EAI Endorsed Transactions on Pervasive Health and Technology

Issue 4, 2022

Articles
Information

Design of telemedicine information query system based on wireless sensor network
Appears in:
phat 22(4): e1

Authors:
Qian Gao, Thippa Reddy Gadekallu

Abstract:
INTRODUCTION: A wireless sensor network-based remote medical information query system is proposed and designed. OBJECTIVE: The proposed method aims at improving the throughput of the hospital information remote query system and reducing the response time METHODS: The system structure is divided i…INTRODUCTION: A wireless sensor network-based remote medical information query system is proposed and designed.
OBJECTIVE: The proposed method aims at improving the throughput of the hospital information remote query system and reducing the response time
METHODS: The system structure is divided into three levels. The presentation layer is responsible for displaying the query operation interface of the function layer. The function layer realizes the query function according to the user instructions. The wireless sensor network is responsible for the transmission of instructions. The data layer starts the query of telemedicine information based on the Top-k query algorithm. In wireless sensor networks, the improved ant colony algorithm is used to optimize it, which improves the information transmission performance of the system.
RESULTS: The experimental results show that the designed system can complete the medical information query according to the needs of users, the system throughput and the residual energy of sink nodes are high, and the maximum response time of the system is always less than 0.5s.
CONCLUSION: It shows that the designed system has strong practical application performance and high application value.
more »
Prediction of Emergency Mobility Under Diverse IoT Availability
Appears in:
phat 22(4): e2

Authors:
Bin Sun, Renkang Geng, Yuan Xu, Tao Shen

Abstract:
INTRODUCTION: Prediction of emergency mobility needs to consider more scenarios as Internet of Things (IoT) develops at a high speed, which influences the quality and quantity of data, manageable resources and algorithms. OBJECTIVES: This work investigates differences in dynamic emergency mobility…INTRODUCTION: Prediction of emergency mobility needs to consider more scenarios as Internet of Things (IoT) develops at a high speed, which influences the quality and quantity of data, manageable resources and algorithms.
OBJECTIVES: This work investigates differences in dynamic emergency mobility prediction when facing dynamic temporal IoT data with different quality and quantity considering diverse computing resources and algorithm availability.
METHODS: A node construction scheme under a small range of traffic networks is adopted in this work, which can effectively convert the road to graph network structure data which has been proved to be feasible and used for the small-scale traffic network data here. Besides, two different datasets are formed using public large scale traffic network data. Representative widely used and proven algorithms from typical types of methods are selected respectively with different datasets to conduct experiments.
RESULTS: The experimental results show that the graphed data and neural network algorithm can deal with the dynamic time series data with complex nodes and edges in a better way, while the non-neural network algorithm can predict the with a simple graph network structure.
CONCLUSION: Our proposed graph construction with graph neural network improves dynamic emergency mobility prediction. The prediction should consider the scenarios of availability of computing resources, quantity and quality of data among other IoT features to improve the results. Later, automation and data enrichment should be improved.
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Hybrid Detection and Mitigation of DNS Protocol MITM attack based on Firefly algorithm with Elliptical Curve Cryptography
Appears in:
phat 22(4): e3

Authors:
Sabitha Banu. A., Dr. G. Padmavathi

Abstract:
A Domain Name Server is a critical Internet component. It enables users to surf the web and send emails. DNS is a database used by millions ofcomputers to determine which address best answers a user’s query. DNS is an unencrypted protocol that may be exploited in numerous ways. The mostpopular DNS …A Domain Name Server is a critical Internet component. It enables users to surf the web and send emails. DNS is a database used by millions ofcomputers to determine which address best answers a user’s query. DNS is an unencrypted protocol that may be exploited in numerous ways. The mostpopular DNS MITM attack uses DNS poisoning to intercept communications and fake them. DNS servers do not verify the IP addresses they forwardtraffic to. In DNS attacks, the attacker either targets the domain name servers or attempts to exploit system weaknesses. The Proposed FFOBLA-ECC model detects the DNS Spoofed nodes in a wireless network using the optimized firefly boosted LSTM with the help of TTL and RTR parametersreceived from the simulation environment and provides authentication between the nodes in order to mitigate it using the Elliptical curve cryptography. The proposed model results are different from the other methods and yield highly accurate results beyond 98% compared with the existing RF, ARF, and KNN methods.
more »
Classification of brain tumor using a multistage approach based on RELM and MLBP
Appears in:
phat 22(4): e4

