**5. Conclusion and future directions**

Raw EMG Signals

EMG Feature Extraction

> Neural Network Decoder

Predicted Joint Angles

iEMG is capable of providing accurate EMG data to the control system. Use of implantable myoelectric sensor (IMS) would result in nullifying the problem of multiple-component EMGs, an inborn problem of surface EMG recording, as well as the nullifying the considerable amount of environmental effects caused for the changes in regular sEMG signal supply. Here the IMS receives commands and power from an external telemetry controller [8]. It drives a coil

**Figure 20.** Block diagram of control strategy [36]

262 Electrodiagnosis in New Frontiers of Clinical Research

*4.2.6. iEMG controlled prosthetic device*

**Figure 21.** Schematic of the implantable myoelectric sensor system[8]

Time-Domain Features

> In this chapter, recent EMG based control methods of assistive robots were comprehensively reviewed. As assistive robots, upper-limb exoskeleton robots and upper-limb prostheses were mainly considered here. At first, the detection and processing of the EMG was explained discussing available EMG extraction systems. Then ways of categorization of EMG based control methods as input information to the controller, architecture of the control algorithm, output of the controller and other ways were discussed. EMG based control methods were categorized based on structure of the control algorithm as pattern recognition based control and non-pattern recognition based control. Even though assistive robots with pattern recog‐ nition based control can be commonly found, control methods that belong to non-pattern recognition based control are hardly found. Recent EMG based control methods of upper-limb exoskeleton robots and prostheses were reviewed separately. In the review recent EMG based control methods of upper-limb exoskeleton robots and upper-limb prostheses were compared considering their features.

> In addition to EMG signals, EEG, EOG and MMG signals also represent the human motion intention and these can be used as input signals to the controller of the assistive robots. Accordingly, in the future a hybrid control algorithm can be developed with a combination of two or more biological signals as inputs to the controller. Assistive robots are expected to function and appear as their biological counterparts. That is, an exoskeleton should ideally act as a second skin for the human and a prosthetic device the same as the natural limb. Accord‐ ingly, control methods of devices should be improved in the future.

> Actuator technology also plays an important role of control methods of exoskeleton robot and prostheses. Actuators drive a robot interacting with human according to control inputs. Linearity, stability, correspondence between human motion and actuator actions are important terms for successful function of actuators and hence the control system too. New actuator technologies can be successfully used with exoskeleton robots and prostheses to improve its function.

> In future developments, the aspect of control systems of the assistive robot can be extended to take the effect of microclimate conditions present around the user and take suitable control efforts to provide comfort to the user. Since exoskeleton robots and prostheses closely interact

with the human, safety conditions should be guaranteed at a maximum level. Although some safety features are connected with mechanical design through stoppers and emergency shutdown systems in an electrical system, proper software locks can be implemented in the control system of the robot to improve the safety features. Further, intelligent safety methods can be introduced to the assistive robot with the help of a feedback system of its control method. One of the human biological signals generated by eye ball movement called electrooculogram (EOG) can be used to generate the feedback signal to the controller. Therefore, when a person feels any unsatisfactory motion of the robot, a particular eye ball movement can be traced and used as a feedback signal and further it can be used to switch off the function of the robot. Since this type of safety method is directly connected with human function it gives maximum protection to the user.

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The performance of the control methods is not only based on the controller; it may vary on selection of different components in the control loop. This includes selection of final control elements or actuators, instrumentation for feedback signal, disturbance rejection (inside control loop or outside to the loop), input signals etc. Therefore selection of actuators and sensors play an important role in exoskeleton and prosthesis control systems. In case of sensors, Micro-Electro-Mechanical System (MEMS) inertial sensors are very suitable to detect the changes in velocity, orientation and location of above assistive robots. This technology has made miniaturized sensors and provides low power consumption, low cost, low size and weight which can be used to enhance the function of control method of assistive robots.
