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 Manik Sharma

Aims & Scope
Indexing
Editorial Board

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
Manik Sharma, DAV University, India
Area Editors
Anind Dey (University of Washington)
Ansar-Ul-Haque Yasar (Hasselt University, Belgium)
Alejandro Dominguez Rodriguez (Autonomous University of Baja California)
Alexandros Tzallas (Technological Educational Institute of Epirus)
Asimina Kiourti (The Ohio State University)
AtaUllah Ghafoor (National University of Modern Languages, Islamabad, Pakistan.)
Arijit Ukil (Tata Consultancy Services)
Bert Arnrich (Boğaziçi University, Istanbul, Turkey)
Daojing He (South China University of Technology, China)
Emilija Stojmenova (Duh University of Ljubljana)
Frank Wallhoff (Jade University of Applied Sciences)
Honggang Wang (UMASS. USA)
Kashif Saleem (King Saud University)
Laszlo Bokor (BME, Hungary)
Marcela Deyanira Rodriguez Urrea (Autonomous University of Baja California)
Mauro Femminella (University of Perugia, Italy)
Melina Frenken (Jade University of Applied Sciences)
Mohammad Upal Mahfuz (University of Wisconsin-Green Bay)
Mosabber Uddin Ahmed (University of Dhaka)
Mojtaba Taherisadr (University of Michigan)
Nadeem Javaid (COMSATS Institute of Information Technology, Islamabad, Pakistan)
Pietro Cipresso (Istituto Auxologico, Milan, Italy)
Razan Hamed (New York Institute of Technology, NY, USA)
Silvia Serino (Catholic University of Milan, Italy)
Stefan Rahr Wagner (Aarhus University)
Tanvir Zia (School of Computing & Mathematics, Charles Sturt University, Australia)
Venet Osmani (CREATE-NET, Trento, Italy)
Wilko Heuten (OFFIS, Germany)
Tessa Dekkers (Delft University, The Netherlands)
Saikishor Jangiti (SASTRA Deemed University, India)
Zhihan Lv (Qingdao University, China)
Antonella Carbonaro (Universita' di Bologna, Italy)
Giorgos Giannakakis (Foundation for Research and Technology Hellas, Greece)
Alessandro Ruggiero (University of Salerno, Italy)
Eduard Babulak (National Science Foundation, USA)
Emilio Serrano (Technical University of Madrid, Spain)
Riccardo Martoglia (University of Modena and Reggio Emilia, Italy)
Alberto Antonietti (École Polytechnique Fédérale de Lausanne, Switzerland)
Netzahualcoyotl Hernandez-Cruz (Ulster University, UK)
Pan Zheng, University of Canterbury, New Zealand

Recently Published
Most Popular

Evaluation Model of Telemedicine Service Quality Based on Machine Sensing Vision
Appears in:
phat 22(3): 5

Authors:
Yingdong Cao, Hui Li, Zeqi Xie, Zhenti Cui, Loknath Sai Ambati

Published:
4th Aug 2022

Abstract:
INTRODUCTION: At present, the common telemedicine service quality evaluation methods can not obtain the key evaluation indicators, which leads to the low accuracy and low user satisfaction. OBJECTIVES: This paper constructs a telemedicine service quality evaluation model based on machine vision te…INTRODUCTION: At present, the common telemedicine service quality evaluation methods can not obtain the key evaluation indicators, which leads to the low accuracy and low user satisfaction.
OBJECTIVES: This paper constructs a telemedicine service quality evaluation model based on machine vision technology.
METHODS: Machine vision technology is used to obtain telemedicine service information, preliminarily select service quality assessment indicators, complete the selection of indicators, build a telemedicine service quality assessment indicator system, adopt subjective and objective combination method to calculate the weight of service quality assessment indicators, and combine matter element analysis method to build a telemedicine service quality assessment model.
RESULTS: The experimental results show that the Cronhach a is higher than 0.7, the Barthel index is higher than 90, and the satisfaction of many users is more than 90%.
CONCLUSION: The proposed method solves the problems existing in the current method and lays a foundation for the development of telemedicine service technology.
more »
Multi index evaluation method of pathological weight loss effect of aerobic exercise based on telemedicine monitoring
Appears in:
phat 22(3): 4

