## 3 Experiment  
To validate the feasibility of the proposed method in terms of estimating the wearer intentions in real time, a walking experiment using the EHA system and a sit-to-stand movement was performed. A schematic diagram of the experimental setup of the exoskeleton robot system is shown in Figure 9 below. The motion profile was designed based on the angle of the hip joint and the pressure on the sole. It was connected to a 12-bit analog-to-digital converter between the TI f28379d main controller unit and the load cell sensors, and the absolute hip joint angles were connected by serial peripheral interface communication. Graphic user interface monitoring was also developed with the Microsoft foundation class, which can save up to 2000 data points of each variable for 20 s. Through the proposed method  
Figure 8: System block diagram of the estimated algorithm combined with the EHA [9]. Figure 9: Schematic diagram of the experimental set-up for the exoskeleton system. ADC, analog-to-digital converter; CAN, controller area network; LVDT, linear variable differential transformer; MCU, main controller unit; SPI, serial peripheral interface; and MFC, Microsoft foundation class. with the sensor input values, the wearer's intention was identified in real time, and a gait profile was created. The estimated gait profile was used as a reference value to control the knee joint position. The motion profile was used as a position input to control the knee joint of the exoskeleton robot. We confirmed whether the proposed algorithm estimates the knee displacement in the gait phase by wearing an exoskeleton robot without an actuator. When walking at intervals of approximately 40 cm in width, the hip joint angles showed an angle change of between \(-10^{\circ}\) and \(30^{\circ}\). The left and right hip joint angles were used as input values for a fuzzy set in Figure 10a. Figure 10b shows the heel, metatarsal, and toe plantar pressures. When the sum of the heel, metatarsal, and toe plantar pressures, after converting to a voltage, was less than 0.1 V, the stance phase rule bases were used; otherwise, the swing phase rule bases were used in the fuzzy inference. The fuzzy inputs and outputs for the swing phase from 1.7 to 2.1 s and for the stance phase from 2.1 to 2.7 s, are shown in Figure 10c,d, where the fuzzy outputs using 68 predefined rule bases and fuzzy inputs were implemented. Figure 10e compares the knee joint angle of the robot and the estimated knee joint angle. During the swing phase, the angular displacement of the knee varied from \(0^{\circ}\) to \(55^{\circ}\). On the other hand, the stance phase exhibited a change of angular displacement from \(0^{\circ}\) to \(30^{\circ}\). Figure 10: Experimental results of the proposed algorithm for estimating the knee joint angle: (**a**) the crisp inputs of the hip joint angles, (**b**) the plantar pressure sensors for distinguishing the gait phase, (**c**,**d**) the fuzzy inputs and outputs, respectively, between 1.7 and 2.7 s, and (**e**) the results of the knee joint angle \(x_{r}\) and the estimated knee joint angle \(\hat{x}_{r}\). The experimental data of the walking motion profile is shown in Figure 11. Figure 11a shows the hip joint angles in degrees. At the beginning of the experiment, the hip joint angles were between \(+10^{\circ}\) and \(-10^{\circ}\). During walking, the left and right hip joint angles varied between \(+40^{\circ}\) and \(-10^{\circ}\). Along with this, the foot pressure sensors were used. When the voltage was below 0.3 V, the stance phase rule base was used; otherwise, the swing phase rule base was used. Figure 11c shows the motor speed in revolutions per minute. When the knee length was estimated well, the speed was maintained between 1000 and \(-1000\) rpm, and when the error increased significantly, the temporary maximum speed of the motor was up to 3500 rpm. Figure 11e compares the actual knee joint angles and estimated knee joint angles of the exoskeleton, where the tracking error is expressed in millimeters, as shown in Figure 11d.