Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749507
E. Sarra, T. Ezzedine
WBAN offers promising and innovative applications that enhance the quality of services provided by the healthcare system; it improves patient's quality of life and saves his lives in many situations. WBAN is composed of tiny medical devices on or implanted in the human body and continuously monitors patient's health. The wireless interface and the mobility of the body network enable easier, practical and less cost applications. WBAN provides uninterrupted distantly health monitoring of patient while he is doing his daily activity and it expect to efficiently deliver emergency collected vital signs to the concerned medical entity. However, the high contention level inside the WBAN, the presence of external collocated wireless network and the use of a shared medium, invoke packet collisions and thus affect the communication quality and reliability of the WBAN. Our goal in this article is to analyse the interference's problem of the WBAN based IEEE 802.15.4 protocol in the presence of Wi-Fi transmitters. We opt also for an adequate simulator and configurable mobility model to investigate different effects of the WBAN density as well as the increase number of Wi-Fi transmitters on the performance of the WBAN. We finally propose a simple, no cost and convenient parameters adjustment method to improve the WBAN's capacity, packet delivery, packet transmission and packet delay.
{"title":"Performance improvement of the wireless body area network (WBAN) under interferences","authors":"E. Sarra, T. Ezzedine","doi":"10.1109/HealthCom.2016.7749507","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749507","url":null,"abstract":"WBAN offers promising and innovative applications that enhance the quality of services provided by the healthcare system; it improves patient's quality of life and saves his lives in many situations. WBAN is composed of tiny medical devices on or implanted in the human body and continuously monitors patient's health. The wireless interface and the mobility of the body network enable easier, practical and less cost applications. WBAN provides uninterrupted distantly health monitoring of patient while he is doing his daily activity and it expect to efficiently deliver emergency collected vital signs to the concerned medical entity. However, the high contention level inside the WBAN, the presence of external collocated wireless network and the use of a shared medium, invoke packet collisions and thus affect the communication quality and reliability of the WBAN. Our goal in this article is to analyse the interference's problem of the WBAN based IEEE 802.15.4 protocol in the presence of Wi-Fi transmitters. We opt also for an adequate simulator and configurable mobility model to investigate different effects of the WBAN density as well as the increase number of Wi-Fi transmitters on the performance of the WBAN. We finally propose a simple, no cost and convenient parameters adjustment method to improve the WBAN's capacity, packet delivery, packet transmission and packet delay.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130030564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749440
Yair Enrique Rivera Julio
The paper focuses on the design of an open telematics architecture for telemedicine linked to a device mobile and ubiquitous, a standalone device with direct connection to the cellular data network LTE (Long Term Evolution). The device developed allows a multiplexing of biometric readings through adaptation of specialized Sensors and distributed in different parts of the body, which allow mapping the vitals signal: level of glycemia, Body Temperature Sensor, Blood Pressure Sensor, Pulse and Oxygen in Blood Sensor (SPO2), Airflow Sensor (Breathing), Galvanic Skin Response Sensor (GSR - Sweating), Electrocardiogram Sensor (ECG) and Electromyography Sensor (EMG). The system's modem (TELIT Le910) allows to obtain geo positioning signal of each patient in real time through GPS positioning GLONASS system. This set of data is sent and stored to a geographic health information system, where there is a specialized middleware for a georeferencing related in real time with those specialized health services and their physical infrastructures. A whole technological system that allows to take advantage of the services 4g and the geographic information systems of health monitoring care of patients with chronic diseases in Colombia, where there are some remote areas and difficult access.
{"title":"Design ubiquitous architecture for telemedicine based on mhealth Arduino 4G LTE","authors":"Yair Enrique Rivera Julio","doi":"10.1109/HealthCom.2016.7749440","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749440","url":null,"abstract":"The paper focuses on the design of an open telematics architecture for telemedicine linked to a device mobile and ubiquitous, a standalone device with direct connection to the cellular data network LTE (Long Term Evolution). The device developed allows a multiplexing of biometric readings through adaptation of specialized Sensors and distributed in different parts of the body, which allow mapping the vitals signal: level of glycemia, Body Temperature Sensor, Blood Pressure Sensor, Pulse and Oxygen in Blood Sensor (SPO2), Airflow Sensor (Breathing), Galvanic Skin Response Sensor (GSR - Sweating), Electrocardiogram Sensor (ECG) and Electromyography Sensor (EMG). The system's modem (TELIT Le910) allows to obtain geo positioning signal of each patient in real time through GPS positioning GLONASS system. This set of data is sent and stored to a geographic health information system, where there is a specialized middleware for a georeferencing related in real time with those specialized health services and their physical infrastructures. A whole technological system that allows to take advantage of the services 4g and the geographic information systems of health monitoring care of patients with chronic diseases in Colombia, where there are some remote areas and difficult access.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121755041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749490
Rute C. Sofia, S. Firdose, L. A. Lopes, W. Moreira, Paulo Mendes
In the context of social well-being and context awareness several eHealth applications have been focused on tracking activities, such as sleep or specific fitness habits, with the purpose of promoting physical well-being with increasing success. Sensing technology can, however, be applied to improve social well-being, in addition to physical well-being. This paper addresses NSense, a tool that has been developed to capture and to infer social interaction patterns aiming to assist in the promotion of social well-being. Experiments carried out under realistic settings validate the NSense performance in terms of its capability to infer social interaction context based on our proposed computational utility functions. Traces obtained during the experiments are available via the CRAWDAD international trace repository.
