In recent years, the aging of society has become a serious problem, especially in developed countries. Walking is an important element in extending healthy life expectancy in old age. In particular, induction of proper ankle joint alignment at heel contact is important during the gait cycle from the perspective of smooth weight transfer and reduction of burden on the knees and hip. In this study, we focus on the behavior of the ankle joint at heel contact and propose an insole-type assist device that can induce the ankle angle inversion/eversion rotation. The proposed device has tilting of the heel part from left to right in response to the rotation of a stepping motor, and an inertial sensor mounted inside controls the heel part to always maintain a horizontal position. The effectiveness of the proposed device is verified by evaluating the amount of lateral thrust of the knee joint of six healthy male subjects during a foot-stepping motion using motion capture system. The results showed that the amount of lateral thrust is significantly reduced by wearing the device with control.

Nowadays, it has been actively expanded to develop assist robots attached directly. In this study, we focused on developing an exoskeletal robot, specifically, a force transmission robot with a rotary drive type ratchet mechanism, to enable users with upper limb disability to make use of their residual function to achieve better function of their upper limbs. A lock/unlock mechanism on the elbow joint is effectively used to transmit the user’s residual function around the shoulder to the hand. We conducted verification experiments on whether the developed mechanism enables the user to transfer the remaining force in the shoulder joint to operation force in the hand. Three subjects with C5 and C6 spinal cord injury with disabilities affecting their hands, lower limbs, and trunk muscles performed the verification experiment with the developed device. We confirmed that they could operate a wheelchair on a slope and on grass when using the developed device, and they could use their residual function around the shoulder more strongly. It can be expected to rehabilitation effect.

We previously proposed a motion support robot and conducted experiments in which a C5-level cervical cord injury patient used the system. This paper proposes to offer motion support to a C4-level spinal cord injury patient who suffers from paralysis of the limbs. Electromyogram (EMG) signals are used to determine the user's intentions. The proposed motion assist robot can then support flexion and extension at the elbow joint. Using frequency analysis of the EMG signal, the patient's intention can be estimated in real time, and the coefficient of viscosity is varied in an admittance controller. With the proposed motion assist method, we were able to realize arbitrary upper limb motion of a C4-level cervical cord injury patient.

Thousands of individuals of all ages are living with a spinal cord injury as a consequence of a traffic, or sports accident or other calamity, and many of these individuals incurred a C5-level spinal cord injury, with a loss of the ability to use their legs and exert extension force from the elbow joints. Many of the motions that are necessary in daily life are difficult or impossible to perform with this level of spinal cord injury, and it is expected that wearable motion-assist robots will someday be available for use by individuals with C5 injuries. In order to be wearable, an assist robot must not limit the user's range of motion while being used, and it must be suitable for a wide range of situations. In the present study, we developed an extension force support system that acts in accord with the operator's intentions under the effect of external force as the operator use a wearable motion-assist robot for an upper limb. The effectiveness of the developed system was demonstrated experimentally.

Many people of all ages have sustained cervical cord injury in traffic accidents or sport accidents, and con sequently suffered physical impairment. For individuals with paralysis of the lower limb who have also lost the ability to extend the elbow, many motions become difficult to perform in daily life, for example, independently operating a wheelchair or pushing open doors. In the future, wearable assist robots are expected to be incorporated into daily life. In order to be wearable, the assist robot must not limit the user's range of motion while being carried or used, and must be suitable for a wide range of situations. In this study, we developed an assist robot for upper limb movement which can assist wheelchair operation. To achieve this, we constructed a model of the upper limb during wheelchair operation with a manipulating force ellipsoid, and we developed an assistance control method for the upper limb using the device to apply force vectors. The effectiveness of the developed system is demonstrated experimentally.

Many people of all ages have sustained cervical cord injury in traffic accidents, falls, or sport accidents, which has resulted in their physical impairment. Among such individuals, dysfunction of the upper limb is of particular concern, even though recovery from dysfunction is possible through rehabilitation. In this study, we developed a wearable assistive robot for the upper limb; this robot can be used to perform various tasks involving upper limb motion in daily life. To achieve this, we devised an algorithm for assisting extension motion. Individuals with C5-level Cervical Cord Injury (CCI) cannot perform extension of the elbow on their own. Therefore, we calculated the reference velocity curve and the angle of extension only from the force in the direction of flexion. In this way, the wearer can autonomously adjust the movement.

Students studying to become therapists have few opportunities for repeated training for the rehabilitation of contracture joints. This paper proposes the concept of a robot hand system for repeated rehabilitation training. A novel robot hand and artificial skin are developed in collaboration with doctors and therapists. Development of the robot hand is based on new design concepts aimed at imitating a human hand with a disability. The joint torque of a disabled person can be estimated by distributed tactile sensors. A model of contracture joints with tendon adhesion is introduced. The robot hand in imitation of contracture joints is governed by the force control based on torque control. The effectiveness of the proposed method is demonstrated experimentally.

The self-organizing map (SOM) is an unsupervised learning method as well as a type of nonlinear principal component analysis that forms a topologically ordered mapping from the high-dimensional data space to a low-dimensional representation space. It has recently found wide applications in such areas as visualization, classification, and mining of various data. However, when the data sets to be processed are very large, a copious amount of time is often required to train the map, which seems to restrict the range of putative applications. One of the major culprits for this slow ordering time is that a kind of topological defect (e.g., a kink in one dimension or a twist in two dimensions) gets created in the map during training. Once such a defect appears in the map during training, the ordered map cannot be obtained until the defect is eliminated, for which the number of iterations required is typically several times larger than in the absence of the defect. In order to overcome this weakness, we propose that an asymmetric neighborhood function be used for the SOM algorithm. Compared with the commonly used symmetric neighborhood function, we found that an asymmetric neighborhood function accelerates the ordering process of the SOM algorithm, though this asymmetry tends to distort the generated ordered map. We demonstrate that the distortion of the map can be suppressed by improving the asymmetric neighborhood function SOM algorithm. The number of learning steps required for perfect ordering in the case of the one-dimensional SOM is numerically shown to be reduced from O(N(3)) to O(N(2)) with an asymmetric neighborhood function, even when the improved algorithm is used to get the final map without distortion.

Although context-dependent spike synchronization among populations of neurons has been experimentally observed, its functional role remains controversial. In this modeling study, we demonstrate that in a network of spiking neurons organized according to spike-timing-dependent plasticity, an increase in the degree of synchrony of a uniform input can cause transitions between memorized activity patterns in the order presented during learning. Furthermore, context-dependent transitions from a single pattern to multiple patterns can be induced under appropriate learning conditions. These findings suggest one possible functional role of neuronal synchrony in controlling the flow of information by altering the dynamics of the network.