2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT)最新文献_第2页

A Preliminary Study of On/Off-Body Propagation Channels for Brain Telemetry Using a Flexible Wearable Antenna 基于柔性可穿戴天线的脑遥测在身/离体传播信道初步研究

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152221

Mariella Särestöniemi, K. Sayrafian-Pour, M. Sonkki, J. Iinatti

{"title":"A Preliminary Study of On/Off-Body Propagation Channels for Brain Telemetry Using a Flexible Wearable Antenna","authors":"Mariella Särestöniemi, K. Sayrafian-Pour, M. Sonkki, J. Iinatti","doi":"10.1109/ISMICT58261.2023.10152221","DOIUrl":"https://doi.org/10.1109/ISMICT58261.2023.10152221","url":null,"abstract":"Flexible electronics are envisioned to play a major role in future wearable medical devices. An important component of this technology is flexible antennas. This paper presents a preliminary study of on-body and off-body propagation channels in Body Area Networks (BAN) using a small Ultra WideBand (UWB) flexible wearable antenna. The research is carried out with physical measurements in an anechoic chamber and a small laboratory room. The on-body measurements include propagation channels between two wearable devices placed on the head and various locations on the arm (i.e., shoulder to wrist). The off-body measurements cover propagation channels between a head-mounted device and an external device placed at various distances from the body. The wearable devices in these measurements use a small flexible antenna that can easily conform to the surface of the body. The measurements are conducted to better understand and characterize the wireless communication channels in applications such as brain monitoring or brain computer interface. The measurement results show that the UWB flexible antenna presented here performs well for both on-body and off-body communication channels.","PeriodicalId":332729,"journal":{"name":"2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125190371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimation of Source Direction with Spherical Array Receiver in Molecular Communication 分子通信中球形阵列接收机的源方向估计

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152165

Fardad Vakilipoor, Abdulhamid N. M. Ansari, M. Ferrari, Maurizio Magarini

引用次数: 0

Real-Time Mastitis Detection in Livestock using Deep Learning and Machine Learning Leveraging Edge Devices 利用边缘设备进行深度学习和机器学习的牲畜乳腺炎实时检测

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152110

Kawshik Kumar Ghosh, Md. Fahim Ul Islam, Abrar Ahsan Efaz, Amitabha Chakrabarty, Shahriar Hossain

{"title":"Real-Time Mastitis Detection in Livestock using Deep Learning and Machine Learning Leveraging Edge Devices","authors":"Kawshik Kumar Ghosh, Md. Fahim Ul Islam, Abrar Ahsan Efaz, Amitabha Chakrabarty, Shahriar Hossain","doi":"10.1109/ISMICT58261.2023.10152110","DOIUrl":"https://doi.org/10.1109/ISMICT58261.2023.10152110","url":null,"abstract":"Livestock production is a crucial part of the global economy with a worth of estimated $1.4 trillion. It provides livelihoods for 1.3 billion people and supports 600 million poor rural household farmers in developing countries. In Bangladesh, it contributes 6.5% to the country's GDP. However, this industry faces substantial financial setbacks when contagious diseases transmit among their livestock. One of the most common and expensive diseases affecting the livestock industry is Bovine Mastitis. This paper presents a real-time system for detecting bovine mastitis in livestock using deep learning (dl) and machine learning (ml) techniques. The system aims to provide a timely and accurate diagnosis of mastitis, ultimately reducing costs and improving the efficiency of treatment. By utilizing dl and ml techniques, the system is able to analyze data collected from edge devices and make accurate predictions about the presence of mastitis. The dataset that has been used for the classification contains both an Image dataset consisting of 1341 images and a Numerical dataset that had been taken from 1100 cows over a period of six days. The edge device utilizes sensors and cameras to collect data from the cow, which is then processed through ml and dl algorithms using Raspberry Pi and cloud computing respectively, and then displays if the cow is infected with mastitis or not. Inception V3 and RandomForest algorithms were used for dl and ml, respectively, and had an accuracy of 99.34% and 99% respectively. The proposed system has the potential to significantly reduce the economic impact of this disease in the dairy industry of Bangladesh and other developing countries by providing timely and accurate diagnosis and helping to improve treatment efficiency and protect the health and productivity of livestock animals.","PeriodicalId":332729,"journal":{"name":"2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116321599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Received Power via RIS in Near Field LOS Channels 近场LOS信道中RIS接收功率分析

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152132

J. Kokkoniemi

引用次数: 0

Recent Progress in ETSI TC SmartBAN Standardization ETSI TC SmartBAN标准化最新进展

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152168

M. Hämäläinen, L. Mucchi, Tuomas Paso, D. Anzai, Hirokazu Tanaka, C. Lanting, Marco Hernandez

引用次数: 0

Visible Light Communications for Healthcare Applications: Opportunities and Challenges 医疗保健应用的可见光通信:机遇与挑战