Authors:
Lei Du, Ramy Amer

Published:
28th Jul 2022

Abstract:
INTRODUCTION: Pathological obesity seriously endangers human health. OBJECTIVES: A multi index evaluation method of pathological weight loss effect of aerobic exercise based on telemedicine monitoring is proposed to evaluate the pathological weight loss effect of aerobic exercise by using telemedi…INTRODUCTION: Pathological obesity seriously endangers human health.
OBJECTIVES: A multi index evaluation method of pathological weight loss effect of aerobic exercise based on telemedicine monitoring is proposed to evaluate the pathological weight loss effect of aerobic exercise by using telemedicine monitoring system.
METHODS: According to the indexes of aerobic exercise affecting weight loss effect, a multi index evaluation system of pathological weight loss effect of aerobic exercise was established. The medical sensor of the telemedicine monitoring system is used to collect the index data in the multi index evaluation system of pathological obese personnel. The medical sensor uses the wireless node to transmit the collected data to the remote monitoring center. The evaluation module of the remote monitoring center uses the collected data and selects the fuzzy comprehensive evaluation method to evaluate the pathological weight loss effect of aerobic exercise.
RESULTS: The experimental results show that this method can effectively use the telemedicine monitoring system to collect the physiological parameters of pathological obese people, and use the parameter collection results to evaluate the effect of aerobic exercise on pathological weight loss.
CONCLUSION: The proposed methods can provide basis for human aerobic exercise pathological weight loss.
more »
Anatomical mining method of cervical nerve root syndrome under visual sensing technology
Appears in:
phat 22(3): 3

Author:
Xianghua Wu

Published:
28th Jul 2022

Abstract:
INTRODUCTION: The gray resolution of anatomical image of cervical nerve root syndrome is low, that can not be mined accurately. OBJECTIVES: Aiming at the defect of low gray resolution of anatomical images, an image mining method using visual perception technology was studied. METHODS: According …INTRODUCTION: The gray resolution of anatomical image of cervical nerve root syndrome is low, that can not be mined accurately.
OBJECTIVES: Aiming at the defect of low gray resolution of anatomical images, an image mining method using visual perception technology was studied.
METHODS: According to the visual perception technology, the internal parameter matrix and external parameter matrix of binocular visual camera were determined by coordinate transformation, and the anatomical images of cervical nerve root syndrome were collected. The collected images are smoothed and enhanced by nonlinear smoothing algorithm and multi-scale nonlinear contrast enhancement method. The directional binary simple descriptor method is selected to extract the features of the enhanced image; Using K-means clustering algorithm, the anatomical image mining of cervical nerve root syndrome is completed by obtaining the initial clustering center and image mining.
RESULTS: Experimental results show that the information entropy of the images mined by the proposed method is higher than 5, the average gradient is greater than 7, the edge information retention is greater than 0.7, the peak signal-to-noise ratio is higher than 30 dB, and the similarity of the same category of images is greater than 0.9.
CONCLUSIONS: This method can effectively mine the anatomical images of cervical nerve root syndrome and provide an important basis for the diagnosis and treatment of cervical nerve root syndrome.
more »
Remote consultation image stitching method based on wireless sensor technology and mathematical morphology
Appears in:
phat 22(31): 5

Author:
Xiaoge Li

Published:
27th Jul 2022

Abstract:
INTRODUCTION: In order to obtain seamless and high-precision remote consultation image mosaic results, a remote consultation image mosaic method based on wireless sensor technology and mathematical morphology is studied. A consultation image acquisition unit based on wireless sensor technology is d…INTRODUCTION: In order to obtain seamless and high-precision remote consultation image mosaic results, a remote consultation image mosaic method based on wireless sensor technology and mathematical morphology is studied. A consultation image acquisition unit based on wireless sensor technology is designed, and the remote consultation image signal is collected by sensor; In the process of signal conditioning, a filter based on mathematical morphology is used to reduce the influence of noise on the accuracy of remote consultation image acquisition.
OBJECTIVES: Compressed sensing technology is used to realize the compression, transmission and recovery of consultation image sampling data.
METHODS: After preprocessing the image through shadow correction, surf algorithm is used to construct the scale space to determine the main direction of feature points in the image; The extended surf descriptor is constructed based on feature points for consultation image registration.
RESULTS: Based on the spatial transformation relationship between images, the improved gradual in and gradual out stitching method is used to complete the remote consultation image stitching. Experimental results show that this method can accurately collect consultation image signals, and the corresponding rate of the feature point extraction results reaches nearly 99%, which is relatively robust.
CONCLUSION: The RMSE error of the image registration results is less than 2.692, which improves the accuracy of the remote consultation image stitching results, well solves the problem of image visual field reduction, and there is no seam in the stitching area.
more »
A remote consultation system for sports injury based on wireless sensor network
Appears in:
phat 22(31): 4