{"title":"NSense: A people-centric, non-intrusive opportunistic sensing tool for contextualizing nearness","authors":"Rute C. Sofia, S. Firdose, L. A. Lopes, W. Moreira, Paulo Mendes","doi":"10.1109/HealthCom.2016.7749490","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749490","url":null,"abstract":"In the context of social well-being and context awareness several eHealth applications have been focused on tracking activities, such as sleep or specific fitness habits, with the purpose of promoting physical well-being with increasing success. Sensing technology can, however, be applied to improve social well-being, in addition to physical well-being. This paper addresses NSense, a tool that has been developed to capture and to infer social interaction patterns aiming to assist in the promotion of social well-being. Experiments carried out under realistic settings validate the NSense performance in terms of its capability to infer social interaction context based on our proposed computational utility functions. Traces obtained during the experiments are available via the CRAWDAD international trace repository.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133792358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749419
V. Silva, M. Rodrigues, R. Barreto, V. Lucena
One of the biggest problems with chronical patients in treatment is medication adherence. Studies indicate that taking drugs out of time influence the patient's treatment decreasing the drugs effect. To minimize this problem, we developed a ubiquitous and intelligent system able to monitor the taking of medicines and to identify whether the patient is meeting the requirements prescribed by the doctor. An architecture provided with a decision system based on rules and trees to evaluate data collected from an intelligent medicine cabinet, sensors and electronic devices available in the patient's home was designed. The system classified the drugs taken pattern and released messages on social networks, SMS, and consumer electronic devices such as TV, smartphone and tablets, without human interference. Its goal is to help keeping the medication on time and helping to decide what to do in case of missing the right time. The algorithms J48, Rep and Random tree, were tested to classify the taking medicine patterns and to chose the right services available. The obtained results are very promising and reached an acceptable accuracy rate.
{"title":"UbMed: A ubiquitous system for monitoring medication adherence","authors":"V. Silva, M. Rodrigues, R. Barreto, V. Lucena","doi":"10.1109/HealthCom.2016.7749419","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749419","url":null,"abstract":"One of the biggest problems with chronical patients in treatment is medication adherence. Studies indicate that taking drugs out of time influence the patient's treatment decreasing the drugs effect. To minimize this problem, we developed a ubiquitous and intelligent system able to monitor the taking of medicines and to identify whether the patient is meeting the requirements prescribed by the doctor. An architecture provided with a decision system based on rules and trees to evaluate data collected from an intelligent medicine cabinet, sensors and electronic devices available in the patient's home was designed. The system classified the drugs taken pattern and released messages on social networks, SMS, and consumer electronic devices such as TV, smartphone and tablets, without human interference. Its goal is to help keeping the medication on time and helping to decide what to do in case of missing the right time. The algorithms J48, Rep and Random tree, were tested to classify the taking medicine patterns and to chose the right services available. The obtained results are very promising and reached an acceptable accuracy rate.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128028347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HEALTHCOM.2016.7749510
M. Mettler
Blockchain technology has shown its considerable adaptability in recent years as a variety of market sectors sought ways of incorporating its abilities into their operations. While so far most of the focus has been on the financial services industry, several projects in other service related areas such as healthcare show this is beginning to change. Numerous starting points for Blockchain technology in the healthcare industry are the focus of this report. With examples for public healthcare management, user-oriented medical research and drug counterfeiting in the pharmaceutical sector, this report aims to illustrate possible influences, goals and potentials connected to this disruptive technology.
