Healthcom. International Conference on e-Health Networking, Applications and Services最新文献

MDT-based Intelligent Route Selection for 5G-Enabled Connected Ambulances. 基于 MDT 的 5G 互联救护车智能路线选择。

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2022-10-01 Epub Date: 2022-12-21 DOI: 10.1109/healthcom54947.2022.9982778

Muhammad Umar Bin Farooq, Marvin Manalastas, Haneya Qureshi, Yongkang Liu, Ali Imran, Mohamad Omar Al Kalaa

{"title":"MDT-based Intelligent Route Selection for 5G-Enabled Connected Ambulances.","authors":"Muhammad Umar Bin Farooq, Marvin Manalastas, Haneya Qureshi, Yongkang Liu, Ali Imran, Mohamad Omar Al Kalaa","doi":"10.1109/healthcom54947.2022.9982778","DOIUrl":"10.1109/healthcom54947.2022.9982778","url":null,"abstract":"The fifth generation of cellular network (5G) can facilitate in-ambulance patient monitoring, diagnosis, and treatment by a remote specialist. However, 5G coverage and link quality can vary in time and location. The ambulance route selection can help meet the communication requirements of the in-ambulance applications. In this paper, we propose an innovative ambulance route selection framework which combines the communication requirements along with the network coverage and resources. The framework leverages the minimization of drive test (MDT) data to estimate the network coverage along the ambulance routes. To address the uneven distribution of location-based user-generated MDT data, we examine the performance and trustworthiness of several interpolation techniques to enrich the global MDT map for route selection. A simulated analysis shows that the proposed framework can dynamically adapt to varying application requirements as well as rapidly changing network conditions such as outages. Results also reveal that nearest neighbor and kriging interpolation techniques help complement the proposed framework by addressing the data sparsity problem.","PeriodicalId":73224,"journal":{"name":"Healthcom. International Conference on e-Health Networking, Applications and Services","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9846196/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10671688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning Based Autism Spectrum Disorder Detection from Videos. 基于机器学习的自闭症谱系障碍视频检测。

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2021-03-01 Epub Date: 2021-04-14 DOI: 10.1109/healthcom49281.2021.9398924

Chongruo Wu, Sidrah Liaqat, Halil Helvaci, Sen-Ching Samson Cheung, Chen-Nee Chuah, Sally Ozonoff, Gregory Young

{"title":"Machine Learning Based Autism Spectrum Disorder Detection from Videos.","authors":"Chongruo Wu, Sidrah Liaqat, Halil Helvaci, Sen-Ching Samson Cheung, Chen-Nee Chuah, Sally Ozonoff, Gregory Young","doi":"10.1109/healthcom49281.2021.9398924","DOIUrl":"10.1109/healthcom49281.2021.9398924","url":null,"abstract":"Early diagnosis of Autism Spectrum Disorder (ASD) is crucial for best outcomes to interventions. In this paper, we present a machine learning (ML) approach to ASD diagnosis based on identifying specific behaviors from videos of infants of ages 6 through 36 months. The behaviors of interest include directed gaze towards faces or objects of interest, positive affect, and vocalization. The dataset consists of 2000 videos of 3-minute duration with these behaviors manually coded by expert raters. Moreover, the dataset has statistical features including duration and frequency of the above mentioned behaviors in the video collection as well as independent ASD diagnosis by clinicians. We tackle the ML problem in a two-stage approach. Firstly, we develop deep learning models for automatic identification of clinically relevant behaviors exhibited by infants in a one-on-one interaction setting with parents or expert clinicians. We report baseline results of behavior classification using two methods: (1) image based model (2) facial behavior features based model. We achieve 70% accuracy for smile, 68% accuracy for look face, 67% for look object and 53% accuracy for vocalization. Secondly, we focus on ASD diagnosis prediction by applying a feature selection process to identify the most significant statistical behavioral features and a over and under sampling process to mitigate the class imbalance, followed by developing a baseline ML classifier to achieve an accuracy of 82% for ASD diagnosis.","PeriodicalId":73224,"journal":{"name":"Healthcom. International Conference on e-Health Networking, Applications and Services","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/healthcom49281.2021.9398924","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39554295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Beats-Per-Minute (BPM): A Microservice-based Platform for the Monitoring of Health Related Data via Activity Trackers 每分钟跳动(BPM):一个基于微服务的平台，用于通过活动跟踪器监控健康相关数据

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2018-09-01 DOI: 10.1109/HealthCom.2018.8531169

Orla OrBrien, Ruairi Donagh OrReilly

引用次数: 3

Improved persuasive design: Matching personal traits and inducing effortful thinking 改进的说服设计:匹配个人特征并诱导努力思考

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2017-01-01 DOI: 10.1109/HealthCom.2017.8210841

Hong Jiang, Y. Qi, Yiwen Chen

引用次数: 0

4G UAV communication system and hovering height optimization for public safety 4G无人机通信系统及悬停高度优化，保障公共安全

