In highly mobile workplaces, wearable walking assistant robots can reduce muscle fatigue in the lower extremities of workers and increase energy efficiency. In this study, walking efficiency according to the development of an ultralight wearable hip-assist robot for industrial workers was verified. Five healthy adult males participated in this study. Their muscle fatigue and energy consumption were compared with and without the robot while walking on a flat treadmill and stairs. When walking on the treadmill while wearing the robot, muscle fatigue in the rectus femoris and gastrocnemius decreased by 90.2% and 37.7%, respectively. Oxygen uptake and energy expenditure per minute also decreased by 8.9% and 13.1%, respectively. When climbing stairs while wearing the robot, fatigue of the tibialis anterior, semitendinosus, and gastrocnemius muscles decreased by 18.2%, 33.3%, and 63.6%, respectively. Oxygen uptake and energy expenditure per minute also decreased by 3.6% and 3.7%, respectively. Although wearing a hip-assist robot could reduce muscle fatigue and use metabolic energy more efficiently, it is necessary to further increase the energy efficiency while climbing stairs. This study is intended to provide basic data to improve the performance of robots.

Total hip replacement is a representative treatment for avascular necrosis of the femoral head. However, the stress shielding caused by the replacement induces dissociation of the artificial hip joint and various complications. Many studies have tried to explore the stress shielding but, most studies have been conducted at macro level and not at micro level. Thus, this study aimed to quantitatively analyze the structural behavior of the proximal femur according to total hip replacement at the micro level to explore the stress shielding. For this purpose, this study selected the artificial hip joint of the single wedge type and implanted the joint into a proximal femur that has a high resolution of 50 μm. Then the structural behavior of the implanted femur was analyzed by comparing that of the intact femur under three daily activity loads. As a result, the high possibility was confirmed that the stress shielding will occur in both cortical and cancellous bones under the one-legged stance movements. Additionally, it was discovered that the cancellous bone had a considerably lesser chance of adducting at an angle similar to the neck shaft angle of an artificial hip joint.

This paper deals with the development of a passive modular hip exoskeleton system aimed at preventing musculoskeletal low back pain, which commonly occurs in heavy weight transport workers, by improving back muscle strength. The passive exoskeleton system has the advantage of being lightweight, making it suitable for modular exoskeleton systems. The cam and spring actuator designed in this study was applied to the passive modular exoskeleton system to build human hip and lumbar muscle strength. In order to evaluate the effectiveness of the passive modular exoskeleton system, a test was performed in which a subject lifted a 15 kg weight three times in a stoop posture, using heart rate measurement and Borg scale recording. According to the results, all subjects showed 26.83% lower maximum heart rate and 34.73% lower average heart rate than those who did not wear the system, and Borg scale evaluation result was lower. All subjects wore this system and did not experience back pain during the experiment. Through this study, we validated the effectiveness of the passive modular exoskeleton system and proved that this system can build the strength of industrial workers and be a solution to prevent musculoskeletal lumbar disease.

The purpose of this study was to suggest the method for automated locomotion modes (Level Walking, Stair Ascent, Stair Descent) detection based on the Radial Basis Function Support Vector Machine (RBF-SVM) for the hip gait assist robot. The universal hip gait assist robot had a limit in detection of the walking intention of users because of the limited sensors’ quantity. Through the offline training, using MATLAB, we trained the collected gait data of users wearing the hip gait assist robot and obtained the parameter of the RBF-SVM model. In the online test, using LabVIEW, we developed the algorithm for the locomotion modes decision of individuals using the optimized parameter of the RBF-SVM. Finally, we executed the gait test for three terrains through the walking environment’s test platform. As a result, the locomotion modes decision rate for three terrains was 98.5%, 99%, and 98% respectively. And the decision delay time of algorithm was 0.03 s, 0.03 s, and 0.06 s respectively.

In this paper, we design and fabricate a wearable walking-assist robot using a tendon-driven method. Most wearable walking-assist robots are designed using the method of the attaching of the motors to the hip, knee, and ankle joints. The robot needs the capacities of the motors attached to the hip and knee joints to equal the weights of the motors attached to the knee and ankle joints and the motor attached to the ankle, respectively. To solve these problems, we design and fabricate the wearable walking-assist robot using a tendon-driven method that rotates the joints by attaching the motors of the hip, knee, and ankle joints to the waist joint, and pulling it with a line. The gait patterns of a normal person are photographed and analyzed, thereby providing the ankle position (x, y) during the walking that is then calculated using the forward kinematic equation, while each joint angle is calculated using the inverse kinematic equation. As a result of the characteristic experiment of the wearable walking-assist robot, the resultant walking aspect is similar to that of the normal person.

In this paper, we designed and fabricated a hip joint torque sensor that can measure the torque applied to the hip joint of a walking assistant robot that can be used by a leg patient. To do this, we modeled the structure of the hip joint torque sensor so that it can be connected to the thigh link and the body of the walking assist robot. We calculated the rated torque of the hip joint torque sensor using computer simulation and determined the size of the torque sensor using a finite element program. The hip joint torque sensor was made by constructing a Wheatstone bridge and attaching a strain gauge. The characteristic test of the fabricated torque sensor was performed using a calibration device, and the reproducibility error and the nonlinearity error of the torque sensor were both less than 0.04%. Therefore, it is proposed that the developed hip joint torque sensor can be attached to the thigh link of the wearable walking assist robot, and the torque sensor can accurately measure the torque applied to the hip joint.