{"title":"Blockchain technology in healthcare: The revolution starts here","authors":"M. Mettler","doi":"10.1109/HEALTHCOM.2016.7749510","DOIUrl":"https://doi.org/10.1109/HEALTHCOM.2016.7749510","url":null,"abstract":"Blockchain technology has shown its considerable adaptability in recent years as a variety of market sectors sought ways of incorporating its abilities into their operations. While so far most of the focus has been on the financial services industry, several projects in other service related areas such as healthcare show this is beginning to change. Numerous starting points for Blockchain technology in the healthcare industry are the focus of this report. With examples for public healthcare management, user-oriented medical research and drug counterfeiting in the pharmaceutical sector, this report aims to illustrate possible influences, goals and potentials connected to this disruptive technology.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"388 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116485954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749451
F. Nammour, K. Danas, N. Mansour
Patient information in healthcare organizations is distributed across several systems and data silos. Clinicians make decisions based on data in patient health records. Improving the efficiency of decision-support requires collective knowledge of all patient information. The classical approach of linking patient data from many databases into one data warehouse poses various problems when it comes to building clinical analytics. An implementation of the Performance Measurement and Management approach used in Engineering and Business is adapted to healthcare scenarios, and a new system is developed that allows clinicians that are not technical professionals to develop, test and apply custom analytics to patient health data. Part I of this paper is an introduction to the problems and current situation in healthcare data analytics. Part II states the aim and objectives. Part III explains the system design and its modular components. Part IV presents the results of three performance indicators evaluated through the system, and evaluates the system through technical and clinical usability methods. Part V concludes and discusses future work.
{"title":"CorporateMeasures: A clinical analytics framework leading to clinical intelligence","authors":"F. Nammour, K. Danas, N. Mansour","doi":"10.1109/HealthCom.2016.7749451","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749451","url":null,"abstract":"Patient information in healthcare organizations is distributed across several systems and data silos. Clinicians make decisions based on data in patient health records. Improving the efficiency of decision-support requires collective knowledge of all patient information. The classical approach of linking patient data from many databases into one data warehouse poses various problems when it comes to building clinical analytics. An implementation of the Performance Measurement and Management approach used in Engineering and Business is adapted to healthcare scenarios, and a new system is developed that allows clinicians that are not technical professionals to develop, test and apply custom analytics to patient health data. Part I of this paper is an introduction to the problems and current situation in healthcare data analytics. Part II states the aim and objectives. Part III explains the system design and its modular components. Part IV presents the results of three performance indicators evaluated through the system, and evaluates the system through technical and clinical usability methods. Part V concludes and discusses future work.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124840841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749508
Zhiqiang Liu, B. Liu, C. Chen
Wireless Body Area Network (WBAN) represents one of the most promising networks to provide health applications for improving the quality of life, such as ubiquitous e-Health services and real-time health monitoring. The resource allocation of an energy-constrained, heterogeneous WBAN is a critical issue that should consider both energy efficiency and Quality of Service (QoS) requirements with the dynamic link characteristics, especially when the limited resource cannot satisfy the expected QoS requirements. In this paper, a buffer aware Energy-efficient and QoS-effective resource allocation scheme is proposed in which the sensor queue buffer states, constraints of QoS metrics and the characteristics of dynamic links are considered. Specifically, a buffer aware sensor evaluation method is designed to dynamically evaluate the sensor state with considering the sensor buffer states for improving the system performance. We then formulate the resource allocation problem for optimizing the transmission power, the transmission rate and the allocated time slots for each sensor to minimize the sum mix-cost, which is defined to characterize the energy cost and QoS cost between attainable QoS support and QoS requirements. Simulation results demonstrate the effectiveness of the buffer aware sensor evaluation method and the proposed energy-efficient and QoS-effective resource allocation scheme.
{"title":"Buffer-aware and QoS-effective resource allocation scheme in WBANs","authors":"Zhiqiang Liu, B. Liu, C. Chen","doi":"10.1109/HealthCom.2016.7749508","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749508","url":null,"abstract":"Wireless Body Area Network (WBAN) represents one of the most promising networks to provide health applications for improving the quality of life, such as ubiquitous e-Health services and real-time health monitoring. The resource allocation of an energy-constrained, heterogeneous WBAN is a critical issue that should consider both energy efficiency and Quality of Service (QoS) requirements with the dynamic link characteristics, especially when the limited resource cannot satisfy the expected QoS requirements. In this paper, a buffer aware Energy-efficient and QoS-effective resource allocation scheme is proposed in which the sensor queue buffer states, constraints of QoS metrics and the characteristics of dynamic links are considered. Specifically, a buffer aware sensor evaluation method is designed to dynamically evaluate the sensor state with considering the sensor buffer states for improving the system performance. We then formulate the resource allocation problem for optimizing the transmission power, the transmission rate and the allocated time slots for each sensor to minimize the sum mix-cost, which is defined to characterize the energy cost and QoS cost between attainable QoS support and QoS requirements. Simulation results demonstrate the effectiveness of the buffer aware sensor evaluation method and the proposed energy-efficient and QoS-effective resource allocation scheme.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124904361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749499
G. Tommasone, M. Bazzani, V. Solinas, P. Serafini
Health education for pregnant women is one of the aims chased by using mobile applications for health prevention and healthy lifestyle promotion. The literature claims the lack of mobile applications with evidence-based information and supported by health professionals. This paper deals with the design, the implementation, and the evaluation of a service for healthy women with a normal pregnancy aimed at promoting healthy lifestyles, monitoring the eating habits and the physical activity, for educational purposes and overweight and obesity prevention in pregnancy.
