Significance level of a query for enterprise data
- Authors: Thi Ngoc Dinh, Loan , Karmakar, Gour , Kamruzzaman, Joarder , Stranieri, Andrew , Das, Rajkumar
- Date: 2017
- Type: Text , Conference proceedings
- Relation: 30th International Business Information Management Association Conference - Vision 2020: Sustainable Economic development, Innovation Management, and Global Growth, IBIMA 2017; Madrid, Spain; 8th-9th November 2017 Vol. 2017-January, p. 4494-4504
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- Description: To operate enterprise activities, a large number of queries need to be processed every day through an enterprise system. Consequently, such a system frequently faces hugely overloaded information and incurs high delay in producing query responses for big data. This is because, traditional queries are normally treated with equal importance. With the advent of big data and its use in enterprise systems and the growth of process complexity, the traditional approach of query processing is no more suitable as it does not consider semantic information and captures all data irrespective of their relevance to a business organization, which eventually increases the computational time in both big data collection and analysis. The significance level of a query can make a trade-off between query response delay and the extent of data collection and analysis. This motivates us to concentrate on determining the significance level of a query considering its importance to an enterprise system. To our knowledge, no such approach is available in the literature. To bridge this research gap, this paper, for the first time, proposes an approach to determine the significance level of a query to prioritize them with the relevance to a business organization. As business processes play key roles in any enterprise system and all business processes are not equally important, this is done by determining the semantic similarity between a query and the processes of a business organization and the importance of a business process to that organization. With a case study on an enterprise system of a retail company, the results produced by our proposed approach have shown that significance level is higher for more important queries compared to the less important ones.
A patient agent to manage blockchains for remote patient monitoring
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2018
- Type: Text , Conference proceedings
- Relation: 7th International Conference on Global Telehealth, GT 2018; Colombo, Sri Lanka; 10th-11th October 2018; published in Studies in Health Technology and Informatics Vol. 254, p. 105-115
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- Description: Continuous monitoring of patient's physiological signs has the potential to augment traditional medical practice, particularly in developing countries that have a shortage of healthcare professionals. However, continuously streamed data presents additional security, storage and retrieval challenges and further inhibits initiatives to integrate data to form electronic health record systems. Blockchain technologies enable data to be stored securely and inexpensively without recourse to a trusted authority. Blockchain technologies also promise to provide architectures for electronic health records that do not require huge government expenditure that challenge developing nations. However, Blockchain deployment, particularly with streamed data challenges existing Blockchain algorithms that take too long to place data in a block, and have no mechanism to determine whether every data point in every stream should be stored in such a secure way. This article presents an architecture that involves a Patient Agent, coordinating the insertion of continuous data streams into Blockchains to form an electronic health record.
- Description: Studies in Health Technology and Informatics
Comparison of pixel N-Grams with histogram, Haralick's features and bag-of-visual-words for texture image classification
- Authors: Kulkarni, Pradnya , Stranieri, Andrew
- Date: 2018
- Type: Text , Conference proceedings
- Relation: IEEE 3rd International Conference on Convergence in Technology: Pune, India ; April 6th-8th, 2018 p. 1-4
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- Description: Texture image classification is very useful in many domains. It has been tried using statistical, spectral and structural approaches. A novel Pixel N-grams technique has emerged for image feature extraction recently. The aim of this paper is to analyse the efficacy of Pixel N-grams technique for texture image classification in comparison with the traditional techniques namely Intensity histogram, Haralick’s features based on co-occurrence matrix and state-of-the-art Bag-of-Visual-Words (BoVW). The experiments were carried out on the benchmark UIUC texture dataset using SVM classifier. The classification performance was compared using Fscore, Recall and Precision. The classification results using Pixel N-gram were significantly better than that using Intensity histogram and Haralick features whereas, they were comparable with the BoVW approach.
Continuous patient monitoring with a patient centric agent : A block architecture
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 32700-32726
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- Description: The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications, including continuous remote patient monitoring (RPM). However, the complexity of RPM architectures, the size of data sets generated and limited power capacity of devices make RPM challenging. In this paper, we propose a tier-based End to End architecture for continuous patient monitoring that has a patient centric agent (PCA) as its center piece. The PCA manages a blockchain component to preserve privacy when data streaming from body area sensors needs to be stored securely. The PCA based architecture includes a lightweight communication protocol to enforce security of data through different segments of a continuous, real time patient monitoring architecture. The architecture includes the insertion of data into a personal blockchain to facilitate data sharing amongst healthcare professionals and integration into electronic health records while ensuring privacy is maintained. The blockchain is customized for RPM with modifications that include having the PCA select a Miner to reduce computational effort, enabling the PCA to manage multiple blockchains for the same patient, and the modification of each block with a prefix tree to minimize energy consumption and incorporate secure transaction payments. Simulation results demonstrate that security and privacy can be enhanced in RPM with the PCA based End to End architecture.
