Comparison of TrackMan Data between Professional and Amateur Golfers at Swinging to Uphill and Downhill Fairways

Background: Golfers face different environmental conditions in each game played under various constraints. Enhancing affordances through training in a constrained outdoor environment is crucial. Objective: To analyze club head behavior at ball impact of a tee shot by 42 professional (PGs) and 25 amateur (AGs) golfers in swinging to uphill and downhill fairway environments using the TrackMan portable launch monitor. Methods: We used TrackMan to compare golf club movement adaptations in 42 PGs and 25 AGs. A 330-m driving range facing both the uphill (+5°) and downhill (-5°) fairways were used. The tee shot area was the only flat ground surface, with the uneven ground between the shot area and the 200-yard fairway. Results: The clubhead speed and attack angle were significantly higher among PGs than among AGs. PGs could adapt their swings to the uphill fairway by increasing the attack angle (3.6°±2.4) by 3.3° compared with the downhill fairway. The attack angle did not correlate with the launch angle among the AGs in the downhill condition, suggesting that they were unable to control the height of the ball based on the far side of the fairway. Conclusion: PGs increased the attack angle in uphill conditions, and their awareness of the affordance, which was different from that of AGs, allowed them to change the optimal ball trajectory to avoid perceived fairway risks. Thus, the more skill a player had, the better he was at recognizing the affordance of the visual field. PGs demonstrated a better ability to adapt to environmental constraints.

Design and analysis of a six-wheeled companion robot with mechanical obstacle-overcoming adaptivity

A six-wheeled companion exploration robot with an adaptive climbing mechanism is proposed and released for the complicated terrain environment of planetary exploration. Benefiting from its three-rocker-arm structure, the robot can adapt to complex terrain with its six wheels in contact with the ground during locomotion, which improves the stability of the robot. When the robot moves on the flat ground, it moves forward through the rotation of the wheels. When it encounters obstacles in the process of moving forward, the front obstacle-crossing wheels hold the obstacle, and the rocker arms on both sides rotate themselves with mechanical adaptivity to drive the robot to climb and cross the obstacle like crab legs. Furthermore, a parameterized geometric model is established to analyze the motion stability and the obstacle-crossing performance of the robot. To investigate the feasibility and correctness of design theory and robot scheme, a group of design parameters of the robot are determined. A prototype of the robot is developed, and the experiment results show that the robot can maintain stability in rugged terrain environments and has a certain ability to surmount obstacles.

Dimensionality Reduction of Human Gait for Prosthetic Control

We seek to use dimensionality reduction to simplify the difficult task of controlling a lower limb prosthesis. Though many techniques for dimensionality reduction have been described, it is not clear which is the most appropriate for human gait data. In this study, we first compare how Principal Component Analysis (PCA) and an autoencoder on poses (Pose-AE) transform human kinematics data during flat ground and stair walking. Second, we compare the performance of PCA, Pose-AE and a new autoencoder trained on full human movement trajectories (Move-AE) in order to capture the time varying properties of gait. We compare these methods for both movement classification and identifying the individual. These are key capabilities for identifying useful data representations for prosthetic control. We first find that Pose-AE outperforms PCA on dimensionality reduction by achieving a higher Variance Accounted For (VAF) across flat ground walking data, stairs data, and undirected natural movements. We then find in our second task that Move-AE significantly outperforms both PCA and Pose-AE on movement classification and individual identification tasks. This suggests the autoencoder is more suitable than PCA for dimensionality reduction of human gait, and can be used to encode useful representations of entire movements to facilitate prosthetic control tasks.

A small footprint printed cross-dipole antenna with wide impedance bandwidth and circular polarization

Wideband circularly polarized (CP) cross-dipole antennas with flat, cavity and artificial magnetic conductor (AMC) reflectors are proposed. Each proposed antenna consists of a pair of driven dipoles, a pair of vacant-quarter printed rings, and a 50Ω coaxial probe. The boomerang shape has been adopted in the crossed-dipole. This shape makes the design more compact, so it can be a good candidate in the antenna array because of reducing the mutual coupling. All numerical simulation works have been done using the ANSYS electromagnetic (EM) software based on the finite element method (FEM) algorithm. The presented crossed-dipole with a cavity has the best performance compared to ones with conventional flat and AMC grounds. However, the crossed-dipole with the AMC ground is a low-profile structure. Thus, the paper investigates and discusses the results of the proposed strctures thoroughly. The obtained impedance bandwidth (IBW) is 42% (5.1-7.85 GHz) and the axial-ratio bandwidth (ARBW) is 7.72% (5.86-6.32 GHz) for the crossed-dipole with the conventional flat ground (i.e., reflector). Furthermore, the IBW and ARBW for the antenna with the cavity reflector are 50.37% (5.08-8.5 GHz) and 26.4% (5.72-7.46 GHz), respectively. The antenna with the AMC ground has the characterstics of the IBW and ARBW as 38.16% (5.36-7.89 GHz) and 15.16% (5.79-6.74 GHz), respectively. All structures are designed to operate for the C-band and wireless local area networks (WLAN) applications.

