LOCOMOTION plays a crucial role on the capacity to perform activities of daily living, personal functional abilities, and independent development in the community. However, clinical conditions such as stroke, spinal cord injury, Parkinson disease and loss of a member by amputation can affect the human locomotion with varying degrees of severity [1], [2]. To overcome or attenuate human gait disorders, devices such as prostheses [3], exoskeletons [4], and smart walkers [5] have been employed for assistance and rehabilitation purposes. Lower limb exoskeletons are being used for gait assistance and rehabilitation therapies. Robotic exoskeletons are successfully employed for rehabilitation exercises due to its higher repeatability and the quantitative feedback of the patient recovery [6]. Furthermore, the embedded sensors can also be used for continuous monitoring and evaluation of patient progress with predefined objectives and allowing the customization of treatment with increasing levels of personalization and difficulties. This customization is achieved through the dynamic interaction between the exoskeleton and the patient, which happens with the transition between passive, active-assisted, and active-resisted movements of the robotic device controller [7]. Considering the human safety, it is desirable that the exoskeleton actuators have low output impedance [7]. Otherwise, there is a risk of accident with the patient [7]. Furthermore, the actuators must have a bandwidth close to the one of human movement in order to perform the desired movements of the physiotherapy section. A straightforward manner to achieve these requirements is by placing an elastic element between the load (human limb) and the actuator. This is the series elastic actuator (SEA) principle proposed in [8]. Although the spring placed between the load and the actuator can significantly reduce the system output impedance, it also reduces the system bandwidth [9]. Since the human movement occurs in low frequencies [10], SEAs have been successfully employed as exoskeletons actuators [11], [12], [7], among others. Another advantage of SEAs is the possibility of estimating the output torque from spring deflection. For this reason, sensors for spring deflection can be employed instead of the torque sensors, which may simplify the actuator instrumentation. However, sensors used to measure these deflections are generally encoders [7] and potentiometers [13] that require mechanical supports precisely assembled due its sensitivity to misalignments. This may result in a less compact system. Additionally, potentiometers may also result in noisy measurements.