order | DV | [53,69] | Katz Fractal Dimension | KATZ |
| [70] | Ł-Score | LS | [71] | Integral Square Descriptor | ISD |
| [71] | Coefficient of Regularization | COR | [71] | Modified Absolute Square Sum | MDIFF |
| [71] | Mean Difference Derivative | MDIFF | [72] | Activity | ACT |
| [72] | Mobility | MOB | [72] | Complexity | COMP |
| [51,52,64] | Integral of Electromyogram | IEMG | [53,68] | Maximum Fractal Length | MFL |
| [51,52,63] | Log Detector | LD | [51,63,64] | Autoregressive Coefficients | AR |
| [63,73] | Second-Order Moment | M2 | [63,64] | Cepstral Coefficients | CC |
| [74] | Mean Absolute Value First Difference | MAVFS | [70] | Mean Squared Ratio | MSR |
| [52,75] | Modified Mean Absolute Value 1 | MMAV1 | [51,63,64] | Difference Autoregressive Coefficient | DAR |
| [52,75] | Modified Mean Absolute Value 2 | MMAV2 | [63,64] | Difference Cepstral Coeffients | DCC |
| [51,58,76] | Mean Absolute Value | MAV | [67,77] | Detrend Fluctuation Analysis | DFA |
| [52,53] | Maximum | MAX | [52,78] | Power Spectrum Ratio | PSR |
| [52,79] | Multiple Hamming Windows | MHW | [80,81] | Signal to Noise Ratio | SNR |
| [52,53,79] | Mean Power | MNP | [82,83] | Critical Exponent | CE |
| [52,79] | Multiple Trapezoidal Windows | MTW | [80,81] | Drop in Power Density Ratio | DPR |
| [52,76] | Root Mean Square | RMS | [51,52] | Histogram | HIST |
| [52,79] | Spectral Moment | SM | [84,85] | Kurtosis | KURT |
| [52,79] | Sum of Squared Integral | SSI | [52] | Mean Absolute Value Slope | MAVS |
| [52,63] | Temporal Moment | TM | [80,81] | Power Spectrum Deformation | OHM |
| [52,53,79] | Total Power | TTP | [52,53] | Peak Frequency | PKF |
| [51,52,63] | Variance | VAR | [53,86] | Power Spectrum Density Fractal Dimension | PSDFD |
| [51,52,63] | v-Order | V | [84,85] | Skewness | SKEW |
| [52] | Waveform Length | WL | [80,81] | Signal to Motion Artefact Ratio | SMR |
| [52,75,87] | Frequency Ratio | FR | [73] | Time Domain Power Spectral Descriptors | TDPSD |
| [59,60] | Median Frequency | MDF | [52] | Variance of Central Frequency | VCF |
| [59,60] | Mean Frequency | MNF | [53,88] | Variance Fractal Dimension | VFD |
| [52] | Slope Sign Change | SSC | [89] | Fused Time Domain Descriptors | FTDD |
| [51,52] | Zero Crossings | ZC | [29,30] | Discrete Wavelet Transform | DWT |
| [90] | Discrete Fourier Transform | DFT | [33] | Wavelet Packet Transform | WPT |
| [91] | Graph Laplacian | GL | [92] | Relative Wavelet Packet Energy | RWPE |
| [71] | Mean Logrithmic Kernel | MLK |