EAI Endorsed Transactions on Pervasive Health and Technology

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

Editor(s)-in-Chief: Gonçalo Marques and Nenad Filipovic

Aims & Scope
Indexing
Editorial Board
Special Issues

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.

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

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)

Recently Published
Most Popular

Blockchain-Enabled Hyperledger Fabric to Secure Data Transfer Mechanism for Medical Cyber-Physical System: Overview, Issues, and Challenges
Appears in:
phat 23(1):

Authors:
P. Vinayasree, A. Mallikarjuna Reddy

Published:
30th Nov 2023

Abstract:
This paper proposes a model to address the challenges faced by medical cyber-physical systems (MCPS) by implementing a permissioned blockchain platform. The platform incorporates the unique properties of blockchain into the network of affected systems, including decentralization, transparency, and …This paper proposes a model to address the challenges faced by medical cyber-physical systems (MCPS) by implementing a permissioned blockchain platform. The platform incorporates the unique properties of blockchain into the network of affected systems, including decentralization, transparency, and immutability. The platform also includes a novel technique to secure MCPS through an automated access-control manager. This manager allows users to control who has access to their data, and can be configured to trust a third party if desired. The paper also extends into networked medical device systems, and discusses how the platform can be used to address critical is-sues specific to this field, such as network design. Finally, the paper discusses how various security features can be integrated into ultra-small devices, enhancing the protection of embedded systems. The overall objective of this research is to develop a secure and efficient data transfer mechanism for MCPS. The proposed platform addresses the challenges faced by MCPS by incorporating the unique properties of blockchain.
more »
Assessment of technological stress levels in university staff: case study
Appears in:
phat 23(1):

Authors:
Edmundo Cabezas-Heredia, Fernando Molina-Granja, Gregory Montenegro-Bosquez, Mónica Salazar, Juan Santillán-Lima, Santiago Ramirez, Orestes Cachay-Boza

Published:
24th Nov 2023

Abstract:
INTRODUCTION: Stress, a natural reaction of the body to challenging circumstances, can manifest itself in different ways and harm both an individual's physical and mental health. From a constant feeling of being overwhelmed to difficulties in concentration and decision-making, stress can undermine …INTRODUCTION: Stress, a natural reaction of the body to challenging circumstances, can manifest itself in different ways and harm both an individual's physical and mental health. From a constant feeling of being overwhelmed to difficulties in concentration and decision-making, stress can undermine the overall quality of life. Physical symptoms such as headaches, digestive disorders and trouble falling asleep often accompany this condition, highlighting its negative impact on the body.
OBJECTIVES: The research aims to determine stress levels in teachers, workers, and university students.
METHODS: The stress test proposed by Dr. Gloria Villalobos was applied and complemented with sociodemographic variables. The population consisted of 224 teachers, 11 staff and 32 students.
RESULTS: The result found to be stress: 4.5% medium, 27.7% high, and 67.8% very high; The correlation is established employing Cramer's V between the variables and the applied test that the results do not influence the phenomenon investigated
CONCLUSION: It concludes the significant presence of medium - high - very high stress in the sample analyzed with serious consequences for health being necessary emerging measures to prevent diseases in university staff.
more »
Artificial Intelligence Application with Contact Tracing for Post COVID -19 Epidemic Management
Appears in:
phat 23(1):

Authors:
Anasuya Swain, Subhalaxmi Sahu, Monalisha Patel, Pradeep Ranjan Dhal

Published:
10th Nov 2023

Abstract:
INTRODUCTION: Post COVID -19 epidemics is in a critical situation which has to be properly managed with right preventive and curative measures to protect the economy and welfare of the Human beings. OBJECTIVES: Effective management of this terrific situation may be possible through the help of con…INTRODUCTION: Post COVID -19 epidemics is in a critical situation which has to be properly managed with right preventive and curative measures to protect the economy and welfare of the Human beings.
OBJECTIVES: Effective management of this terrific situation may be possible through the help of contact tracing and its application of AI mechanism. Here the authors as taken the available data for the testing of the significance of AI approach for contract tracing proper management of the post COVID epidemic situation.
METHODS: Here contact tracing data are collected analysed interpreted and validity is tested with the help of statistical tools like egression, coefficient and Annova for the testing of the available data with its further application.
R ESULTS: AI application creates more awareness, vaccination, self-testing, isolation and intake medicine
CONCLUSION: Artificial Intelligence &social media plays a vital role for the creation of social awareness and proper manage of post COVID-19 epidemics.
more »
Virtual reality for physical and psychological improvement during the treatment of patients with breast cancer: Systematic review
Appears in:
phat 23(1):