{"title":"Midwifery E-Health: From design to validation of “Mammastyle — Gravidanza Fisiologica”","authors":"G. Tommasone, M. Bazzani, V. Solinas, P. Serafini","doi":"10.1109/HealthCom.2016.7749499","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749499","url":null,"abstract":"Health education for pregnant women is one of the aims chased by using mobile applications for health prevention and healthy lifestyle promotion. The literature claims the lack of mobile applications with evidence-based information and supported by health professionals. This paper deals with the design, the implementation, and the evaluation of a service for healthy women with a normal pregnancy aimed at promoting healthy lifestyles, monitoring the eating habits and the physical activity, for educational purposes and overweight and obesity prevention in pregnancy.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"317 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122151780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749452
Chengliang Yang, C. Delcher, E. Shenkman, S. Ranka
Inpatient hospital readmissions for potentially avoidable conditions are problematic and costly. In this paper, we build machine learning models using variables widely available in health claims data to predict patients' 30-day readmission risks at the time of discharge. These models show high predictive power on a U.S. nationwide readmission database. They are also capable of providing interpretable risk factors globally at the population level and locally associated with each single discharge. In addition, we propose a model-agnostic approach to provide confidence for each prediction. Altogether, using models with high predictive power, interpretable risk factors and prediction confidence may enable health care systems to accurately target high-risk patients and prevent recurrent readmissions by accurately anticipating the probability of readmission at the point of care.
{"title":"Predicting 30-day all-cause readmissions from hospital inpatient discharge data","authors":"Chengliang Yang, C. Delcher, E. Shenkman, S. Ranka","doi":"10.1109/HealthCom.2016.7749452","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749452","url":null,"abstract":"Inpatient hospital readmissions for potentially avoidable conditions are problematic and costly. In this paper, we build machine learning models using variables widely available in health claims data to predict patients' 30-day readmission risks at the time of discharge. These models show high predictive power on a U.S. nationwide readmission database. They are also capable of providing interpretable risk factors globally at the population level and locally associated with each single discharge. In addition, we propose a model-agnostic approach to provide confidence for each prediction. Altogether, using models with high predictive power, interpretable risk factors and prediction confidence may enable health care systems to accurately target high-risk patients and prevent recurrent readmissions by accurately anticipating the probability of readmission at the point of care.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116885785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/HealthCom.2016.7749461
Mohamed Abomhara, M. B. Lazreg
A work-based access control (WBAC) model is proposed by introducing the team role concept and modifying the user-role assignment model from a previous work. The main goals of WBAC are flexibility, easy manageability, security, as well as suitability to support cooperative work of dynamic teams in healthcare environments. One of the major challenges of WBAC regards authorization constraints in terms of organizational policies. In this article, we show how Unified Modeling Language (UML) and Object Constraints Language (OCL) are utilized to design and analyze the authorization constraints of WBAC in cooperative engagements with complex scenarios in the collaborative healthcare domain. We also demonstrate how the authorization constraints expressed in OCL can be implemented, tested and validated using the Eclipse Modeling Framework (EMF) tool. Using EMF, the modeling and validation of OCL constraints were smooth and straightforward tasks which can help the policy designers in many organizations during designing or/and analyzing of access control policies.
{"title":"UML/OCL-based modeling of work-based access control policies for collaborative healthcare systems","authors":"Mohamed Abomhara, M. B. Lazreg","doi":"10.1109/HealthCom.2016.7749461","DOIUrl":"https://doi.org/10.1109/HealthCom.2016.7749461","url":null,"abstract":"A work-based access control (WBAC) model is proposed by introducing the team role concept and modifying the user-role assignment model from a previous work. The main goals of WBAC are flexibility, easy manageability, security, as well as suitability to support cooperative work of dynamic teams in healthcare environments. One of the major challenges of WBAC regards authorization constraints in terms of organizational policies. In this article, we show how Unified Modeling Language (UML) and Object Constraints Language (OCL) are utilized to design and analyze the authorization constraints of WBAC in cooperative engagements with complex scenarios in the collaborative healthcare domain. We also demonstrate how the authorization constraints expressed in OCL can be implemented, tested and validated using the Eclipse Modeling Framework (EMF) tool. Using EMF, the modeling and validation of OCL constraints were smooth and straightforward tasks which can help the policy designers in many organizations during designing or/and analyzing of access control policies.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"559 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115998467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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