Qingkai  Zhen

Dr. Qingkai Zhen


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 February 2018 in Proceedings
Verified
Conference Paper
Open access
PDF file
QHQi Hu
Qi Hu
QCQi Chen
Qi Chen
YLYongqing Liu
Yongqing Liu
QZQingkai Zhen
Qingkai Zhen
In the sport science fields, for a long time there are various attempts to explore more advanced technology in order to collect kinds of information concerned during athletes training and matches. In the paper, a footwork training and testing system has been developed by adopting the advanced technology of Wireless Sensor Network (WSN). The system is comprised of some wireless senor nodes and gateways, system control software and so on. By means of the system, the daily footwork training methods and modes will be simulated to automatically guide the training of the athletes, at the same time the training data concerned will be automatically recorded, including moving velocity, moving frequency and success average, moving exercise duration and so on, and it is facilitate to evaluate digitally the training and testing effects for coaches and athletes. The system will bring about an auxiliary means in sport science training and research, make coaches and researchers have more options for the technical and information forms, and provide the technology foundation for synchronizing and intermingling the training and testing smoothly.

12 February 2018 in Proceedings
Verified
Conference Paper
Open access
PDF file
QZQingkai Zhen
Qingkai Zhen
YLYongqing Liu
Yongqing Liu
QHQi Hu
Qi Hu
QCQi Chen
Qi Chen
The number of steps can be used to measure the distance, intensity, frequency, and oxygen consumption of the human activities indirectly, it has great significance to evaluate the amount of human movement. Different from traditional methods which based on wearable sensors, video based methods have the advantages of non-contact. In this paper, we propose a novel infrared video based accurate step counting algorithm for treadmills. Our approach is mainly divided into two parts, e.g., shoulder tracking and step counting. Shoulder movement is less disturbed and can accurately reflect the gait information than other body parts in the processing of running. By tracking the position of the shoulder in the image sequence, and analyzing the peaks and troughs of the trajectory, we can calculate the number of steps accurately in real time. The experiments are conducted on our own datasets, and the result achieved clearly demonstrate the effectiveness of the proposed method.