Authors:
Bryan Tito-Llana, Nils Riveros-Torre, Brian Meneses-Claudio, Monica Auccacusi-Kañahuire

Published:
30th Oct 2023

Abstract:
During breast cancer treatment, patients face various physical and psychological problems. However, a promising solution has been found in the use of virtual reality as a tool to address these problems. Our goal was to identify the most common problems and symptoms during treatment, as well as inve…During breast cancer treatment, patients face various physical and psychological problems. However, a promising solution has been found in the use of virtual reality as a tool to address these problems. Our goal was to identify the most common problems and symptoms during treatment, as well as investigate the effectiveness of virtual reality in addressing them. We also set out to determine if there are any disadvantages associated with using this system. To this end, we conducted a systematic review using a non-experimental, descriptive, and qualitative-quantitative approach. 20 open access articles were selected in the Scopus database, following established inclusion and exclusion criteria. The results revealed that anxiety and pain are the most common symptoms experienced during breast cancer treatment. Regarding the effectiveness of virtual reality to treat these symptoms, differences were found: a significant impact on anxiety was observed (p < 0.001), but no significant impact on pain was found (p < 0.07). In addition, only three studies mentioned the possible presence of cyberdisease as an obstacle. In conclusion, anxiety and pain are the most common symptoms during breast cancer treatment. Virtual reality shows high efficacy in managing anxiety, but its effectiveness in pain management is limited. In addition, technological advances appear to have reduced the occurrence of cyberdisease and associated drawbacks, although little information is available in the studies reviewed.
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Web accessibility for people with dyslexia: A systematic literature review
Appears in:
phat 23(1):

Authors:
Leonardo Enco-Jáuregui, Brian Meneses-Claudio, Monica Auccacusi-Kañahuire

Published:
27th Oct 2023

Abstract:
As the digital age advances, the internet has become a vital source of information and social participation; And with it, opportunities and benefits are manifested that can only be obtained through this single means. That is why it is essential to ensure that everyone can have equal access and oppo…As the digital age advances, the internet has become a vital source of information and social participation; And with it, opportunities and benefits are manifested that can only be obtained through this single means. That is why it is essential to ensure that everyone can have equal access and opportunities when browsing the web. This review focuses on investigating the current state of knowledge of web accessibility for people with dyslexia. To achieve this, various computer solutions, design recommendations and study of web accessibility guidelines were reviewed, whose main objective is to improve the experience of users with dyslexia when browsing the web. A total of 120 original articles were extracted from the Scopus database, of which 22 studies met the inclusion criteria. The results showed that many of the web design customization options provided by these solutions were able to improve the web browsing and reading experience for people with dyslexia. In conclusion, this RSL allowed to identify a large number of software-based solutions and design recommendations to provide accessibility to people with dyslexia. Among the most important factors considered in these studies is the organization of content, typography and color contrast. Additionally, it is important to highlight the need to continue adjusting these proposals according to the different opinions and suggestions provided by the participants during the evaluations. And finally, it is recommended to obtain larger samples of participants so that, in this way, more representative results can be obtained during future research.
more »
Telemedicine in Latin America: a bibliometric analysis
Appears in:
phat 23(1):

Authors:
Fabrizio Del Carpio-Delgado, Rafael Romero-Carazas, Gustavo Eduardo Pino-Espinoza, Linda Flor Villa-Ricapa, Eva Luisa Núñez-Palacios, Margoth Marleny Aguilar-Cuevas, Antony Paul Espiritu-Martinez

