# Review of sEMG for Robot Control: Techniques and Applications
## 3 Processing and Pattern Recognition Methods
### Pre-Processing  
The primary purpose of pre-processing is to obtain filtered signals. Generally, noise can be divided into six classes: electronic devices' inherent noise, ambient noise, motion artifacts, inherent instability of sEMG signals, electrocardiographic artifacts, and cross-talk \begin{table}
\begin{tabular}{c c c c} \hline
**Body Part** & **Joint** & **Muscles** & **References** \\ \hline  & & biceps brachii & \\  & & triceps brachii & \\  & & flexor carpi radialis & \\  & & extensor carpi radialis & \\  & & flexor carpi ulnaris & \\  & & extensor carpi ulnaris & \\  & & flexor digitorum superficialis & [3; 7; 11; 16; 22; 23; 24; 25; 37; 70; 77; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 90; 91] \\  & & brachoratorialis brachialis & \\  & & aconeus & \\  & & pronator trees & \\  & & supinator & \\  & & extensor digitorum & \\ \hline  & & biceps brachii & \\  & & deltoid & \\  & & pectoralis major & \\  & & supraspinatus & \\  & & trapezius & [9; 22; 23; 37; 75; 80; 82; 84; 86; 87; 88; 91; 92; 93] \\  & & teres major & \\  & & teres minor & \\  & & infragnipatus & \\  & & latissimus dorsi & \\ \hline  & & Hip & gluteus maximus & [10] \\ \hline  & & & bandriceps femoris & \\  & & hamstring & \\  & & gastrocnemius & [5; 34; 80; 94; 95; 96; 97; 98; 99] \\ Lower-limb & & & anterior tibial & \\ \hline  & & gastrocnemius & \\  & & anterior tibial & \\  & & peroneus longus & [2; 4; 6; 34; 100] \\  & & extensor digitorum longus & \\  & & peroneus brevis & \\ \hline  & Face & masseter muscle & [13] \\ \cline{2-2} Other parts & Abdomen & rectus abdominis & [80] \\ \cline{2-2}  & Back & erector spinalis & [12; 80] \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._from muscles around the target area [100; 103; 104]. Although some artifacts and cross-talk have been avoided by selecting the electrode position and using a wireless transform, raw data acquired by the sEMG sensor still contain many noise signals. The most helpful information from the sEMG signal is distributed in the frequency band of 0 Hz-500 Hz, and the primary energy is concentrated in 20 Hz-150 Hz [105]. Based on this fact, most studies have used band-pass filters, and the frequency band of filtering is 20 Hz-500 Hz. [PERSON] [106; 107] and [PERSON] [8; 108; 109; 110; 101]'s works are based on a broader frequency band from 20 Hz to 1750 Hz, whereas others focus on a narrow band. The Butterworth band-pass filter is the most popular filter. The main difference in those studies in which the Butterworth filter is used is its order. Bidirectional filters help prevent phase shifts that filters may introduce [42; 51; 77; 92]. To eliminate the influence of power frequency interference on sEMG, a signal with a small amplitude, [PERSON] [111] and [PERSON] [112] used a notch filter at 50 Hz or 60 Hz. On the contrary, some scholars believe that the notch filter filters the bioelectrical information in the corresponding frequency band; therefore, they did not use a notch filter [96]. In addition to placing electrodes on the target muscles, [PERSON] [113] and [PERSON] [112] also placed an extra sensor on the nearby inactive muscle as the resting signal channel. By subtracting the resting signal from the signals of each target channel, the baseline noise and cross-talk can be filtered. After the first round of filtering, a low-pass filter was used again in some studies because the contraction frequency of muscles in healthy people is low under normal conditions [12; 32; 42; 86]. High-frequency (>10 Hz) nerve stimulation triggers tonic contraction of skeletal muscle, which is a concern of scholars who pay attention to Parkinson's disease and stroke patients. The power of the sEMG signal is meager, and the maximum amplitude is generally less than 10 mV [48]. Therefore, amplifying the sEMG signal is necessary to facilitate the signal acquisition. However, most acquisition systems can perform this step automatically, and researchers no longer need to handle it manually. The amplitude of the sEMG signals is assumed to be proportional to the muscle tension [48].