Design and Research of Remote Monitoring System for Sports Injury Rehabilitation Training

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Abstract

In order to study the sports injuries that often occur in athletes’ training and competition and solve the problems of low monitoring accuracy of injury mode data and large difference of resistance signal waveforms in the traditional monitoring system, this paper proposes the application of wireless sensor network in monitoring process. The accuracy of data monitoring with 9 different degree injury modes set by 1–9 squares in the traditional system is lower, while the accuracy of sports injury rehabilitation monitoring based on wireless sensor network is higher, which can be maintained above 90%. The experimental results show that the monitoring system has high monitoring accuracy of damage mode data and small difference of resistance signal waveform. It is basically consistent with the actual waveform.

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A Systematic Review of Landsat Data for Change Detection Applications: 50 Years of Monitoring the Earth

MohammadAli Hemati, Mahdi Hasanlou, Masoud Mahdianpari … (2021)

With uninterrupted space-based data collection since 1972, Landsat plays a key role in systematic monitoring of the Earth’s surface, enabled by an extensive and free, radiometrically consistent, global archive of imagery. Governments and international organizations rely on Landsat time series for monitoring and deriving a systematic understanding of the dynamics of the Earth’s surface at a spatial scale relevant to management, scientific inquiry, and policy development. In this study, we identify trends in Landsat-informed change detection studies by surveying 50 years of published applications, processing, and change detection methods. Specifically, a representative database was created resulting in 490 relevant journal articles derived from the Web of Science and Scopus. From these articles, we provide a review of recent developments, opportunities, and trends in Landsat change detection studies. The impact of the Landsat free and open data policy in 2008 is evident in the literature as a turning point in the number and nature of change detection studies. Based upon the search terms used and articles included, average number of Landsat images used in studies increased from 10 images before 2008 to 100,000 images in 2020. The 2008 opening of the Landsat archive resulted in a marked increase in the number of images used per study, typically providing the basis for the other trends in evidence. These key trends include an increase in automated processing, use of analysis-ready data (especially those with atmospheric correction), and use of cloud computing platforms, all over increasing large areas. The nature of change methods has evolved from representative bi-temporal pairs to time series of images capturing dynamics and trends, capable of revealing both gradual and abrupt changes. The result also revealed a greater use of nonparametric classifiers for Landsat change detection analysis. Landsat-9, to be launched in September 2021, in combination with the continued operation of Landsat-8 and integration with Sentinel-2, enhances opportunities for improved monitoring of change over increasingly larger areas with greater intra- and interannual frequency.