Study and Design of Distributed Badminton Agility Training and Test System

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Abstract

In order to improve the agility of college students, this paper designs a distributed agility training system. The system includes an upper computer and nine lower computers, in which the lower computer realizes the functions of data acquisition and communication with the upper computer and calculates the reaction time. The Android-based system software was installed in the upper computer to complete the functions of network connection, setting training times and showing the exercise time. In order to test the effectiveness of the equipment, nine university students were invited to complete agility training over 8 weeks with the help of agility training equipment in preparatory, enhancement and special stages. A t-test (Student’s t test) was conducted on the test results at different positions on the front and middle and back areas of the court before and after the training. The results show that the agility of the experimental objects was significantly improved after training, from the midpoint to any point at the front, middle and back court (p < 0.01). This shows that using equipment designed to develop agility for long-term training can promote the sensitive quality in badminton learners.

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Balance training for neuromuscular control and performance enhancement: a systematic review.

Astrid Zech, Markus Hübscher, Lutz Vogt … (2016)

As a result of inconsistencies in reported findings, controversy exists regarding the effectiveness of balance training for improving functional performance and neuromuscular control. Thus, its practical benefit in athletic training remains inconclusive. Our objective was to evaluate the effectiveness of training interventions in enhancing neuromuscular control and functional performance. Two independent reviewers performed a literature search in Cochrane Bone, Joint and Muscle Trauma Group Register and Cochrane Controlled Trials Register, MEDLINE, EMBASE, PEDro (Physiotherapy Evidence Database), and SCOPUS. Randomized controlled trials and controlled trials without randomization with healthy and physically active participants aged up to 40 years old were considered for inclusion. Outcomes of interest were postural control, muscle strength, agility, jump performance, sprint performance, muscle reflex activity, rate of force development, reaction time, and electromyography. Data of interest were methodologic assessment, training intervention, outcome, timing of the outcome assessment, and results. Standardized mean differences and 95% confidence intervals were calculated when data were sufficient. In total, 20 randomized clinical trials met the inclusion criteria. Balance training was effective in improving postural sway and functional balance when compared with untrained control participants. Larger effect sizes were shown for training programs of longer duration. Although controversial findings were reported for jumping performance, agility, and neuromuscular control, there are indications for the effectiveness of balance training in these outcomes. When compared with plyometric or strength training, conflicting results or no effects of balance training were reported for strength improvements and changes in sprint performance. We conclude that balance training can be effective for postural and neuromuscular control improvements. However, as a result of the low methodologic quality and training differences, further research is strongly recommended.

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Spatio-temporal Laplacian pyramid coding for action recognition.

Ling Shao, Xiantong Zhen, Dacheng Tao … (2014)

We present a novel descriptor, called spatio-temporal Laplacian pyramid coding (STLPC), for holistic representation of human actions. In contrast to sparse representations based on detected local interest points, STLPC regards a video sequence as a whole with spatio-temporal features directly extracted from it, which prevents the loss of information in sparse representations. Through decomposing each sequence into a set of band-pass-filtered components, the proposed pyramid model localizes features residing at different scales, and therefore is able to effectively encode the motion information of actions. To make features further invariant and resistant to distortions as well as noise, a bank of 3-D Gabor filters is applied to each level of the Laplacian pyramid, followed by max pooling within filter bands and over spatio-temporal neighborhoods. Since the convolving and pooling are performed spatio-temporally, the coding model can capture structural and motion information simultaneously and provide an informative representation of actions. The proposed method achieves superb recognition rates on the KTH, the multiview IXMAS, the challenging UCF Sports, and the newly released HMDB51 datasets. It outperforms state of the art methods showing its great potential on action recognition.