Authors:
Hongming Guo, Ting Yang

Published:
27th Jul 2022

Abstract:
INTRODUCTION: Although current research methods can realize the effective collection of human physiological signals in the health monitoring system, they cannot obtain the ideal detection effect due to the influence of the communication performance in the health monitoring system. OBJECTIVES: In o…INTRODUCTION: Although current research methods can realize the effective collection of human physiological signals in the health monitoring system, they cannot obtain the ideal detection effect due to the influence of the communication performance in the health monitoring system.
OBJECTIVES: In order to improve the monitoring performance of remote consultation, a sports injury remote consultation system based on wireless sensor network is designed.
METHODS: The wearable sensors is used in the body area network to collect human physiological signals. Through the wireless sensor network of the wireless communication module, the collected human physiological signals are transmitted to the remote consultation module. The wireless communication module selects CC2530 chip as the core chip of the wireless communication module. A fixed partition routing algorithm based on energy balance is used to stably transmit human physiological signals.
RESULTS: The consultation personnel of the remote consultation module make a sports injury consultation judgment based on the received physiological signal results of the human body. The system test results show that the designed system can accurately monitor various physiological indicators of the human body. The wireless sensor network energy consumption of the system in this paper is all less than 500J, the energy consumption variance of the cluster head is less than 4×10-3, and the number of surviving nodes can be guaranteed to be higher than 130. It has high communication performance of wireless sensor network.
CONCLUSION: The system can accurately judge whether there is a sports injury according to the monitoring results of physiological indicators, and realize the effective consultation of sports injury.
more »
Diagnosis of abnormal body temperature based on deep neural network
Appears in:
phat 22(3): 2

Authors:
Jinxiang Peng, Li Zhang

Published:
27th Jul 2022

Abstract:
INTRODUCTION: A method for diagnosing abnormal body temperature based on deep neural network is proposed. OBJECTIVES: To improve the diagnostic accuracy, reduce the false alarm rate, and improve the diagnostic level of abnormal body temperature. METHODS: According to the weight of the temperature…INTRODUCTION: A method for diagnosing abnormal body temperature based on deep neural network is proposed.
OBJECTIVES: To improve the diagnostic accuracy, reduce the false alarm rate, and improve the diagnostic level of abnormal body temperature.
METHODS: According to the weight of the temperature sensor node itself and its neighbor nodes, the network trust relationship is established, and the node trust value is output through the combination of decision-making. Use trust value and double threshold to identify and remove malicious nodes, and optimize the network structure. The optimized temperature sensor network is used to collect human body temperature data.
RESULTS: A deep neural network is used to construct a diagnosis model of abnormal body temperature, so as to realize the diagnosis of abnormal body temperature.
CONCLUSION: The experimental results show that the method in this paper has high diagnostic accuracy, low false positive rate and high diagnostic efficiency, and can improve the diagnostic level of abnormal body temperature.
more »
Design of remote injury diagnosis system for Wushu competition based on wireless sensor network
Appears in:
phat 22(3): 1

Author:
Chunguang Pan

Published:
27th Jul 2022

Abstract:
INTRODUCTION: In this paper, a remote injury diagnosis system for Wushu competition based on wireless sensor network is designed to improve the safety of athletes in the process of Wushu competition. OBJECTIVES: Improve the safety of athletes during martial arts competitions. METHODS: The pulse s…INTRODUCTION: In this paper, a remote injury diagnosis system for Wushu competition based on wireless sensor network is designed to improve the safety of athletes in the process of Wushu competition.
OBJECTIVES: Improve the safety of athletes during martial arts competitions.
METHODS: The pulse sensor, temperature sensor and ECG sensor are set as the terminal nodes of the remote injury diagnosis system for Wushu competition. The physiological parameters of athletes in Wushu competition are collected by the sensor, and the collected parameters are transmitted to the wireless RF module. The wireless RF module uses the wireless sensor network to realize the wireless communication of various parameter data through the routing node and terminal node, and transmits the data to the remote diagnosis module. The remote diagnosis module uses the collected physiological parameters of athletes to realize the remote diagnosis of injury in Wushu competition through particle swarm optimization-support vector machine diagnosis model.
RESULTS: The experimental results show that the designed system can remotely collect the physiological parameters of athletes in Wushu competition, and remotely diagnose the injury of Wushu competition according to the collected data, and the diagnosis accuracy is as high as 99%.
CONCLUSION: It has good safety performance and is of practical significance.
more »
Remote medical video region tamper detection system based on Wireless Sensor Network
Appears in:
phat 22(31): 3

