Gait analysis can objectively assess abnormal walking, and some walking parameters can help recognize the disease. Existing commercial systems are either too expensive and require attachments to the body or have limitations in detecting abnormal gait. A vision system has been proposed to address this. However it had limitations where the accuracy was inferior in some parameters such as gait phase, step length and width, etc. Therefore we developed a Tactile sensor-based treadmill to detect gait phase, step length, and width. A pilot test was performed and analyzed through an infrared marker-based motion capture system to compare the accuracy of the proposed system. The measured spatiotemporal gait parameters were analyzed through mean and standard deviation and compared to the baseline system. As a result of the experiments, it was confirmed that higher step width performance was achieved compared to previous studies. Future studies will validate the system with many participants and conduct clinical studies on gait recognition through abnormal gait analysis.

In the case of the visually impaired, in order to pick up an object, the entire shape is grasped while straddling the object first. When we grasp the characteristics of the object sufficiently by using the tactile sense of the hand, we touch the point which is the center of gravity and listen to the object once. When you want to perform object-graping with only the tactile sense under the conditions of other senses, such as vision, a series of actions is repeated. This paper deals with the behavior based control study of the robot hand using the tactile sense and applied to the 4 DOF hand developed by our laboratory by evolving the subsumption architecture (SA) proposed by R.Brooks.

To realize a robot hand interacting like a human hand, there are many tactile sensors sensing normal force, shear force, torque, shape, roughness and temperature. This sensing signal is essential to manipulate object accurately with robot hand. In particular, slip sensors make manipulation more accurate and breakless to object. Up to now several slip sensors were developed and applied to robot hand. Many of them used complicate algorithm and signal processing with vibration data. In this paper, we developed novel principle slip sensor using separation layer. These two layers are moved from each other when slip occur. Developed sensor can sense slip signal by measuring this relative displacement between two layers. Also our principle makes slip signal decoupled from normal force and shear force without other sensors. The sensor was fabricated using the NBR(acrylo-nitrile butadiene rubber) and the Ecoflex as substrate and a paper as dielectric. To verify our sensor, slip experiment and normal force decoupling test were conducted.