一种用于无线体域网络睡眠姿势识别的增强型姿势预测贝叶斯网络算法

IF 3.1 Q2 HEALTH CARE SCIENCES & SERVICES
A. Roshini, K. Kiran
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引用次数: 3

摘要

无线身体区域网络在提供一致的健康监测设施方面获得了独特的认可。几项研究通过在站立、行走、坐着和跑步等被视为活动姿势的常规活动中使用星形拓扑结构的集中方法来影响生理信号监测。与散步、站立、坐着和跑步等常规活动不同,对于那些接受过手术的人、呼吸问题的受害者和新冠肺炎患者来说,床上睡眠姿势监测是非常必要的,因为无人看管的患者导致睡眠中的死亡率很高,因此氧气失衡是他们的主要问题。医学界的建议指出,强烈建议有上述问题的患者采用俯卧的睡眠姿势,以保持人体内的氧气水平。使用分布式通信模型,其中网状拓扑用于以中继方式传送到信宿的数据分组。密切监测受试者在睡眠期间的心跳率(HBR)和图像监测,并将其作为所提出的姿势预测贝叶斯网络(PP-BN)的输入,以预测连续的姿势,从而提高姿势识别的准确率。该模型的准确率优于现有的分类和预测算法,后者以清理后的数据集作为输入,以获得更好的预测结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Enhanced Posture Prediction-Bayesian Network Algorithm for Sleep Posture Recognition in Wireless Body Area Networks
Wireless body area networks have taken their unique recognition in providing consistent facilities in health monitoring. Several studies influence physiological signal monitoring through a centralized approach using star topology in regular activities like standing, walking, sitting, and running which are considered active postures. Unlike regular activities like walking, standing, sitting, and running, the in-bed sleep posture monitoring of a subject is highly necessary for those who have undergone surgery, victims of breathing problems, and victims of COVID-19 for whom oxygen imbalance is a major issue as the mortality rate in sleep is high due to unattended patients. Suggestions from the medical field state that the patients with the above-mentioned issues are highly suggested to follow the prone sleep posture that enables them to maintain the oxygen level in the human body. A distributed model of communication is used where mesh topology is used for the data packets to be carried in a relay fashion to the sink. Heartbeat rate (HBR) and image monitoring of the subject during sleep are closely monitored and taken as input to the proposed posture prediction-Bayesian network (PP-BN) to predict the consecutive postures to increase the accuracy rate of posture recognition. The accuracy rate of the model outperforms the existing classification and prediction algorithms which take the cleaned dataset as input for better prediction results.
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来源期刊
CiteScore
6.90
自引率
2.30%
发文量
19
审稿时长
12 weeks
期刊介绍: The overall aim of the International Journal of Telemedicine and Applications is to bring together science and applications of medical practice and medical care at a distance as well as their supporting technologies such as, computing, communications, and networking technologies with emphasis on telemedicine techniques and telemedicine applications. It is directed at practicing engineers, academic researchers, as well as doctors, nurses, etc. Telemedicine is an information technology that enables doctors to perform medical consultations, diagnoses, and treatments, as well as medical education, away from patients. For example, doctors can remotely examine patients via remote viewing monitors and sound devices, and/or sampling physiological data using telecommunication. Telemedicine technology is applied to areas of emergency healthcare, videoconsulting, telecardiology, telepathology, teledermatology, teleophthalmology, teleoncology, telepsychiatry, teledentistry, etc. International Journal of Telemedicine and Applications will highlight the continued growth and new challenges in telemedicine, applications, and their supporting technologies, for both application development and basic research. Papers should emphasize original results or case studies relating to the theory and/or applications of telemedicine. Tutorial papers, especially those emphasizing multidisciplinary views of telemedicine, are also welcome. International Journal of Telemedicine and Applications employs a paperless, electronic submission and evaluation system to promote a rapid turnaround in the peer-review process.
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