Published:
27th Oct 2023

Abstract:
Introduction: Telemedicine revolutionizes health care by removing geographic barriers and improving access. Although it faces challenges such as privacy and equity of access, bibliometric studies are crucial to understanding its impact and guiding future research. Methods: The study used a descrip…Introduction: Telemedicine revolutionizes health care by removing geographic barriers and improving access. Although it faces challenges such as privacy and equity of access, bibliometric studies are crucial to understanding its impact and guiding future research.
Methods: The study used a descriptive bibliometric methodology based on the Scopus database to analyze telemedicine research in Latin America over the last ten years, resulting in 2105 academic articles. Tools such as SciVal and VOSviewer were used to perform quantitative and visual analyses of the publications, including creating bibliometric maps.
Result: From 2013-2022, 2105 academic articles on telemedicine were published in Latin America, with a significant impact on the health field. A particular focus is observed on topics such as psychological support, COVID-19, imaging diagnosis and cancer treatment, highlighting the relevance of telemedicine in these contexts. In addition, international collaboration was associated with a more significant impact. Brazil produced articles, and the importance of collaboration between academia and the corporate sector in this field was highlighted.
Conclusions: Telemedicine has grown in Latin America, especially during the pandemic, offering benefits such as psychological support and expedited diagnosis and treatment; however, it faces challenges such as a lack of equitable access to technology and concerns about data privacy. Brazil leads scientific production in this field.
more »
Autism Spectrum Disorder Classification Using Machine Learning and Deep Learning- A Survey
Appears in:
phat 23(1):

Authors:
Reeja S R, Sunkara Mounika

Published:
26th Oct 2023

Abstract:
Modern, highly developed technology has impacted reputable procedures in the medical and healthcare industries. Smart healthcare prediction to the senior sick patient is not only for quick access to data but also to get dependable treatment in an accurate prediction by healthcare service provider. …Modern, highly developed technology has impacted reputable procedures in the medical and healthcare industries. Smart healthcare prediction to the senior sick patient is not only for quick access to data but also to get dependable treatment in an accurate prediction by healthcare service provider. smart health prediction helps in the identification of numerous diseases. Based on patient experience, Deep learning technology provides a robust application space in the medical sector for health disease prediction problems by applying deep learning techniques to analyze various symptoms. In order to classify things and make precise predictions about diseases, deep learning techniques are utilized. people's health will be more secure, medical care will be of a higher caliber, and personal information will be kept more secret. As deep learning algorithms become more widely used to construct an interactive smart healthcare prediction and evaluation model on the basis of the deep learning model, CNN is upgraded. Advanced deep learning algorithms combined with multi-mode approaches and resting-state functional magnetic resonance represent an innovative approach that researchers have taken. A DL structure for the programmed ID ASD using highlights separated from the corpus callosum and cerebrum volume from the Stand dataset is proposed. Imaging is used to reveal hidden diseased brain connectome patterns to find diagnostic and prognostic indicators.
more »
Application of virtual reality in simulated training for arthroscopic surgeries: A systematic literature review
Appears in:
phat 23(1):

Authors:
Juan Molleda-Antonio, Erick Vargas-Montes, Brian Meneses-Claudio, Monica Auccacusi-Kañahuire

Published:
26th Oct 2023

Abstract:
INTRODUCTION: In recent years, technology has provided significant contributions to the health area with innovative projects such as artificial intelligence, virtual reality, augmented reality, etc. OBJECTIVE: This review aims to review studies that propose solutions with virtual reality (VR) tech…INTRODUCTION: In recent years, technology has provided significant contributions to the health area with innovative projects such as artificial intelligence, virtual reality, augmented reality, etc.
OBJECTIVE: This review aims to review studies that propose solutions with virtual reality (VR) technologies for the training of surgeons in the arthroscopic surgery procedure.
Method: We identified 352 articles from the Scopus database, from 2017 to the present, of which 31 studies were retrieved by a screening procedure based on the principles of the PRISMA declaration for the study of this systematic literature review (RSL).
Results: The implementation of virtual reality in surgical simulations has significantly reduced the percentage of risk in the execution of arthroscopic surgeries.
Conclusions: The virtual reality implemented in the simulations of arthroscopic surgeries stands out and represents a promising tool that will allow improvements with respect to the formation of skills and the anticipation of possible events. However, it is necessary to address certain limitations, such as the accuracy and realism of simulations, as well as the implementation of haptic or perceptual systems to improve tactile or visual feedback during simulation.
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Evaluation of the effectiveness of personal electronic health assistants in monitoring patients with chronic diseases
Appears in:
phat 23(1):

