Journal of neuroengineering and rehabilitation
34461938
BACKGROUND: Human beings can enhance their distance running performance with the help of assistive devices. Although several such devices are available, they are heavy and bulky, which limits their use in everyday activities. In this study, we develo...
Aiming at the crossing problem of complex terrain, to further improve the ability of obstacles crossing, this paper designs and develops an all-terrain wheel-legged hybrid robot (WLHR) with strong adaptability to the environment. According to the ope...
Uneven terrain in natural environments challenges legged locomotion by inducing instability and causing limb collisions. During the swing phase, the limb releases from the ground and arcs forward to target a secure next foothold. In natural environme...
The locomotion performance of the current legged miniature robots remains inferior compared to even the most simple insects. The inferiority has led researchers to utilize biological principles and control in their designs, often resulting in improve...
Due to the wide application of human activity recognition (HAR) in sports and health, a large number of HAR models based on deep learning have been proposed. However, many existing models ignore the effective extraction of spatial and temporal featur...
Greater understanding of differences in technique between runners may allow more beneficial feedback related to improving performance and decreasing injury risk. The purpose of this study was to develop and test a support vector machine classifier, w...
Running gait patterns have implications for revealing the causes of injuries between higher-mileage runners and low-mileage runners. However, there is limited research on the possible relationships between running gait patterns and weekly running mil...
The transition from the lab to natural environments is an archetypal challenge in robotics. While larger robots can manage complex limb-ground interactions using sensing and control, such strategies are difficult to implement on small platforms where...
Recent advances in both lightweight deep learning algorithms and edge computing increasingly enable multiple model inference tasks to be conducted concurrently on resource-constrained edge devices, allowing us to achieve one goal collaboratively rath...