Absiract -The purpose of this study was to analyze the kinematics and EMG of backward walking on treadmill. There were sixteen health male subjects, aged 21-29 years, volunteered to participate in this study. The Infortronic Ultraflex Gait Analysis System was used to record the data of the five different walking patterns, including forward walking on level ground (F.W.), backward walking on level ground (B.W.), forward walking on treadmill (F.W.T.), backward walking on treadmill (B.W.T.), and backward walking on inclined 10% treadmill (B.W.T.I.).In this study, we found that backward walking on inclined treadmill was the most stable pattern and the increased average muscle activity was noted. Backward walking on inclined treadmill may serve to further enhance the positive effects of backward walking on a flat surface.
Image recognition technology plays an important role in advanced driver assistance systems (ADAS). The objective of this study is to explore the feasibility of using heterogeneous image fusion to improve the object detection performance of the ADAS. Among the many possible combinations of image types, the fusion of infrared (IR) and visible (VIS) images has great potential because of their complementary characteristics. Most studies on image fusion assume that the images involved align themselves perfectly, which is unrealistic. We address this alignment issue in this study, review various methods of image alignment and fusion, and propose an image-fusion approach that combines alignment and fusion methods for the ADAS application. Finally, we used deep learning networks to detect pedestrian and vehicle objects before and after the image fusion. The experimental results show that the fusion of IR and VIS images can improve the object detection performance of deep-learning networks. Compared with previous studies on fusion, the proposed approach ranks top if the detection accuracy improvement and execution speed are considered as a whole. This study also found that, to use image fusion to improve the object detection accuracy of deep learning networks, it is better to use fused images directly instead of unfused VIS images as the training samples.
This study examines the validity of the Sensory Balance Test (SBT), which uses the technology of computerized dynamic posturography, to screen children for sensory processing impairments. Twenty typically developing children and 20 children with sensory processing impairments were administered the SBT under six different sensory conditions. The results show that children's sensory balance composite scores (SBT summary score) are associated with their sensory processing functioning status (adjusted odds ratio = 0.97; 95% confidence interval = [0.95, 0.99], p = .004). Children's sensory balance composite scores, together with age and gender, successfully predicted their current sensory processing functioning status as the predicted status had excellent agreement with children's current status (Kappa = 0.80). Typically developing children performed significantly better than children with sensory processing impairments while tested under sensory conflict conditions. Findings from this study support that the SBT is an appropriate and effective tool to screen children for possible sensory processing impairments.
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