Authors:
Manuel Benigno Villanueva De La Cruz, Cecilia Isabel Lévano Zegarra, Roxana Maribel Bustamante Vega, Cesar Lorenzo Torres Sime, Julio Brayan Saldaña Narro, Lucio-Arnulfo Ferrer-Peñaranda, Roberto Carlos Dávila-Morán

Published:
24th Oct 2023

Abstract:
Introduction: Chronic diseases pose significant challenges in healthcare, which has driven the development of electronic health solutions. The effectiveness of these solutions in the management of diseases such as hypertension has generated interest, but further in-depth, evidence-based evaluation …Introduction: Chronic diseases pose significant challenges in healthcare, which has driven the development of electronic health solutions. The effectiveness of these solutions in the management of diseases such as hypertension has generated interest, but further in-depth, evidence-based evaluation is required.
Objective: The study aims to comprehensively evaluate how a customizable web platform, called "HyperVigilance", influences blood pressure control in hypertensive patients, considering additional variables such as patient satisfaction, quality of life and costs associated with treatment. In addition, the aim is to explore possible demographic factors that could moderate the results.
Methodology: The study was conducted with a quasi-experimental research design that included an intervention group using the "HyperVigilance" platform and a control group receiving standard medical care. Statistical tests were applied and demographic factors such as age, gender and socioeconomic status were considered.
Results: The use of the "HyperVigilance" platform resulted in a significant reduction in blood pressure, increased patient satisfaction and a marked improvement in quality of life, as well as a reduction in the costs associated with the treatment of hypertension.
Conclusions: The study concludes that the "HyperVigilance" platform is effective in controlling blood pressure and improving quality of life in patients with hypertension. The results support the growing role of digital interventions in chronic disease management, but highlight the need for long-term studies and exploration of different populations for a more complete understanding of their impact.
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Algorithms used for facial emotion recognition: a systematic review of the literature
Appears in:
phat 23(1):

Authors:
José Armando Tiznado Ubillús, José Alfredo Herrera Quispe, Luis Antonio Rivera Escriba, Marysela Ladera-Castañeda, César Augusto Atoche Pacherres, Miguel Ángel Atoche Pacherres, Carmen Lucila Infante Saavedra

Published:
24th Oct 2023

Abstract:
INTRODUCTION: We currently live in a society that is constantly changing and technology has developed algorithms that allow facial emotion recognition, because facial expression transmits people's mood, feelings and state of soul. However, it is required that future research can improve the quality…INTRODUCTION: We currently live in a society that is constantly changing and technology has developed algorithms that allow facial emotion recognition, because facial expression transmits people's mood, feelings and state of soul. However, it is required that future research can improve the quality of emotion detection by improving the quality of the data set and the model used, for this reason, it is necessary to investigate other machine learning algorithms in the recognition of facial emotions, as they exist. identification deficiencies that limit the discrimination of extracted structural features.
OBJECTIVE: The purpose of the article was to analyze the most used algorithms for facial emotion recognition, through a systematic literature review, according to the PRISMA method.
METHOD: A search for information was carried out in articles published in open access such as: Scopus, Web of Science (WOS) and Association for Computing Machiner (ACM) in the period 2022 and 2023, totaling 38 selected articles.
RESULTS: The results obtained indicate that the algorithms most used by the authors are SVM and SoftMax with a total of 17.65% each.
CONCLUSION: It is concluded that the SVM and SoftMax algorithms are the most predominant, playing a crucial role in achieving optimal levels of precision in the training of the models. These algorithms, with their robustness and ability to deal with complex data, have proven to be fundamental pillars in the field of facial emotion recognition.
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A Guide to Using Asynchronous Remote Communities (ARC) for Researching Distributed Populations
Appears in:
phat 17(11): e4

Authors:
Haley MacLeod, Ben Jelen, Annu Prabhakar, Lora Oehlberg, Katie Siek, Kay Connelly

