## 1 Introduction
The simulation experiment results show that after wearing the lower limb exoskeleton, its energy consumption can be reduced by 58.6% when bearing an additional 100 Kg payload. This proves that the knee-joint lower limb exoskeleton can effectively help the human body bear heavy loads and reduce the energy consumption of the human body during the walking process [21]. Some researchers have worked on the optimal design of exoskeletons using AnyBody software [26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37]. Geonea presents a design solution for a new exoskeleton robot leg mechanism. A virtual prototype based on AnyBody was created. Kinematic and kinetic analysis of the proposed exoskeleton robot was carried out. The proposed exoskeleton was found to achieve similar motion patterns in the hip and knee joints as in normal human walking [23]. [PERSON] proposed a parameter optimization method for the exoskeleton. A validation analysis was also carried out using AnyBody software. The optimized exoskeleton reduces the estimated muscle force by an average of 5.73%. The average reduction in muscle force was 14.5%, and the peak reduction was 32.2% compared to not wearing the exoskeleton [24]. [PERSON] applied AnyBody software to establish the overall model of the human body and hip rehabilitation device. The inverse dynamics simulation and muscle force analysis of the overall model were carried out to obtain the force and muscle activity of the hip muscle groups when using the hip rehabilitation device. The experimental results were used to provide data support for the optimization of the hip rehabilitation device [26]. [PERSON] investigated the effectiveness of lower limb exoskeletons in rehabilitation training [28]. The contraction rates of the major muscles of the lower limbs were analyzed by simulating the trajectory of the rehabilitation robot in the sagittal plane. The results showed that the contraction rates of the thigh muscle groups were the same. The differences in the calf and hip muscle groups were statistically significant. However, the analysis targeted a single factor and was not comprehensive enough. [PERSON] proposed a method for modeling an exoskeleton robot based on AnyBody software. The dynamics of the robot system are analyzed using AnyBody software and ADAMS. The relationship between the change law of the turning angle of the kinematic joints, the connection force of the kinematic joints, and the GRF is given. Finally, a solution for easy manufacturing of the robotic system using 3D printing technology was proposed [29]. Although many studies have explored human body movement patterns and optimization strategies of exoskeletons [38; 39; 40; 41; 42; 43; 44], there is a lack of human-machine simulation studies of a real exoskeleton attached to the musculoskeletal model with unilateral movement disorders. At present, most studies have been performed on normal people. Most stroke patients exhibit unilateral dyskinesia [45; 46; 47]. Since exoskeletons are intended for patients with disabilities, it is necessary to explore whether exoskeleton robots could actually meet the needs of patients. In this paper, two virtual models were built in AnyBody software. The first one is a human-exoskeleton model driven by healthy slow walking kinematics. The kinetic and biomechanical parameters of the human model and the human exoskeleton model were compared and analyzed. The effect of the lower limb exoskeleton on the human body can be quantitatively analyzed. The second model is the SSP subject-exoskeleton model, which is driven by kinematic data from subjects with unilateral movement disorders walking with a real exoskeleton. Since the measurement data were obtained from participants wearing the exoskeleton, the predicted GRF accuracy will validate both models.