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152290

S. Caputo, Giacomo Borghini, S. Jayousi, Adnan Rashid Chaudhry, L. Mucchi

引用次数: 0

Security of Wireless Body Area Networks for Healthcare Applications: Comparison between ETSI and IEEE Approaches 用于医疗保健应用的无线体域网络的安全性:ETSI和IEEE方法的比较

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152140

Giacomo Borghini, S. Caputo, L. Mucchi, Adnan Rashid Chaudhry, S. Jayousi, M. Hämäläinen, Tuomas Paso, Marco Hernandez

引用次数: 0

Reinforcement Learning based Cloud and Edge Resource Allocation for Real-Time Telemedicine 基于强化学习的实时远程医疗云和边缘资源分配

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152231

Ivana Kovacevic, Rana Inzimam Ul Haq, Jude Okwuibe, T. Kumar, S. Glisic, M. Ylianttila, E. Harjula

{"title":"Reinforcement Learning based Cloud and Edge Resource Allocation for Real-Time Telemedicine","authors":"Ivana Kovacevic, Rana Inzimam Ul Haq, Jude Okwuibe, T. Kumar, S. Glisic, M. Ylianttila, E. Harjula","doi":"10.1109/ISMICT58261.2023.10152231","DOIUrl":"https://doi.org/10.1109/ISMICT58261.2023.10152231","url":null,"abstract":"Future healthcare services will extensively exploit wireless telehealth solutions in various healthcare use cases from preventive home monitoring to highly demanding real-time scenarios, such as monitoring an emergency patient's vital functions in an ambulance or ICU unit. Reliable real-time communications and computing are needed to enable these highly critical health services. However, the majority of current telehealth use cases are cloud - based, which poses a challenge to provide sufficient Quality of Service (QoS). The traditional centralized cloud infrastructure cannot meet the latency and reliability requirements due to long and unreliable communication routes. Therefore, the most advanced cloud solutions integrate edge computing as an integral part of the computational architecture to bring a part of the computational infrastructure to the proximity of the data sources and end-nodes, thus constituting an edge-cloud continuum. This continuum is capable of serving applications with real-time requirements. However, since edge computing capacity is a limited resource, solutions are needed for deciding which tasks should be run on edge and which at the data center. In this paper, we propose a machine learning-based solution to prioritize ultra-low-latency tasks for running on the edge to meet their strict delay requirements while leaving other tasks to be executed at remote servers. Our proposed solution in comparison to the baseline has a significantly lower dropping rate and outperforms fixed - interval scheduling solutions in terms of resource efficiency.","PeriodicalId":332729,"journal":{"name":"2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131250300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulation and Implementation of an IoT-based Secure Smart Biology Laboratory for Smart Cities 基于物联网的智慧城市安全智能生物实验室的仿真与实现

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152089

N. Alsbou, Reuben Lane, Lalita Gurung, Imad Ali

引用次数: 0

Medical Imaging System Design using Microwave Antennas and Portable Platform 基于微波天线和便携式平台的医学成像系统设计

2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT) Pub Date : 2023-05-10 DOI: 10.1109/ISMICT58261.2023.10152069

N. Alsbou, Karidjatou Cisse, Colton Cox, Mubaraak Akinbola, Imad Ali

{"title":"Medical Imaging System Design using Microwave Antennas and Portable Platform","authors":"N. Alsbou, Karidjatou Cisse, Colton Cox, Mubaraak Akinbola, Imad Ali","doi":"10.1109/ISMICT58261.2023.10152069","DOIUrl":"https://doi.org/10.1109/ISMICT58261.2023.10152069","url":null,"abstract":"When discussing medical imaging systems, microwave imaging is considered one of the emerging techniques that provide fast, safe, cost effective and noninvasive medical imaging modality compared to other conventional imaging techniques such as x-ray, magnetic resonance imaging (MRI), and computed tomography imaging (CT). The imaging in microwave imaging system can be performed by mapping the interactions of microwave photons with the medium including signal reflection, attenuation and propagation. These factors are dependent on the water or blood content of the tissue. The maps of electromagnetic properties of the tissue generated with microwave imaging is used to generate medical images for different clinical applications such as leukemia, bone degradation, tumor and traumatic brain injury (TBI) detection. This paper proposes a medical imaging system that is able to produce three-dimensional images in a much safer and cheaper way compared to conventional imaging methods. The medical imaging system proposed is a work in progress and this paper is intended to outline the design and show the preliminary medical images obtained.","PeriodicalId":332729,"journal":{"name":"2023 IEEE 17th International Symposium on Medical Information and Communication Technology (ISMICT)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131467304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0