Downloads:
6369

Abstract:
Existing research methods are largely intended to be conducted co-located and synchronously with a study population, but this approach is not feasible with remote or distributed populations. We describe a needs assessment study we conducted on Facebook. We report on our use of adapted versions of c…Existing research methods are largely intended to be conducted co-located and synchronously with a study population, but this approach is not feasible with remote or distributed populations. We describe a needs assessment study we conducted on Facebook. We report on our use of adapted versions of commonly used HCI research methods and lessons learned from this approach.
more »
Security and Privacy Issues with IoT in Healthcare
Appears in:
phat 18(14): e2

Authors:
Anil Chacko, Thaier Hayajneh

Downloads:
4069

Abstract:
In healthcare, the Internet of Things (IoT) oﬀers many beneﬁts, including being able to monitor patients more closely and using data for analytics. When it comes to IoT for medical device integration, the focus is shifted towards the consumer end, such as glucose meters, blood pressure cuﬀs, and ot…In healthcare, the Internet of Things (IoT) oﬀers many beneﬁts, including being able to monitor patients more closely and using data for analytics. When it comes to IoT for medical device integration, the focus is shifted towards the consumer end, such as glucose meters, blood pressure cuﬀs, and other devices designed to record data on patient vital signs. This enables healthcare providers to automatically collect information and apply decision support rules to allow for earlier intervention in the treatment process. Unfortunately, medical companies often do not consider the security risks of connecting these devices to the internet. There is a possibility that a zero-day exploit in a medical device can be used to injure or even kill someone without being detected. The rise in hackable medical devices has forced the FDA to issue formal guidance on how medical device makers should handle reports about cyber vulnerabilities. This paper aims to explore the role of IoT in healthcare, vulnerabilities, attacks, and security issues and solutions.
more »
Voice-Based Detection of Parkinson’s Disease through Ensemble Machine Learning Approach: A Performance Study
Appears in:
phat 19(19): e2

Authors:
Iqra Nissar, Danish Raza Rizvi, Sarfaraz Masood, Aqib Nazir Mir

Downloads:
3517

Abstract:
INTRODUCTION: Parkinson's disease (PD) occurs due to the deficiency of dopamine that regulates various activities of the human body. Researchers have identified that voice is an underlying symptom of PD. Recently, Machine learning (ML) has helped in solving problems of computer vision, natural la…INTRODUCTION: Parkinson's disease (PD) occurs due to the deficiency of dopamine that regulates various activities of
the human body. Researchers have identified that voice is an underlying symptom of PD. Recently, Machine learning
(ML) has helped in solving problems of computer vision, natural language processing, speech recognition etc.

OBJECTIVES: This paper aims to analyse the effect of feature type selection i.e. MFCC and TQWT on the efficiency of
voice based PD detection system along with the use an ensemble learning based classifier for this task.

METHODS: Hence, in this work, various machine learning models, including Logistic Regression, Naive Bayes, KNN,
Random Forest, Decision Tree, SVM, MLP, and XGBoost, have been employed and explored for PD detection purpose.
The task of Feature selection was also done using minimum-Redundancy and Maximum-Relevance (mRMR) and
Recursive Feature Elimination (RFE) techniques.

RESULTS: The results of the XGBoost with mRMR feature selection, outperformed all other models with a high accuracy
of 95.39% and precision, recall and F1-score of 0.95 each, when both MFCC and TQWT features were selected.

CONCLUSION: The results obtained strongly support the use of XGBoost model for the voice sample based detection of
PD along with mRMR feature selection technique.
more »
An Efficient Face Mask Detector with PyTorch and Deep Learning
Appears in:
phat 21(25): e4

Authors:
CMAK. Zeelan Basha, B.N. Lakshmi Pravallika, E. Bharani Shankar

Downloads:
3392

Abstract:
INTRODUCTION: The outbreak ofacoronavirus disease in 2019 (COVID-19) has created a global health epidemic that has had a major effect on the way we view our environment and our daily lives. The Covid-19 affected numbers are rising at a tremendous pace. Because of that, many countries face an econom…INTRODUCTION: The outbreak ofacoronavirus disease in 2019 (COVID-19) has created a global health epidemic that has had a major effect on the way we view our environment and our daily lives. The Covid-19 affected numbers are rising at a tremendous pace. Because of that, many countries face an economic catastrophe, recession, and much more. One thing we should do is to separate ourselves from society, remain at home, and detach ourselves from the outside world. But that's no longer a choice, people need to earn to survive, and nobody can remain indefinitely within their homes. As a precaution, people should wear masks while keeping social distance, but some ignore such things and walk around.

