Application of Surface Electromyographic Signals to Control Exoskeleton Robots

The electromyographic signals abbreviated as EMG, represent the amount of electrical potential generated by the muscle cells when they contract or when they are at rest. Basically, EMG signals can be classified into two types according to the place where they are extracted. The EMG signals detect from inside of the muscles are called as intramuscular EMG whereas EMG signals detect from skin surface of the muscles are called surface EMG. The extraction procedure of intramuscular EMG signals is invasive. The intramuscular EMG signals are difficult to use practically, since the invasive procedure of extraction. EMG signals of human muscles are important biological signals to understand the motion intention of human. Therefore, the EMG signals can be used as input information to control robotic systems (Farry et al., 1996; Kiguchi et. al., 2001). The surface EMG signal is commonly used for this purpose since it can be extracted easily without applying a non-invasive method (Farry et al., 1996). The exoskeleton robot is a device which can be worn by the human operator as an orthotic device (Perry & Rosen, 2007). The same system operated in different modes can be used for different fundamental applications: power-assist device, human-amplifier, rehabilitation device, and haptic interface (Perry & Rosen, 2007). The skin surface EMG signals of the muscles can be used as input information of the controllers of exoskeleton robot (Kiguchi et al., 2001). The EMG signals vary from person to person. In addition, it differs for the same motion even with the same person. The physical conditions such as tiredness, sleepiness, etc. (Kiguchi et al., 2007). Therefore, characteristics of the EMG signals should be carefully considered when developing a control method for exoskeleton robot using EMG signals as input information. Since the surface EMG signals can directly reflect the human motion intention they can be used as main input information to the controller of exoskeleton robot to realize automatic control for the physically weak persons without manipulating any other equipment. Such kind of control is especially important for the system used by elderly, injured, or physically weak persons. This chapter presents an experimental study of upper-limb surface EMG signals and two cases of applying surface EMG signals to control an upper-limb exoskeleton robot. The applied method to process surface EMG signals to use as input information to the control method is also explained. At first, surface EMG signal extraction method and processing