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

      research-article
      Author(s): , ,
      Publication date (Electronic):
      Journal: Journal of Healthcare Engineering
      Publisher: Hindawi

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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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          Most cited references23

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          The KIMORE dataset: KInematic assessment of MOvement and clinical scores for remote monitoring of physical REhabilitation

          Marianna Capecci, Maria Ceravolo, Francesco Ferracuti … (2019)
          Article 0 comments Cited 16 times – based on 0 reviews     Review now
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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.
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              Design and Development of an Arduino Based Data Logger for Photovoltaic Monitoring System

              Najwa Nasuha Mahzan (2016)
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                Author and article information

                Contributors
                Ruiming Qi:
                ORCID: https://orcid.org/0000-0002-4228-8802
                Journal
                Journal ID (nlm-ta): J Healthc Eng
                Journal ID (iso-abbrev): J Healthc Eng
                Journal ID (publisher-id): JHE
                Title: Journal of Healthcare Engineering
                Publisher: Hindawi
                ISSN (Print): 2040-2295
                ISSN (Electronic): 2040-2309
                Publication date Collection: 2021
                Publication date (Electronic): 27 September 2021
                Volume: 2021
                Electronic Location Identifier: 4390089
                Affiliations
                Department of Physical Education, Hebei Academy of Fine Arts, Hebei 050700, China
                Author notes

                Academic Editor: Balakrishnan Nagaraj

                Author information
                https://orcid.org/0000-0002-2414-4725
                https://orcid.org/0000-0001-8859-5683
                https://orcid.org/0000-0002-4228-8802
                Article
                DOI: 10.1155/2021/4390089
                PMC ID: 8490025
                PubMed ID: 34616532
                SO-VID: edcf8784-11c5-4d7a-8a2b-d0d0b48c37c8
                Copyright © Copyright © 2021 Hongyan Liu et al.
                License:

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 16 July 2021
                Date accepted : 2 September 2021
                Categories
                Subject: Research Article

                Data availability:

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