OBJECTIVES: To develop aFace Mask Detector with OpenCV, PyTorch, and Deep Learning that helps to detect whether or not a person wears a mask.

METHODS: A Neural Network model called ResNet is trained on the dataset. Furthermore, this work makes use of the inbuilt Face Detector after training. Finally, we predict whether or not a person is wearing a mask along with the percentage of the face covered or uncovered.

RESULTS: The validation results have been proposed to be 97% accurate when compared to applying different algorithms.

CONCLUSION: This Face Mask Detection System was found to be apt for detecting whether or not people wear masks in public places which contribute to their health and also to the health of their contacts in this COVID-19 pandemic.
more »
A Review of Medical Image Segmentation Algorithms
Appears in:
phat 21(27): e6

Authors:
K.K.D. Ramesh, G. Kiran Kumar, K. Swapna, Debabrata Datta, S. Suman Rajest

Downloads:
2569

Abstract:
INTRODUCTION: Image segmentation in medical physics plays a vital role in image analysis to identify the affected tumour. The process of subdividing an image into its constituent parts that are homogeneous in feature is called Image segmentation, and this proces…INTRODUCTION: Image segmentation in medical physics plays a vital role in image analysis to identify the affected tumour. The process of subdividing an image into its constituent parts that are homogeneous in feature is called Image segmentation, and this process concedes to extract some useful information. Numerous image segmentation techniques have been developed, and these techniques conquer different restrictions on conventional medical segmentation techniques. This paper presents a review of medical image segmentation techniques and statistical mechanics based on the novel method named as Lattice Boltzmann method (LBM). The beauty of LBM is to augment the computational speed in the process of medical image segmentation with an accuracy and specificity of more than 95% compared to traditional methods. As there is not much information on LBM in medical physics, it is intended to present a review of the research progress of LBM.

OBJECTIVE: As there is no review paper on the research progress of the LB method, this paper presents a review with an objective to give some thought regarding the different segmentation for medical image and novel LB method to advance interest for future investigation and exploration in medical image segmentation.

METHODS: This paper in attendance a short review of medical image segmentation techniques based on Thresholding, Region-based, Clustering, Edge detection, Model-based and the novel method Lattice Boltzmann method (LBM).

CONCLUSION: In this paper, we outlined various segmentation techniques applied to medical images, emphasize that none of these problem areas has been acceptably settled, and all of the algorithms depicted are available for broad improvement. Since LBM has the benefits of speed and adaptability of modelling to guarantee excellent image processing quality with a reasonable amount of computer resources, we predict that this method will become a new research hotspot in image processing.
more »
Future Prospective of Soft Computing Techniques in Psychiatric Disorder Diagnosis
Appears in:
phat 18(15): e1

Authors:
Manik Sharma, Natalia Romero

Downloads:
2514

Abstract:
more »
Overcoming Barriers to Healthcare Access and Delivery
Appears in:
phat 18(15): e2

Authors:
Foluso Ayeni, Zacchaeus Omogbadegun, Nicholas Omoregbe, Sanjay Misra, Lalit Garg

Downloads:
2406

Abstract:
Access to standard and economical health care delivery, availability of significant health information are viewed as some of the most functional public health interventions in present-day history. Despite that, current information obtained from the WHO regarding Nigeria’s health condition shows tha…Access to standard and economical health care delivery, availability of significant health information are viewed as some of the most functional public health interventions in present-day history. Despite that, current information obtained from the WHO regarding Nigeria’s health condition shows that the average existence expectancy is at 54 years and maternal mortality at 608 per 100,000 live births as a result of poor health care services. Several aspects of health informatics have been applied to solve these challenges such as the transformation of records from manual to electronic. Among these are the telemedicine and socialized healthcare, which have been barely adopted in developing nations. This work thus proposes an architectural framework for a cloud-supported socialized healthcare system. In order to achieve this; a webbased application software was designed and implemented through the use of cloud computing technology platforms and server side scripting tools. This study proves that socialized healthcare will really go a long way in defeating barriers of viable human access and delivery.
more »
Ear-Lead Multiple Smart Bio Sensor System in M-health
Appears in:
phat 16(6): e5