Authors:
Mrs. R. Bhavani, Dr. K. Vasanth

Abstract:
INTRODUCTION: Automatic segmentation and classification of brain tumors help in improvement of treatment which will increase the life of the patient. Tumor may be noncancerous (benign) or cancerous (malignant). Precancerous cells may also form into cancer. OBJECTIVES: Hough CNN is applied for sele…INTRODUCTION: Automatic segmentation and classification of brain tumors help in improvement of treatment which will increase the life of the patient. Tumor may be noncancerous (benign) or cancerous (malignant). Precancerous cells may also form into cancer.
OBJECTIVES: Hough CNN is applied for selected section which applies hough casting technique in segmentation. METHODS: A multistage methodof extracting features, with multistage neighbouring is done for emerging an exact brain tumor classifying methodology.
RESULTS: In this dataset three types of brain tumors are available they are meningioma, glioma, and pituitary.. CONCLUSION: This paperpresented an efficient brain tumor classification approach which involves multiscale preprocessing, multiscale feature extraction and classification.
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Aortic Stenosis Detection Using Spectral Statistical Features of Heart Sound Signals
Appears in:
phat 22(4): e5

Authors:
S. V. Mahesh Kumar, P. Dhinakar, R. Nishanth

Abstract:
INTRODUCTION: Aortic stenosis (AS) is a severe complicated heart valve disease. This valve abnormality is a slow-progressive condition and mostly asymptomatic. Hence, there is a need for a rapid non-invasive diagnosis method with minimal feature extraction. OBJECTIVE: In this paper, we proposed a …INTRODUCTION: Aortic stenosis (AS) is a severe complicated heart valve disease. This valve abnormality is a slow-progressive condition and mostly asymptomatic. Hence, there is a need for a rapid non-invasive diagnosis method with minimal feature extraction.
OBJECTIVE: In this paper, we proposed a spectral features-based rapid heart sound signal analysis method to identify the AS stages with minimum number of features.
METHODS: In this study, the heart sound signals were collected from the medical database and transformed into the frequency domain for further spectral feature analysis. We used the windowing technique to conditioning the heart signals before spectral analysis. The spectral statistical features were extracted from the computed frequency spectrum. The range of statistical features was compared for normal, early, and AS sound signals.
RESULTS: In experiments, the normal, early, and delayed AS heart sound signals were used. The normal/unhealthy condition of a heart was identified using the statistical features of the frequency spectrum. The experimental results show the statistical difference between the normal and AS heart sound signal spectrums.
CONCLUSION: The experimental results confirmed that the statistical features derived from the heart sound signal spectrums were varied according to the AS condition. Hence, the spectral statistical features can be considered as rapid predictors of AS.
more »

Scope

EAI Endorsed Transactions on Pervasive Health and Technology is open access, a peer-reviewed scholarly journal focused on personal electronic health assistants, health crowdsourcing, data mining, knowledge management, IT applications to the needs of patients, disease prevention, and awareness, electronic and mobile health platforms including design and more. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications. From 2021, the journal publishes five issues per year. Authors are not charged for article submission and processing.

Topics

Knowledge Representation and Reasoning

Physiological models for interpreting medical sensor data
Sensing/Actuating Technologies and Pervasive Computing
Medicine, Nursing, and Allied Health Professions
Human-Computer Interaction and Computer Supported Cooperative Work
Hardware …

Knowledge Representation and Reasoning

Physiological models for interpreting medical sensor data
Sensing/Actuating Technologies and Pervasive Computing
Medicine, Nursing, and Allied Health Professions
Human-Computer Interaction and Computer Supported Cooperative Work
Hardware and Software Infrastructures
Activity recognition and fall detection
User modelling and personalization
Modelling of Pervasive Healthcare environments
Sensor-based decision support systems
Design and evaluation of patient and ambient-related sensors
Wearable and implantable sensor integration
Data fusion in pervasive healthcare environments
Data mining of medical patient records
Software architectures
Electronic Health Records

Understanding Users

Identifying and addressing stakeholder needs
Usability and acceptability
Barriers and enablers to adoption
Social implications of pervasive health technology, and social inclusion
Coverage and delivery of pervasive healthcare services
Patient and caregiver empowerment
Diversity: population and condition-specific requirements
Inclusive research and design: engaging underrepresented populations
Digital interventions and health behavior change

Applications

Autonomous systems to support independent living
Clinical applications, validation and evaluation studies
Telemedicine and mHealth solutions
Chronic disease and health risk management applications
Health/Wellbeing promotion and disease prevention
Home based health and wellness measurement and monitoring
Continuous vs event-driven monitoring of patients
Smart homes and hospitals
Using mobile devices in the storage, update, and transmission of patient data
Wellbeing and lifestyle support
Systems to support individuals with auditory, cognitive, or vision impairments
Systems to support caregivers

Pervasive Healthcare Management

Challenges surrounding data quality
Standards and interoperability in pervasive healthcare
Business cases and cost issues
Security and privacy issues
Training of healthcare professional for pervasive healthcare
Legal and regulatory issues
Staffing and resource management

Scopus (CiteScore 2020: 0.7)
Ei Compendex
DOAJ
DBLP
CrossRef
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Special Issues

