EAI Endorsed Transactions on Pervasive Health and Technology

Issue 28, 2021

Editor(s)-in-Chief: Manik Sharma

Articles
Information

Early and Precise Detection of Pancreatic Tumor by Hybrid Approach with Edge Detection and Artificial Intelligence Techniques
Appears in:
phat 21(28): e1

Authors:
Bhawna Dhruv, Neetu Mittal, Megha Modi

Abstract:
INTRODUCTION: Pancreatic cancer is highly lethal as it grows, spreads rapidly and difficult to diagnose at its early stages. It can be identified through scan images. The tumorous images obtained from imaging techniques suffer from the drawback of cryptic data due to presence of unwanted noise and …INTRODUCTION: Pancreatic cancer is highly lethal as it grows, spreads rapidly and difficult to diagnose at its early stages. It can be identified through scan images. The tumorous images obtained from imaging techniques suffer from the drawback of cryptic data due to presence of unwanted noise and poor contrast.

OBJECTIVE: To reduce the risk of pancreatic cancer, its detection and diagnosis at an early stage becomes crucial.

METHODS: The proposed work encompasses the processing of CT scans of pancreatic tumor using classical and artificial intelligence based optimized edge detection techniques for optimization and detection of tumor.

RESULTS: The simulation results are highly encouraging as evident from the far improved visibility of resultant images with Particle Swarm Optimization.

CONCLUSION: The output image with PSO shows the quality enhanced CT images which helps in accurate detection and diagnosis of the pancreatic tumor at an early stage providing an aid in medical imaging.
more »
An Empirical Study on Challenges Faced by the Elderly in Care Centres
Appears in:
phat 21(28): e2

Authors:
Jie Li, Wei Wei Goh, NZ Jhanjhi, Filzah Binti Md Isa, Sumathi Balakrishnan

Abstract:
INTRODUCTION: The fact of our lives is that we will be reaching to elderly life stage sooner or later. Our elderly community has been left far behind of new technology updates. Technology advances just as age is catching up on us. To many who are in their twilight years, …INTRODUCTION: The fact of our lives is that we will be reaching to elderly life stage sooner or later. Our elderly community has been left far behind of new technology updates. Technology advances just as age is catching up on us. To many who are in their twilight years, using cutting edge technologies may be a hurdle in their activities of daily living (ADLs).

OBJECTIVES: Therefore, this study aims to identify and measure the ADL challenges that the elderly encounter and improve their quality of life (QoL).

METHODS: This research embarked on semi-structured interviews at 9 geriatric care centres in Malaysia to investigate the ADL challenges by the elderly residents. The thematic analysis approach was employed for data analysis and further discussion.

RESULTS: The research findings suggested that the QoL of the elderly is limited by the challenges of geriatric issues, poor living conditions, and technology acceptance barriers.

CONCLUSION: In conclusion, the current research provides an overview of the ADL challenges faced by the elderly with recommendations of user-centred Internet of Things (IoT) devices for elderly to use in an ambient assisted living (AAL) environment in Society 5.0.
more »
Enhanced Boykov's graph cuts based segmentation for Cervical Cancer Detection
Appears in:
phat 21(28): e3

Authors:
G. N. Balaji, S. V. Suryanarayana, J. Sengathir

Abstract:
Introduction: Cervical cancer is considered as the major curse to women society of the world due to their low survival rate. However, the prognosis of cervical cancer at an early stage through periodic screening was identified to enhance the survival probability of the women patients around the wor…Introduction: Cervical cancer is considered as the major curse to women society of the world due to their low survival rate. However, the prognosis of cervical cancer at an early stage through periodic screening was identified to enhance the survival probability of the women patients around the world.

Objective: In this paper, a Boykov-Kolmogorov Graph Cuts and Cloud Model-based Synergy Integrated Segmentation (BKGC-CMSIS) Technique for facilitating predominant cervical cancer detection from the pap smear images used for prognosis.

Methods: This proposed BKGC-CMSIS scheme introduces an effective Boykov-Kolmogorov Graph Cuts-based image partitioning method that estimates the image data through a synergy cloud model for formulating objective functions. The objective function used in this proposed BKGC-CMSIS scheme includes a data item and a smooth term for boundary preservation in order to determine the deviation of each pixel corresponding to the different regions of the cervical pap smear cells.

Results: Also, it identifies the data item through the utilization of X-condition cloud generator for determining and defining the accurate boundaries of cytoplasm and nuclei derived from the pap smear cells. This proposed BKGC-CMSIS scheme uses the merits of membership degree through the incorporation of the smooth term for estimating the degree of similarity existing among the neighboring regions of the cervical pap smear cells.