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2017-01-01 DOI: 10.1109/HealthCom.2017.8210823

Ting Chen, Yun Xiao, Xiangmo Zhao, Tao Gao, Zhigang Xu

引用次数: 3

Performance improvement of the wireless body area network (WBAN) 无线体域网络(WBAN)的性能改进

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2016-09-01 DOI: 10.1109/HealthCom.2016.7749509

E. Sarra, T. Ezzedine

{"title":"Performance improvement of the wireless body area network (WBAN)","authors":"E. Sarra, T. Ezzedine","doi":"10.1109/HealthCom.2016.7749509","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749509","url":null,"abstract":"The introduction of the Wireless Body Area Network (WBAN) grows significantly regarding its flexibility, accuracy, costs efficiency and mobility. It supports a huge range of innovative applications that improve the quality of life and enhance services. In the health care system, the majority of WBAN applications are responsible of handling critical data in order to monitor the patient health state and to save his live in many cases. That's why WBAN should efficiently deliver patient's vital signs to specialized medical entity (doctor, emergency, ‥). However, the particular architecture of WBAN and the movement patterns of the body part affect the communication quality. Moreover, the number of WBAN nodes increases the contention level to access to the shared wireless medium; this consequently produces packets collisions and the loss of critical data. We evaluated in this article the performance of the WBAN within different scenarios. We investigated different effects of the number of nodes as well as the different body state (standing, running) on the WBAN's reliability. We, finally, proposed a simple, no cost and convenient Adaptive Transmit Power Mechanism (ATPM) to improve the WBAN link quality without consuming unnecessary energy.","PeriodicalId":73224,"journal":{"name":"Healthcom. International Conference on e-Health Networking, Applications and Services","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77083368","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: 7

Software reliability analysis in air traffic control system 空中交通管制系统软件可靠性分析

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2015-04-21 DOI: 10.1109/ICNSURV.2015.7121264

Qu Jingyi, Wu Renbiao, Yang Jun, Wang Wenyi

引用次数: 1

An assessment of wind farms' electromagnetic impact for the aerodrome 风电场对机场电磁影响的评估

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2015-04-21 DOI: 10.1109/ICNSURV.2015.7121227

Wang Xiaoliang, Ma Yuzhao, He Wei-kun, Wang Wenyi, Wu Renbiao

{"title":"An assessment of wind farms' electromagnetic impact for the aerodrome","authors":"Wang Xiaoliang, Ma Yuzhao, He Wei-kun, Wang Wenyi, Wu Renbiao","doi":"10.1109/ICNSURV.2015.7121227","DOIUrl":"https://doi.org/10.1109/ICNSURV.2015.7121227","url":null,"abstract":"As a source of clean energy wind power has attracted great interests around the world. However, recent research revealed that wind farms may interfere with surveillance and navigation instruments in aerodromes such as radar, radio navigation instrument, etc because of wind farms' reflection, scattering and shadowing to the electromagnetic wave. Therefore, wind farms may further threaten aviation safety. Around a new aerodrome in the construction in the east of China, there are several wind farms nearby. Our laboratory was assigned to assess the impact of wind farms nearby on this new aerodrome. This paper presents our assessment scheme and particular methods for this actual case. The electronic equipments which may be interfered with by wind farms in the assessed aerodrome include SSR (secondary surveillance radar), VOR (VHF omnidirectional radio range) and ILS (instrument landing system). We assessed the wind farms' impact on these equipments separately. The assessment procedure includes four steps: geographic position relationship assessment, zone partition assessment, visibility assessment and detailed engineering assessment. The wind farm we assessed is only 4–11 kilometers away from the base point of the runway of the new aerodrome. There are 32 wind turbines whose height is over 100 meters in this nearest wind farm. All wind turbines distribute on a hill not far from the aerodrome. Fortunately, this wind farm is not on the direction of the runway, but on the side of the runway. Some assessment results are given in the paper. The assessment scheme presented in the paper is valuable for site selection of aerodromes, surveillance and navigation electronic equipments and wind farms. It also could give reference for type selection of electronic equipments of the aerodrome in the construction.","PeriodicalId":73224,"journal":{"name":"Healthcom. International Conference on e-Health Networking, Applications and Services","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91159254","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

Unmanned Aircraft System (UAS) standards development: RTCA SC-228 status 无人机系统(UAS)标准发展:RTCA SC-228状态

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2015-04-21 DOI: 10.1109/ICNSURV.2015.7121363

S. Trees

引用次数: 2

Using Machine Learning to Identify Benign Cases with Non-Definitive Biopsy. 使用机器学习识别非明确活检的良性病例。

Healthcom. International Conference on e-Health Networking, Applications and Services Pub Date : 2013-10-09 DOI: 10.1109/HealthCom.2013.6720685

Finn Kuusisto, Inês Dutra, Houssam Nassif, Yirong Wu, Molly E Klein, Heather B Neuman, Jude Shavlik, Elizabeth S Burnside

引用次数: 4