Editors-in-Chief
Nenad Filipovic, University of Kragujevac, Serbia
Jun Hu, Eindhoven University of Technology, The Netherlands
Area Editors
Alberto Antonietti (École Polytechnique Fédérale de Lausanne, Switzerland)
Alejandro Dominguez Rodriguez (Autonomous University of Baja California)…

Editors-in-Chief
Nenad Filipovic, University of Kragujevac, Serbia
Jun Hu, Eindhoven University of Technology, The Netherlands
Area Editors
Alberto Antonietti (École Polytechnique Fédérale de Lausanne, Switzerland)
Alejandro Dominguez Rodriguez (Autonomous University of Baja California)
Alessandro Ruggiero (University of Salerno, Italy)
Alexandros Tzallas (Technological Educational Institute of Epirus)
Andjela Blagojevic (University of Kragujevac, Serbia)
Anind Dey (University of Washington)
Ansar-Ul-Haque Yasar (Hasselt University, Belgium)
Antonella Carbonaro (Universita' di Bologna, Italy)
Arijit Ukil (Tata Consultancy Services)
Asimina Kiourti (The Ohio State University)
AtaUllah Ghafoor (National University of Modern Languages, Islamabad, Pakistan.)
Bert Arnrich (Boğaziçi University, Istanbul, Turkey)
Boban Stojanovic (University of Kragujevac, Serbia)
Branko Arsic (University of Kragujevac, Serbia)
Constantinos Pattichis (University of Cyprus, Cyprus)
Daojing He (South China University of Technology, China)
Djordje Jakovljevic (Coventry University, UK)
Eduard Babulak (National Science Foundation, USA)
Emilija Stojmenova (Duh University of Ljubljana)
Emilio Serrano (Technical University of Madrid, Spain)
Frank Wallhoff (Jade University of Applied Sciences)
Giorgos Giannakakis (Foundation for Research and Technology Hellas, Greece)
Honggang Wang (UMASS. USA)
Kashif Saleem (King Saud University)
Laszlo Bokor (BME, Hungary)
Lazar Dasic (University of Kragujevac, Serbia)
Marcela Deyanira Rodriguez Urrea (Autonomous University of Baja California)
Marko Robnik-Sikonja (University of Ljubljana, Slovenia)
Mauro Femminella (University of Perugia, Italy)
Melina Frenken (Jade University of Applied Sciences)
Michalis Zervakis (Technical University of Crete, Greece)
Milos Ivanovic (University of Kragujevac, Serbia)
Milos Kotlar (University of Belgrade, Serbia)
Mohammad Upal Mahfuz (University of Wisconsin-Green Bay)
Mojtaba Taherisadr (University of Michigan)
Mosabber Uddin Ahmed (University of Dhaka)
Nadeem Javaid (COMSATS Institute of Information Technology, Islamabad, Pakistan)
Netzahualcoyotl Hernandez-Cruz (Oxford University, UK)
Nikolaos Bourbakis, Wright State University in Ohio, United States
Pan Zheng, University of Canterbury, New Zealand
Pietro Cipresso (Istituto Auxologico, Milan, Italy)
Razan Hamed (New York Institute of Technology, NY, USA)
Riccardo Martoglia (University of Modena and Reggio Emilia, Italy)
Saikishor Jangiti (SASTRA Deemed University, India)
Silvia Serino (Catholic University of Milan, Italy)
Stefan Rahr Wagner (Aarhus University)
Tanvir Zia (School of Computing & Mathematics, Charles Sturt University, Australia)
Tessa Dekkers (Delft University, The Netherlands)
Tijana Sustersic (Faculty of Engineering, University of Kragujevac)
Veljko Milutinovic (University of Belgrade, Serbia)
Venet Osmani (CREATE-NET, Trento, Italy)
Wilko Heuten (OFFIS, Germany)
Zhihan Lv (Qingdao University, China)
Zoran Bosnic (University of Ljubljana, Slovenia)
Ognjen Pavic (Institute for Information Technology, University of Kragujevac, Serbia)
Analúcia Schiaffino Morales (Federal University of Santa Catarina, Brazil)
Emeritus Editors-in-Chief
Gonçalo Marques, Polytechnic of Coimbra, Portugal

Journal Blurb

Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/phat/index

Publisher: EAI
ISSN: 2411-7145
Volume: 8

Published: 2022-10-31

Design of telemedicine information query system based on wireless sensor network

Prediction of Emergency Mobility Under Diverse IoT Availability

Hybrid Detection and Mitigation of DNS Protocol MITM attack based on Firefly algorithm with Elliptical Curve Cryptography

Classification of brain tumor using a multistage approach based on RELM and MLBP

Aortic Stenosis Detection Using Spectral Statistical Features of Heart Sound Signals

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