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Titlebook: Body Area Networks. Smart IoT and Big Data for Intelligent Health Management; 16th EAI Internation Masood Ur Rehman,Ahmed Zoha Conference p

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發(fā)表于 2025-3-21 18:18:30 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Body Area Networks. Smart IoT and Big Data for Intelligent Health Management
期刊簡(jiǎn)稱16th EAI Internation
影響因子2023Masood Ur Rehman,Ahmed Zoha
視頻videohttp://file.papertrans.cn/190/189534/189534.mp4
學(xué)科分類Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engi
圖書封面Titlebook: Body Area Networks. Smart IoT and Big Data for Intelligent Health Management; 16th EAI Internation Masood Ur Rehman,Ahmed Zoha Conference p
影響因子.This book constitutes the refereed post-conference proceedings of the 16.th .International Conference on Body Area Networks, BodyNets 2021, held in October 2021. The conference was held virtually due to the COVID-19 pandemic.. The 21 papers presented were selected from 44 submissions and issue new technologies to provide trustable measuring and communications mechanisms from the data source to medical health databases. Wireless body area networks (WBAN) are one major element in this process. Not only on-body devices but also technologies providing information from inside a body are in the focus of this conference. Dependable communications combined with accurate localization and behavior analysis will benefit WBAN technology and make the healthcare processes more effective..
Pindex Conference proceedings 2022
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Monitoring Discrete Activities of Daily Living of Young and Older Adults Using 5.8?GHz Frequency Mod is to monitor activities of daily living using the publicly available dataset recorded in nine different geometrical locations for ninety-nine volunteers including young and older adults (65+) using 5.8?GHz Frequency Modulated Continuous Wave (FMCW) radar. In this work, we experimented with discret
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Wireless Sensing for Human Activity Recognition Using USRPincluding intrusion detection, healthcare and so on. Radio Frequency (RF) signal when propagating through the wireless medium encounters reflection and this information is stored when signals reach the receiver side as Channel State information (CSI). This paper develops an intelligent wireless sens
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Detecting Alzheimer’s Disease Using Machine Learning Methods dementia with Alzheimer’s disease is expected to increase rapidly in the next few years. Currently, healthcare systems require an accurate detection of the disease for its treatment and prevention. Therefore, it has become essential to develop a framework for early detection of Alzheimer’s disease
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FPGA-Based Realtime Detection of Freezing of Gait of Parkinson Patientso compare our results with state of the art solutions we used the well-known open dataset Daphnet. Our most important findings are even though we used a tool to map the trained model to the FPGA we can detect FoG in less than a millisecond which will give us sufficient time to trigger cueing and by
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Received WiFi Signal Strength Monitoring for Contactless Body Temperature Classificationeading. This work explores an alternative way of classifying temperature using the ubiquitous WiFi waveform. By merely observing the change in the received signal strength indicator (RSSI), body temperature can be classified as below normal, normal, or warm. Using a smartphone as the receiver and a
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