# Switched Control of Motor Assistance and Functional Electrical Stimulation for Bieps Curls +
## 4 Discussion  
The results in Table 1 show that the average position and velocity errors of the impaired arm are similar to that of the unimpaired arm for both participants, despite each having movement disorders that significantly limit performing daily activities with their impaired arm. By design, the motor only contributes as needed and the FES activates the biceps throughout flexion. The goal of rehabilitation is generally to challenge the patient to build muscle and coordination, but not so much that they can only perform a limited number of repetitions. The assist-as-needed motor controller, in combination with the FES-controller, allows for this sort of rehabilitation goal and are a promising development for rehabilitation robotics. Since the control system essentially replaces the broken neurological pathways in the participant and, since volitional effort was not encouraged, it may be expected that the experiments on the participant's impaired arms performed similar to their healthy arms; however, there are many factors that the control system must account for in a healthy vs. impaired limb. For instance, the impaired limb is likely not used much in daily activities, and, thus, has atrophied and requires more FES and motor assistance, for which the control system automatically adjusts. Moreover, the electrodes used in this study were surface electrodes placed on the skin, which may not penetrate deep enough to reach all muscle fibers, which may disproportionately affect the impaired arm that already takes more control input to move. Lastly, the first participant had physical damage in addition to neurological damage in his impaired right arm, which the designed control system was able to account for. In [19], exponential tracking of the desired elbow angle trajectory is achieved and the motor assists when the stimulation comfort threshold \(\Gamma\) is reached; however, the motor only assists for an instant before the error drops, resulting in the FES control input to fall below the single threshold \(\Gamma\). This method resulted in the motor being frequently activated and deactivated (i.e., chattering), in addition to the chattering that can result from sliding mode control. Not only does this fail to accurately mimic the relatively consistent and smooth muscle contractions achieved during voluntary exercise, it is also undesirable from a control and hardware perspective. Comparing the error and stimulation results in Figure 3 of this paper to Figures 3 and 4 of [19], it can be seen that both the stimulation and the error smoothly increase and decrease in the current experiments, but change very quickly around the threshold value in [19]. Since the motor control input is mathematically dependent on the FES control input, when the FES control input is chattering, so is the motor. Moreover, the reliance on the motor for longer bouts results in lower average position and velocity errors. The results from [19] motivated the control design in this paper, where the motor continues to assist the muscle until \(u_{m}\) reaches the lower threshold \(\gamma_{j}\). Moreover, to prevent the motor from turning on and off more frequently as the biceps fatigues, the motor remains activated until the position and velocity errors are low enough to result in an FES control input of \(\gamma_{j}\). This does not guarantee that the motor is activated over a longer amount of time or range of elbow angles, which is typically the result because it takes more time for \(u_{m}\) to rise back to \(\Gamma\). However, if a physical therapist or other rehabilitation specialist desired, \(\rho=1\) would cause the lower threshold to remain constant throughout the protocol. As seen in Figure 3, as an example of a typical portion of an experiment, changes in the stimulation pulsewidth mirror changes in the position error, but with a short lag time.