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Walking is one of the most important activities. However, when abnormalities occur during walking, falls occur. Fractures caused by falls may significantly reduce activities of daily living and quality of life. Falls due to external factors occur during the swing phase when the leg is floating. Detection of the period from the moment the lower leg becomes vertical to the moment of the heel contact may help elucidate the phenomenon of falls in the future and may prevent falls by some manipulation during this period. Therefore, in this study, we develop an algorithm for detecting terminal swing independent of walking speed using a 6-axis sensor attached to the heel of shoes. Preliminary experiments were conducted on a treadmill at walking speeds of 2, 3, 4, and 5 km/h. The theoretical time of the terminal swing was measured using motion capture. Preliminary experimental results showed a correlation between the maximum angular velocity of the lateral direction axis of the 6-axis sensor and the acceleration in the toe direction at the beginning of the terminal swing. Therefore, this study proposes an algorithm for detecting terminal swing using the relationship between the maximum angular velocity of the lateral direction axis and the acceleration in the toe direction at the beginning of the terminal swing. Comparing the time of the beginning of the terminal swing between the proposed method and motion capture, it was confirmed that the algorithm could detect the terminal swing at walking speeds of 3, 4, and 5 km/h with a smaller error than in previous studies.

This study proposes a method for estimating the positions of vehicles in urban environments with high accuracy. We employ satellite positioning by GNSS for position estimation. Real-time kinematic-global navigation satellite systems (RTK-GNSS) with high precision in satellite positioning can estimate positions with centimeter-scale accuracy. However, in urban areas, the position estimation performance deteriorates owing to multipath errors. Therefore, we propose a method to improve the positioning results by increasing the robustness against multipath using vehicle trajectory. The vehicle trajectory estimates the travel route using the attitude angle and speed. Attitude angles are heading, pitching and slip angle. Trajectories can be generated with 0.5m error performance per 100m. In the proposed method, the trajectory is used as a constraint to solve the multipath of RTK-GNSS. In the evaluation test, the ratio of high-accuracy position estimation improved by up to approximately 30% compared to the conventional method. It is assumed that this method can enhance the development of self-driving cars, AGV control and SLAM technology by eliminating errors and calculating reliability.

Walking ability plays a major role in being healthy. Assessment of the walking ability of cane users in daily life will assist in rehabilitation implementation and health maintenance. We are developing a system for evaluating the walking ability of a cane user based on the motion of the cane. The purpose of this study was to analyze the correlation between the walking ability and the cane motion indicators that can be measured using an inertial measurement unit(IMU), and to identify the indicators that can be used to evaluate the walking ability. Twelve postoperative patients who had undergone total knee arthroplasty, uni-compartmental knee arthroplasty, total hip arthroplasty or bipolar hip arthroplasty were video recorded while walking along a 6 mlong straight line with a cane, and the resulting IMU data were recorded. We detected the timing of the initial contact and the terminal contact of the cane based on the jerk norm and the absolute angular jerk, calculated using the IMU data. We used gait velocity and step length as the walking ability indicators, and analyzed the correlation between these two indicators and the indicators detected using the IMU. These indicators were the angles in the sagittal and coronal planes of the cane at the initial contact and terminal contact, the acceleration and the jerk norms at the initial contact and terminal contact, the time of the cane touching the ground, and the maximum angular velocity while swinging the cane. Gait velocity was related to the acceleration and the jerk normof the cane at the terminal contact and the time of the cane touching the ground. Step length was related to the cane angle in the sagittal plane at the initial contact and terminal contact, the acceleration normand the jerk normat the terminal contact, and the maximum angular velocity while swinging the cane. These findings proved that the IMU attached to the cane could measure the indicators related to walking ability. [ABSTRACT FROM AUTHOR]

People adjust their gait by interacting with the surrounding environment. Thus, hidden factors in the environment such as fall risk that influence the gait can be exposed by measuring its change during daily walking. For this purpose, in this paper, we employed wearable IMU sensors that enables measurement of stride length and stride time of the pedestrian without environment fixed MoCap system. We also used the GPS receiver for measuring the global position of the pedestrian simultaneously, since the IMU sensors only offer a local change of the gait. The change of the stride length and the stride time were calculated from the IMU sensors and mapped onto the geographic map referring to the GPS data for constructing the Geographical Information System (GIS) of the gait. These gait indices changed according to the type of the walkway, plane, stair, and slope. Also, even in the same walkway, the indices changed by the environmental factors such as obstacles, walking direction and traffic light. The experimental results suggest that measurement of the gait during daily walking in the daily environment seemed to have the potential to expose the factors hidden in the environment such as the fall risk that influence the gait.