A Simple Simulation System for Quantifying Buttock Loads Caused by Daily Activities of Wheelchair Users.

The purpose of this study is to quantify the load generated on the buttocks during wheelchair operation in order to clarify the cause of pressure injuries on the buttocks of wheelchair users. In the case of repeated measurements, pressure injuries may occur by conducting experiments with people with actual disabilities. In this study, we proposed a method of dynamic simulation using a humanoid model in order to carry out buttock load safely due to exercise. In addition, the load on the buttocks is quantified by reproducing a simulated cushion that reproduces the actual physical properties on the simulator. When we conducted an evaluation experiment of the developed simulation to quantify the buttock load, we confirmed the validity of this simulator in the front-back direction. On the other hand, the correlation with the actual data is low in the left-right direction, and it is considered necessary to improve the humanoid model in order to improve the accuracy.

Simple Three-Dimensional Motion Measurement System using Marker-IMU System.

Image-based motion capture system have a limited measurement range, and the inertial motion capture system cannot directly acquire the position information. In addition, simple and robust measurement is required in the realization field, but it is difficult with the conventional motion capture system. Therefore, in this research, we constructed a system that robustly measures human movements by combining images and IMUs. High-accuracy visual markers were used to measure the position and orientation by images. By combining this with an IMU, we have established a robust measurement method even for hiding. In addition, by using the environmental reference marker, it is possible to acquire the absolute position even if the camera moves. In fact, we measured the movement and walking movements of human upper limbs, and realized continuous and smooth movement measurement by this method.

Estimating Movements of Human Body for the Shirt-Type Wearable Device Mounted on the Strain Sensors Based on Convolutional Neural Networks.

To measure the life log of humans and enjoy virtual or augmented reality video games, several wearable devices have been developed that allow users to intuitively input commands. However, monitoring and estimating three-dimensional human motions for extended periods using the wearable devices is difficult. Therefore, this study aims to develop a method that estimates the joint angles of the upper human body using a wearable suit implanted with strain sensors with a nonlinear characteristic. We used a convolutional neural network (CNN) to estimate the joint angles. We established a CNN estimator based on the training data of two adult males and confirmed that this estimator could estimate the joint angles of other adult males. To monitor the caretakers in a care facility, we measure the care-working motion, such as motions that care workers transform the elder persons, estimate each joint angle, and visualize the motions on Unity.

Validation of Improvements of Robotic Devices for Nursing Care using a Sensing Dummy Simulating Human Body.

The population in advanced countries is rapidly aging, and these countries are faced with various issues pertaining to the rapidly aging population. It is expected that manpower shortages for nursing care of the elderly will be resolved using robotic devices. A method is necessary for quantifying the load of the human body that is envisaged to encourage the widespread use of robotic devices for nursing care. Therefore, we developed a sensing human dummy consisted of several sensors that emulated the stiffness of the human body and its shape. In a previous study, we developed the buttock dummy that consisted of emulated bones and soft tissue. In this study, we mounted force sensors, and emulated blade bones and soft skin. We compared the robotic beds "Resyone" with "Resyone Plus" and showed that the latter elicited improved comfort with respect to the former. In these experiments, we used the sensing dummy and the visual markers to evaluate the load and the posture of users. From the validation experiments, the shear force of the sacral bone of Resyone Plus was determined to be lower than that for Resyone owing to the movement of the foot.

Gait training assist system of a lower limb prosthetic visualizing muscle activation pattern using a color-depth sensor.

Some unilateral lower-limb amputees load the intact limb more than the prosthetic limb. This can cause chronic pains, fatigue, lumbago, and joint diseases, including knee osteoarthritis. To avoid and counteract these symptoms it is necessary to improve their asymmetric gait. Increasing the function of the hip abductor muscle is important to maintaining symmetrical weight distribution. Therefore, the purpose of this study is to develop a training assist system, which estimates and visualizes an abductor muscle by using a color-depth sensor. To estimate the muscle activation, first, the floor reaction force is calculated using a simple dynamic model. Then, the hip torque is calculated using joint angles. The floor reaction force and, the muscle length are calculated based on a human musculoskeletal model. Muscle activity is estimated by these parameters. Evaluation experiments of this proposed method were performed on healthy persons and unilateral trans femoral amputees, and the effectiveness of this proposed algorithm has been confirmed.

Rehabilitation for hemiplegia using an upper limb training system based on a force direction.

Hemiplegia patients have complete paralysis of half their body, and encounter many challenges in living an independent life. Rehabilitation of the lower body is more important than that of the upper body for independent living; thus, recovering upper body functions of their paralyzed side is not enough. Rehabilitation robots may be used to assist training without therapists. In this study, a small portable rehabilitation robot was developed for use at home, and a new training method was proposed. This robot consists on an omni wheel mechanism and a force sensor, and is capable of deciding the motion based on the force value. Voluntary movement of a hemiplegia patient is recovered by the rehabilitation robot and proposed training method. Thus, verification experiments were performed using participants with hemiplegia. The CCI (Co-Contraction Index) from after training were smaller than ones of before training, thus the movement skills of the participants improved with respect to controlling force direction and magnitude. Moreover, manual function test (MFT) scores increased as reflected by improvements in the motor function of the upper limb using the proposed training method.

Exercise system for eccentric tibialis anterior contraction to improve ambulatory function.

This study has developed a device and system for the exercise of eccentric contraction of the tibialis anterior, with the objective of maintaining ambulatory function. A system was built that allows for exercises of appropriate load and speed, by providing the trainee with force data in the form of visual feedback. An experimental verification with two healthy participants shows small variation in the Myoelectric data during the repetitive exercise. The result suggest the possibility of higher reproducibility of the proposed exercise in comparison with manual exercise. As a clinical test, elderly ambulatory participants who frequented a day care facility performed exercises for one month (twice weekly) using the proposed device and exercise system. To verify the exercise results, a TUG test was performed, which is an assessment index for functional mobilization capacity. Shorter TUG in the majority of the participants suggests a possible beneficial effect in ambulatory function.