Conclusion: The experimental results of this proposed BKGC-CMSIS scheme is also potent in enhancing the classification accuracy by 14% superior to the benchmarked cervical cancer detection schemes considered for investigation.
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Cloud based IoT Smart Healthcare System for Remote Patient Monitoring
Appears in:
phat 21(28): e4

Authors:
G. Jaya Lakshmi, Mangesh Ghonge, Ahmed J. Obaid

Abstract:
INTRODUCTION: Covid-19 has exposed the necessitate for the rapid acceptance of increasingly pioneering digital health technologies, especially remote health monitoring. The digital revolution in Healthcare is dynamic ease of use of inexpensive concern solutions, enhancing patien…INTRODUCTION: Covid-19 has exposed the necessitate for the rapid acceptance of increasingly pioneering digital health technologies, especially remote health monitoring. The digital revolution in Healthcare is dynamic ease of use of inexpensive concern solutions, enhancing patient care, reducing complications, improving effectiveness, and authorizing healthcare decision-makers with intelligence insight at the point of care.

OBJECTIVES: The primary objective of this work is to depict the need to recognize wearable sensors as a prerequisite for supporting paradigms in monitoring patients in real-time and enabling access information from the cloud.

METHODS: Internet of Things (IoT) is the association of substantial objects where information and communication tools connect various embedded devices to the internet for gathering and switching over data. The combinations of embedded devices with cloud servers recommend extensive pertinence of IoT to several areas of human life. This paper has proposed a method through cloud-based IoT healthcare sensors to formulate patient monitoring remotely. In combination with the implementation of various inbuilt capabilities, internet-enabled heterogeneous wearable sensors can be used for the collection of biomedical data to transmit patient data directly to cloud severe systems to monitor health remotely.

RESULTS: Smart healthcare monitoring includes channels of communication, embedded internal and external sensors, IoT server, and cloud storage. The health parameters activities are done at various levels of refining named application layer, management layer, network layer and layer of device. Different data sensors have been collected by wireless media from nodes. It is saved as an unstructured dataset in the cloud. For security with username and password, a patient database is created. Authorized individuals have access to the cloud in order to monitor cloud sensor data in data log, analogue log, digital input and digital output.

CONCLUSION: Patient physical parameters like heart beat respiration ,high temperature and stress are calculated via sensors and can be progressed by WIFI unit in the cloud. From this healthcare practitioner will analyze medical to have effective medication. For face-to-face consultation between doctors and patients, the video feature can be added in the future work.
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ASSISTO eCARE 4.0 -- An IoT- and AI-based architecture for assisted active aging
Appears in:
phat 21(28): e5

Authors:
Leonardo Bertini, Dario Bruneo, Massimo Mecella, Emilia Reda

Abstract:
INTRODUCTION: All over Europe, there is an increasing demand for social/welfare services and a shift towards a demand increasingly formed by a mix of well-being and safety. Artificial intelligence (AI), Internet-of-Things (IoT) and cloud computing techniologies can play a major role in such a typ…INTRODUCTION: All over Europe, there is an increasing demand for social/welfare services and a shift towards a
demand increasingly formed by a mix of well-being and safety. Artificial intelligence (AI), Internet-of-Things (IoT) and
cloud computing techniologies can play a major role in such a type of services.

OBJECTIVES: The aim of this work was to investigate, design, develop and validate a prototype platform, named Assisto
eCare 4.0, providing “well-being” and “safety” services/functionalities to home elderly residents.

METHODS: The platform builds upon biometric technologies and analytics functionalities exploiting AI techniques
in order to limit human intervention during emergencies and automatically and immediately deciding actions to be
performed by making the operators intervene also directly at the user home.

RESULTS: The prototype has been validated with a group of 22 users over a period of more than 7 months. The results
derived from the final evaluation questionnaire show that the majority of participants rated the service as excellent.

CONCLUSIONS: The platform has been released according to the API-as-a-Service model, proposing itself with a
pioneering model of social open innovation, which is to develop and test the IT system and then to make it available
to all those who want to use it. Currently (July 2021) the system has been engineered and offered by a consortium of
different industries and is operative in the Rome area.
more »

Scope

EAI Endorsed Transactions on Pervasive Health and Technology is an open access, peer-reviewed scholarly journal focused on personal electronic health assistants, health crowdsourcing, data mining and knowledge management, IT applications to 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 with a quarterly frequency. 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)
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DOAJ
DBLP
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Special Issues

Editors-in-Chief
Gonçalo Marques, Polytechnic of Coimbra, Portugal
Nenad Filipovic, University of Kragujevac, Serbia
Area Editors
Alberto Antonietti (École Polytechnique Fédérale de Lausanne, Switzerland)
Alejandro Dominguez Rodriguez (Autonomous University of Baja California)
Alessan…

Editors-in-Chief
Gonçalo Marques, Polytechnic of Coimbra, Portugal
Nenad Filipovic, University of Kragujevac, Serbia
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)

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: 7

Published: 2021-10-19

Early and Precise Detection of Pancreatic Tumor by Hybrid Approach with Edge Detection and Artificial Intelligence Techniques

An Empirical Study on Challenges Faced by the Elderly in Care Centres

Enhanced Boykov's graph cuts based segmentation for Cervical Cancer Detection

Cloud based IoT Smart Healthcare System for Remote Patient Monitoring

ASSISTO eCARE 4.0 -- An IoT- and AI-based architecture for assisted active aging

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