Authors:
Sujuan Li, Shichen Huang

Published:
26th Jul 2022

Abstract:
INTRODUCTION: A new telemedicine video tamper detection system based on wireless sensor network is proposed and designed in this paper. OBJECTIVES: This work is proposed to improve the performance of telemedicine video communication and accurately detect the tamper area in telemedicine video. MET…INTRODUCTION: A new telemedicine video tamper detection system based on wireless sensor network is proposed and designed in this paper.
OBJECTIVES: This work is proposed to improve the performance of telemedicine video communication and accurately detect the tamper area in telemedicine video.
METHODS: The sensor nodes in the sensing layer are responsible for collecting telemedicine video information and transmitting the information to the data layer. The data layer completes the storage of information and transmits it to the processing layer. The detection module of the processing layer detects the tampered area of the telemedicine video through two parts: suspicious moving point calculation and tamper detection, and transmits the detection results to the application display layer for display.
RESULTS: The experimental results show that the designed detection system can accurately detect the tampered area in the telemedicine video, and the packet loss rate is significantly reduced, and the maximum packet loss rate is no more than 1%.
CONCLUSION: The proposed detection system for remote medical video based on wireless sensor network can better meet the requirements of region tamper detection.
more »
E-appointments at primary care physicians during Covid-19 pandemic: viewpoint and satisfaction of medical consumers
Appears in:
phat 22(31): 2

Authors:
Viktor Denkovski, Goce Gavrilov

Published:
23rd May 2022

Abstract:
INTRODUCTION: Use of e-appointment systems in primary care (EASPC) is a common practice in western countries, however, there is no evidence of implementation in R. N. Macedonia and other similar countries in development. OBJECTIVES: This study explores the viewpoints and satisfaction of medical co…INTRODUCTION: Use of e-appointment systems in primary care (EASPC) is a common practice in western countries, however, there is no evidence of implementation in R. N. Macedonia and other similar countries in development.
OBJECTIVES: This study explores the viewpoints and satisfaction of medical consumers (MC) on EASPC, and the impact of Covid-19 global pandemic concerning their appointments at primary care physicians.
METHODS: A survey on MC above the age of 15 years was conducted in July 2020. The results were analysed in SPSS 23.
RESULTS: The majority of participants were in favour on implementing an EASPC despite their neutral satisfaction with the walk-in method. Furthermore, they were confident in its effectiveness in the fight against spreading of Covid-19.
CONCLUSION: The MC opinion and satisfaction is crucial when developing health care systems and their implementation as a mix of services. For the system to succeed, it must be financed and supported adequately and as such, further research is necessary to explore a real-time EASPC usage.
more »
The associations between mental health and environmental factors in New Zealand: A region-based analytical study
Appears in:
phat 22(31): 1