The classification of skateboarding tricks via transfer learning pipelines

This study aims at classifying flat ground tricks, namely Ollie, Kickflip, Shove-it, Nollie and Frontside 180, through the identification of significant input image transformation on different transfer learning models with optimized Support Vector Machine (SVM) classifier. A total of six amateur skateboarders (20 ± 7 years of age with at least 5.0 years of experience) executed five tricks for each type of trick repeatedly on a customized ORY skateboard (IMU sensor fused) on a cemented ground. From the IMU data, a total of six raw signals extracted. A total of two input image type, namely raw data (RAW) and Continous Wavelet Transform (CWT), as well as six transfer learning models from three different families along with grid-searched optimized SVM, were investigated towards its efficacy in classifying the skateboarding tricks. It was shown from the study that RAW and CWT input images on MobileNet, MobileNetV2 and ResNet101 transfer learning models demonstrated the best test accuracy at 100% on the test dataset. Nonetheless, by evaluating the computational time amongst the best models, it was established that the CWT-MobileNet-Optimized SVM pipeline was found to be the best. It could be concluded that the proposed method is able to facilitate the judges as well as coaches in identifying skateboarding tricks execution.

Effects of Individualized Gait Rehabilitation Robotics for Gait Training on Hemiplegic Patients: Before-After Study in The Same Person

Background : Lower-limb exoskeleton robots are being widely used in gait rehabilitation training for stroke patients. However, most of the current rehabilitation robots are guided by predestined gait trajectories, which are often different from the actual gait trajectories of specific patients. One solution is to train patients using individualized gait trajectories generated from the physical parameters of patients. Hence, we aimed to explore the effect of individual gaits on energy consumption situation during gait rehabilitation training for hemiplegic patient with low-limb exoskeleton robot.Methods : 9 unilateral-hemiplegic patients were recruited. On the first day of the experiment, the 9 patients were guided by a low-limb exoskeleton robot, walking on a flat ground for 15 minutes in general gait trajectory, which was gained by CGA (clinical gait analysis) method.On the other day, the same 9 patients wore the identical robot and walked on the same flat ground for 15 minutes in individualized gait trajectory. The main physiological parameters including heart rate (HR) and peripheral capillary oxygen saturation (SpO2) were acquired via cardiotachometer and oximeter before and after the walking training. The energy consumption situation was indicated by the variation of the value of HR and SpO2 after walking training compared to before.Results : Between-group comparison shows that the individualized gait trajectory training results in lower increase in HR levels and decrease in SpO2 levels in experimenters compared to general gait trajectory training. Difference has statistical significance(p<0.05).Conclusions : Using individualized gait guidance in rehabilitation walking training can significantly improve energy efficiency for hemiplegic patient with stroke.Trial registration: Registered on 29 July 2021 at Chinese Clinical Trial Registry (ChiCTR2100049310). https://www.chictr.org.cn/edit.aspx?pid=130960\&htm=4

Studies for Frost Heave Characteristics and the Prevention of the High-Speed Railway Roadbed in the Zoige Wetland, China

The Xining–Chengdu high-speed railway crosses the Zoige Wetland, located on the northeast edge of the Qinghai-Tibet Plateau and the upper reaches of the Yellow River. The cold climate and frost-heave-sensitive subgrade soil cause a large frost heave deformation of the roadbed, threatening the safety of trains. This article systematically studied the ground temperature development, frost heave characteristics, soil water content, and groundwater level variations by field investigation and monitoring. The maximum frost heave deformations of the natural flat ground and hillslope reached 25.64 and 3.17 mm, respectively, and this significant discrepancy was mainly caused by the groundwater supply conditions. Future roadbed stability on the flat ground may be compromised by frost heave deformation. To solve this problem, contrasting indoor tests were conducted to analyze the frost heave characteristics of natural ground clay and replacement coarse-grained soil (CGS). It was shown that the absorbed external water mainly changed into dispersed pore ice in the freezing CGS, while it mainly changed into the layered ice lens in the freezing clay. Further tests showed that the frost susceptibility of the CGS was proportional to the fines content and initial water content. The poorly graded CGS had weaker frost susceptibility than the well-graded CGS. The results suggest that anti-frost methods should be fully considered, including strict control of fines content and water content, prioritizing the use of poorly graded filling, and disruption of local water accumulation in the filling layer.

Barrier-Free Wheelchair with a Mechanical Transmission

Wheelchairs are an important means of transportation for the elderly and disabled. However, the movement of wheelchairs on long curbs and stairs is restricted. In this study, a wheelchair for climbing stairs was developed based on a mechanical transmission system that rotates the entire driving part through a link structure and an actuator to change the speed. The first mode drives the caterpillar, and the second mode drives the wheels. When driving on flat ground, it uses landing gears and wheels, and when climbing stairs, it uses the caterpillar; accordingly, a stable driving is possible. The stability of the transmission is confirmed through stress analysis. The method used in our study makes it is possible to manufacture lightweight wheelchairs because a single motor drives both the wheel and caterpillar through the transmission system.