###### Abstract  
Robot-assisted gait training (RAGT) is a promising therapeutic vehicle to maximize active participation and enhance functional neuroplasticity in patients with central nervous system pathology by adequately adjusting gait speed, body weight support (BWS) level, and impedance provided by the exoskeleton. The aim of the present study was to determine the relationship between RAGT training parameters (BWS and speed) and electromyography (EMG) muscle activity torques in the knee and hip joint during RAGT. To analyze the correlation between the joint torques measured in the Walkbot gait rehabilitation system and the EMG signal of the lower limbs (vastus lateralis oblique, biceps femoris, tibialis anterior, and gastrocnemius) and understand the real-time state of the lower limb an experiment involving 20 subjects was conducted. The EMG-torque relationship was evaluated in a general rehabilitation training setting to overcome the limitations of in vivo settings. Pearson correlation coefficient analysis was performed at \(p<0.05\). Moderate relationships between biceps femoris activation data and hip and knee torques were statistically significant, ranging from \(r=0.412\) to \(-0.590\), \(p<0.05\). Importantly, inverse relationships existed between hip torques and vastus lateralis oblique, biceps femoris, and tibialis anterior activation, respectively. The present results demonstrated the association between EMG locomotor control patterns and torque generation in the hip and knee joints during RAGT-treadmill under the different BWS and walking speed settings while adjusting the impedance mode parameters in non-neurological adults. Additionally, the EMG locomotor control patterns, concurrent torque generation in the hip and knee joints, and application of different BWS and walking speed parameters in the RAGT were linked to the gait speed and BWS. The outcomes also showed that the amount of BWS supplied had an impact on the effects of treadmill speed on muscle activity and temporal step control. It is essential to adjust RAGT parameters precisely in order to maximize training session efficiency and quality. The results of this study nevertheless call for more investigation into the relationship between muscle activity and torque outcomes in diseased populations with gait impairment. robot-assisted gait training; body weight support; gait speed; muscle activity; torque +
Footnote †: journal: Applied Sciences  
accomplish the goals of gait training, including offering support, propulsion, stability, and foot clearance, using three key parameters: BWS, treadmill speed, and impedance [5; 6]. Thus, patients who are unable to voluntarily accommodate these parameters can elicit neuroplastic changes in the task-specific proprioceptive and somatosensory information necessary for gait rehabilitation as changes occur in the spinal and supra-spinal networks stimulating unaided walking [7; 8; 9; 10; 11]. An impedance-based control mode in the Walkbot is an interactive resistive-assistive system that enables a patient to move with or against impedance-based resistive-assistive forces [12]. For instance, the lower the impedance (e.g., 10-100%), the higher is the resistive-assistive force interactively exerted as the patient actively attempts to reach a target in ankle-knee-hip segmental kinematic and kinetic coordination, which is concurrently provided in the real-time presentation system [13]. This allows low impedance control to elicit greater active participation of patients through human-robot interactions. In contrast, high impedance control is designed to guide the lower limbs to follow a predefined trajectory. Regarding BWS, the locomotor muscles cannot be activated properly if the patient's weak muscles are overloaded with body weight. However, they could adequately re-learn weight-bearing steps, interlimb coordination, and foot placement with ideal muscle coordination using RAGT with BWS.