# A Review on Upper Limb Rehabilitation Robots
## EMG-Driven Exoskeleton Robots
### Exoskeleton Based on the Neuro-Fuzzy Control Method  
EMG controlling based on the neuro-fuzzy method is characterized by providing a real-time controlling and was efficiently used to control exoskeletons [64]. The physical condition and the nonlinear behavior of the muscle contractions are factors that affect the strength of the EMG, which can be eliminated by using the neuro-fuzzy controlling method. In addition, the EMG quality could be compromised due to shifting of the sEMG electrodes from their positions during limb movements, and ultimately, the neuro-fuzzy method can be used to reduce this shifting effect [64]. The mean absolute value (MAV) feature is used as a control feature in the neuro-fuzzy control method. The MAV feature was chosen due to its efficiency in comparison to other features, such as the slope sign changes, slope \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Source** & \
\begin{tabular}{c} **Type of** \\ **Exoskeleton** \\ \end{tabular} &
\begin{tabular}{c} **Input** \\ **Parameters** \\ \end{tabular} & **Controlling Technique** & **Characteristics** \\ \hline
[60; 61] & Hand & EMG signal & Blind source separation &
\begin{tabular}{c} Adding further degrees of \\ freedom requires adding more \\ sensors \\ \end{tabular} \\ \hline
[62; 63] & Hand & EMG signal & \
\begin{tabular}{c} • binary \\ controlling algorithm \\ \end{tabular} &
\begin{tabular}{c} • It is characterized by its \\ low weight. \\ \end{tabular} \\
[62; 63] & Exoskeleton & EMG signal & \
\begin{tabular}{c} • Variable \\ controlling algorithm \\ \end{tabular} &
\begin{tabular}{c} • More robust controlling \\ algorithm is required to \\ obtain accurate movements. \\ \end{tabular} \\ \hline
[64] & Upper limb & EMG signal and & Neuro-fuzzy controlling &
\begin{tabular}{c} Mean absolute value (MAV) is \\ used as a controlling feature. \\ \end{tabular} \\ \hline
[65] & SUEFUL-7 & Combination of \
\begin{tabular}{c} EMG signal and \\ force signal. \\ \end{tabular} & Muscle model oriented based &
\begin{tabular}{c} Impedance control is modified in \\ real time according to the \\ extracted EMG signal and limb \\ posture. \\ \end{tabular} \\ \hline
[66] & NEUROExos & EMG signal & proportional control method &
\begin{tabular}{c} Two EMG signals are extracted \\ from the biceps and triceps to \\ provide better control. \\ \end{tabular} \\ \hline
[55] & Elbow & EMG signal & \
\begin{tabular}{c} Artificial Neural Network \\ (ANN) \\ \end{tabular} &
\begin{tabular}{c} Seven EMG signals are extracted \\ from seven muscles. \\ \end{tabular} \\ \hline
[67] & Upper limb & EMG signal & Genetic algorithm (GA) & • &
\begin{tabular}{c} RMS is used as a \\ controlling feature. \\ Shoulder, upper arm, lower \\ arm muscles and joints \\ are involved. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Summary of electromyogram (EMG)-driven robots and their control methods. mean absolute value, zero-crossing or wave form length [68]. The neuro-fuzzy control method is characterized by its ability to adapt to any physical condition for different patients; training, however, is required for an efficient adaption [55]. The neuro-fuzzy method is commonly used in robots that are dedicated for improving the life quality of elderly and disabled people [69; 70]. Reference [69] designed a one degree of freedom exoskeleton robot that is used at the elbow complex. The proposed exoskeleton robot depends on the extracted EMG signal to perform the limb's motions. The fuzzy neural network controller was embedded into the controller [64]. The proposed exoskeleton rehabilitates the impaired limb by providing different angular velocities in addition to variations in impedance. The EMG signal extracted from the biceps and the wrist force were used as inputs for the exoskeleton robot [62]. The study involved recruiting three subjects; the subjects were asked to perform flexion/extension at the elbow joint with no weight at first; then, a weight of seven kilograms was used. The system showed effectiveness in supporting the lower limb movements.