Authors:
Numan Celik, Wamadeva Balachandran, Nadarajah Manivannan

Downloads:
2336

Abstract:
In this paper, we present a multi-parameter wearable sensor system in conjunction with a smartphone to enable a real-time unobtrusive monitoring of core body temperature, electrocardiogram (ear-lead ECG), and blood oxygen saturation (SpO2) on ambulatory patients. Clinical research illustrating that…In this paper, we present a multi-parameter wearable sensor system in conjunction with a smartphone to enable a real-time unobtrusive monitoring of core body temperature, electrocardiogram (ear-lead ECG), and blood oxygen saturation (SpO2) on ambulatory patients. Clinical research illustrating that continuing accurate measurements of core body temperature (CBT) are crucial to investigate human thermoregulation in ambulatory environment and during activity. On the other hand, ECG remains the mainstay test for primary diagnosis and survival analysis of heart diseases. We implement a wireless multisensory system that measures both the tympanic temperature inside the ear and ECG data from an ear and an arm. The behind-the-Ear device makes desirable to measure ECG data without any chest belt and allow the patient to move around freely. The proposed Bluetooth device has similarity of a hearing aid and is wirelessly connected to a smartphone for data transmission and displaying. This device not only gives access to the core temperature and ECG data in real time, but also the device can be controlled – removed and reapplied – by the patient at any time, thus increasing the performance of personal health applications.
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Deep Medical Image Reconstruction with Autoencoders using Deep Boltzmann Machine Training
Appears in:
phat 20(24): e2

Authors:
Saravanan. S, Sujitha Juliet

Downloads:
2284

Abstract:
INTRODUCTION: Deep learning-based Image compression achieves a promising result in recent years as compared with the traditional transform coding methodology. Autoencoder, an unsupervised learning algorithm with the input value as same as that of the output value, is considered in this research wo…INTRODUCTION: Deep learning-based Image compression achieves a promising result in recent years as compared with the traditional transform coding methodology. Autoencoder, an unsupervised learning algorithm with the input value as same as that of the output value, is considered in this research work for effective medical image reconstruction.

OBJECTIVES: Medical data needs to be reconstructed without distorting the details present over it. A deep neural network that accepts the data and processes it to the other several layers and reconstructs that data is achieved by autoencoder.

METHODS: Deep Autoencoder is implemented in this methodology as it has been considered for high dimensionality reduction. Layer by layer pretraining is achieved using an approximate inference algorithm called Deep Boltzmann Machine.

RESULTS: The proposed method proves to be efficient when compared with the performance of the other autoencoders such as Deep Autoencoder with multiple Backpropagation (DA-MBP), Deep Autoencoder with RBM (DA-RBM) and Deep Convolutional Autoencoder with RBM (DCA-RBM).

CONCLUSION: Performance metrics are measured in terms of Mean Square Error, Structural similarity Index and PSNR.
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Low-threshold CMOS Rectifier Design for Energy Harvesting in Biomedical Sensors
Appears in:
phat 16(6): e4

Authors:
Mehmet Yuce, Ali Mohammadi, Jean-Michel Redoute

Downloads:
2080

Abstract:
The power transfer efficiency of energy harvesting systems is strongly dependent on the power conditioning circuits, especially rectifiers. The voltage drop across rectifier and its leakage current can drastically influence the efficiency. The hybrid energy harvesters impose even more severe co…The power transfer efficiency of energy harvesting systems
is strongly dependent on the power conditioning circuits,
especially rectifiers. The voltage drop across rectifier and
its leakage current can drastically influence the efficiency.
The hybrid energy harvesters impose even more severe constraints on the rectifier. The low Vth transistors and bulk
regulation technique are used in this work to mitigated the
voltage drop and leakage current, respectively. It has been
shown that the bulk regulation stops the current leakage
through body of PMOS transistor. A near zero threshold
cross connected CMOS rectifier is presented in this work using the standard 180nm UMC technology and experimental
analysis are carried out to evaluate the circuit performance.
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Publisher: EAI
ISSN: 2411-7145
Number of Volumes: 8

Last Published: 2022-12-20