Authors:
Morten Viehoff, Daniel Grossman, Leona Huang, Jianwei Jiang, Pan Zheng

Published:
5th May 2022

Abstract:
INTRODUCTION: Connections between environmental factors and mental health issues have been postulated in many different countries around the world. Previously undertaken research has shown many possible connections between these fields, especially in relation to air quality and extreme weather even…INTRODUCTION: Connections between environmental factors and mental health issues have been postulated in many different countries around the world. Previously undertaken research has shown many possible connections between these fields, especially in relation to air quality and extreme weather events. However, research on this subject is lacking in New Zealand, which is difficult to analyse as an overall nation due to its many micro-climates and regional differences.
OBJECTIVES: The aim of this study and subsequent analysis is to explore the associations between environmental factors and poor mental health outcomes in New Zealand by region and predict the number of people with mental health-related illnesses corresponding to the environmental influence.
METHODS: Data are collected from various public-available sources, e.g., Stats NZ and Coronial services of New Zealand, which comprised four environmental factors of our interest and two mental health indicators data ranging from 2016 up until 2020. The four environmental factors are air pollution, earthquakes, rainfall and temperature. Two mental health indicators include the number of people seen by District Health Boards (DHBs) for mental health reasons and the statistics on suicide deaths. The initial analysis is carried out on which regions were most affected by the chosen environmental factors. Further analysis using Auto-Regressive Integrated Moving Average(ARIMA) creates a model based on time series of environmental data to generate estimation for the next two years and mental health projected from the ridge regression.
RESULTS: In our initial analysis, the environmental data was graphed along with mental health outcomes in regional charts to identify possible associations. Different regions of New Zealand demonstrate quite different relationships between the environmental data and mental health outcomes. The result of later analysis predicts that the suicide rate and DHB mental health visits may increase in Wellington, drop-in Hawke's Bay and slightly increase in Canterbury for the year 2021 and 2022 with different environmental factors considered.
CONCLUSION: It is evident that the relationship between environmental and mental health factors is regional and not national due to the many micro-climates that exist around the nation. However, it was observed that not all factors displayed a good relationship between the regions. We conclude that our hypotheses were partially correct, in that increased air pollution was found to correlate to increased mental health-related DHB visits. Rainfall was also highly correlated to some mental health outcomes. Higher levels of rainfall reduced DHB visits and suicide rates in some areas of the country.
more »

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:
6007

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 »
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:
2856

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 »
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:
2564

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 »
Security and Privacy Issues with IoT in Healthcare
Appears in:
phat 18(14): e2

Authors:
Anil Chacko, Thaier Hayajneh

Downloads:
2251

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 »
Future Prospective of Soft Computing Techniques in Psychiatric Disorder Diagnosis
Appears in:
phat 18(15): e1

Authors:
Manik Sharma, Natalia Romero

Downloads:
2213

Abstract:
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:
2131

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.
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:
2016

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 »
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:
1906

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.
more »
Designing a resilient supply chain: An approach to reduce drug shortages in epidemic outbreaks
Appears in:
phat 20(21): e2

Authors:
Jose Antonio Lozano-Diez, Jose Antonio Marmolejo-Saucedo, Roman Rodriguez-Aguilar

Downloads:
1663

Abstract:
INTRODUCTION: Supply network design is a long-studied topic that has evolved to address disruptive situations. The risk of supply chain disruption leads to the development of resilient supply chains that are capable of reacting eﬀectively. OBJECTIVES: In the context of public health, drug suppl…INTRODUCTION: Supply network design is a long-studied topic that has evolved to address disruptive situations. The risk of supply chain disruption leads to the development of resilient supply chains that are capable of reacting eﬀectively.

OBJECTIVES: In the context of public health, drug supply networks face shortage challenges in many situations, such as current epidemic outbreaks such as COVID-19. Drug shortages can occur due to manufacturing problems, lack of infrastructure, and immediate reaction mechanisms.

METHODS: The case study is solved with anyLogistix optimization and simulation software.

RESULTS: We present the results of a hypothetical study on the impact of COVID-19 on a regional supply network. The results of this research are intended to be the basis for the design of resilient supply chains in epidemic outbreaks.

CONCLUSION: Drug providers should consider strategies to prevent or reduce the impact of shortages as well as disruption spreads.
more »
Body-IMU autocalibration for inertial hip and knee joint tracking
Appears in:
phat 16(5): e3

Authors:
Sarvenaz Salehi, Gabriele Bleser, Attila Reiss, Didier Stricker

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1648

Abstract:
Sensor to body calibration is a key requirement for capturing accurate body movements in applications based on wearable systems. In this paper, we consider the specific problem of estimating the positions of multiple inertial measurement units (IMUs) relative to the adjacent body joints. To deriv…Sensor to body calibration is a key requirement for capturing accurate body movements in applications based on wearable systems.
In this paper, we consider the specific problem of estimating the positions of multiple inertial measurement units (IMUs) relative to
the adjacent body joints. To derive an efficient, robust and precise method based on a practical procedure is a crucial as well as
challenging task when developing a wearable system with multiple
embedded IMUs. In this work, first, we perform a theoretical analysis of an existing position calibration method, showing its limited
applicability for the hip and knee joint. Based on this, we propose a method for simultaneously estimating the positions of three IMUs
(mounted on pelvis, upper leg, lower leg) relative to these joints.
The latter are here considered as an ensemble. Finally, we perform
an experimental evaluation based on simulated and real data, showing the improvements of our calibration method as well as lines of future work.
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Publisher: EAI
ISSN: 2411-7145
Number of Volumes: 8

Last Published: 2022-07-27