Research on Sports Injury Rehabilitation Detection Based on IoT Models for Digital Health Care.

IF 2.6 4区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Big Data Pub Date : 2024-12-17 DOI:10.1089/big.2023.0134

Zhiyong Wu, Zhida Huang, Nianhua Tang, Kai Wang, Chuanjie Bian, Dandan Li, Vumika Kuraki, Felix Schmid

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引用次数: 0

Abstract

Physical therapists specializing in sports rehabilitation detection help injured athletes recover from their wounds and avoid further harm. Sports rehabilitators treat not just commonplace sports injuries but also work-related musculoskeletal injuries, discomfort, and disorders. Sensor-equipped Internet of Things (IoT) monitors the real-time location of medical equipment such as scooters, cardioverters, nebulizer treatments, oxygenation pumps, or other monitor gear. Analysis of medicine deployment across sites is possible in real time. Health care delivery based on digital technology to improve access, affordability, and sustainability of medical treatment is known as digital health care. The challenging characteristics of such sports injury rehabilitation for digital health care are playing position, game strategies, and cybersecurity. Hence, in this research, health care IoT-enabled body area networks (HIoT-BAN) have been designed to improve sports injury rehabilitation detection for digital health care. The health care sector may benefit significantly from IoT adoption since it allows for enhanced patient safety; health care investment management includes controlling the hospital's pharmaceutical stock and monitoring the heat and humidity levels. Digital health describes a group of programmers made to aid health care delivery, whether by assisting with clinical decision-making or streamlining back-end operations in health care institutions. A HIoT-BAN effectively predicts the rise in sports injury rehabilitation detection with faster digital health care based on IoT. The research concludes that the HIoT-BAN effectively indicates sports injury rehabilitation detection for digital health care. The experimental analysis of HIoT-BAN outperforms the IoT method in terms of performance, accuracy, prediction ratio, and mean square error rate.

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基于物联网模型的数字医疗运动损伤康复检测研究。

专门从事运动康复检测的物理治疗师帮助受伤的运动员从伤口中恢复，避免进一步的伤害。运动康复师不仅治疗常见的运动损伤，还治疗与工作有关的肌肉骨骼损伤、不适和疾病。配备传感器的物联网（IoT）可以监控医疗设备的实时位置，如踏板车、心律转复器、雾化器治疗、氧合泵或其他监控设备。实时分析跨站点的药物部署是可能的。基于数字技术的医疗保健服务旨在改善医疗的可及性、可负担性和可持续性，这被称为数字医疗保健。这种运动损伤康复对数字医疗的挑战特征是比赛位置，比赛策略和网络安全。因此，在本研究中，医疗保健物联网身体区域网络（iot - ban）被设计用于改善数字医疗保健的运动损伤康复检测。医疗保健部门可能会从物联网的采用中受益匪浅，因为它可以提高患者的安全性；医疗保健投资管理包括控制医院的药品库存和监测热量和湿度水平。数字健康描述了一组帮助医疗保健提供的程序，无论是通过协助临床决策还是简化医疗保健机构的后端操作。基于物联网的更快的数字医疗，HIoT-BAN有效地预测了运动损伤康复检测的增长。研究认为，HIoT-BAN有效地为数字医疗的运动损伤康复检测提供了依据。实验分析表明，IoT- ban在性能、准确率、预测比、均方错误率等方面都优于IoT方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

9.10

自引率

2.20%

发文量

期刊介绍： Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.