Data analytics to select markers and cut-off values for clinical scoring
- Authors: Stranieri, Andrew , Yatsko, Andrew , Venkatraman, Sitalakshmi , Jelinek, Herbert
- Date: 2018
- Type: Text , Conference proceedings
- Relation: ACSW '18: Proceedings of the Australasian Computer Science Week Multiconference; Brisbane; 29th January -2nd February 2018 p. 1-6
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- Description: Scoring systems such as the Glasgow-Coma scale used to assess consciousness AusDrisk to assess the risk of diabetes, are prevalent in clinical practice. Scoring systems typically include relevant variables with ordinal values where each value is assigned a weight. Weights for selected values are summed and compared to thresholds for health care professionals to rapidly generate a score. Scoring systems are prevalent in clinical practice because they are easy and quick to use. However, most scoring systems comprise many variables and require some time to calculate an final score. Further, expensive population-wide studies are required to validate a scoring system. In this article, we present a new approach for the generation of a scoring system. The approach uses a search procedure invoking iterative decision tree induction to identify a suite of scoring rules, each of which requires values on only two variables. Twelve scoring rules were discovered using the approach, from an Australian screening program for the assessment of Type 2 Diabetes risk. However, classifications from the 12 rules can conflict. In this paper we argue that a simple rule preference relation is sufficient for the resolution of rule conflicts.
Medical system choice: Information that affects the selection of healthcare provider in Australia?
- Authors: Sahama, Tony , Stranieri, Andrew , Butler-Henderson, Kerryn , Golden, Isaac
- Date: 2018
- Type: Text , Conference paper
- Relation: 40th Medical Informatics in Europe Conference MIE 2018 Vol. 247, p. 596
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- Description: Many complementary and alternative medical practices (CAM) are readily assessable in Australia alongside Allopathic practitioners. Although CAM practices are prevalent, little is known about how patients seek and use information when deciding which system to consult. We report some preliminary findings of a longitudinal study, designed to solicit factors that influence the Australian public when selecting from diverse medical systems. Fifty-four general public participants, willing to provide their confidential and anonymous opinion were included. The magnitudes of importance, critical in influencing factors, were screened. Results indicated a medical system was selected for its effectiveness, safety, credentials and care (p<0.001). Consultation time, convenience, cost, empowerment and rapport were less important factors (p<0.001) influencing selection of a medical system. The level of choices by participants [χ2 (1, N=54) = 53.445, p<0.001] follow similar trends found for those in conventional medical systems. This contrasts with findings in other locations, where cost and time were major contributing factors when selecting medical systems.
Significance level of a big data query by exploiting business processes and strategies
- Authors: Dinh, Loan , Karmakar, Gour , Kamruzzaman, Joarder , Stranieri, Andrew
- Date: 2018
- Type: Text , Conference paper
- Relation: 13th Joint International Baltic Conference on Databases and Information Systems Forum and Doctoral Consortium, Baltic-DB and IS Forum-DC 2018 Vol. 2158, p. 63-73
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- Description: Querying data is one of the most frequent activities in business organisations. The tasks involving queries for big data collection, extraction and analysis have never been easy, because to obtain the high quality responses, the expected outcome from these tasks need to be more accurate and highly relevant to a business organisation. The emergence of big data era has further complicated the task. The enormous volume of data from diverse sources and the variety of queries impose a big challenge on business organisations on how to extract deep insight from big data within acceptable time. Determining significance levels of queries based on their relevance to business organisations is able to deal with such challenge. To address this issue, up to our knowledge, there exists only one approach in the literature to calculate the significance level of a query. However, in this approach, only business processes are considered by manually selecting weights for core and non-core business processes. As the significance level of a query must express the importance of that query to a business organisation, it has to be calculated based on the consideration of business strategic direction, which requires the consideration of both business processes and strategies. This paper proposes an approach for the first time where the significance level of a query is determined by exploiting process contributions and strategy priorities. The results produced by our proposed approach using a business case study show the queries that are associated with more important business processes and higher priority strategies have higher significance levels. This vindicates the application of the significance level in a query to dynamically scale the semantic information use in capturing the appropriate level of deep insight and relevant information required for a business organisation. Copyright © 2018 for this paper by the papers' authors.
Supporting regional aged care nursing staff to manage residents’ behavioural and psychological symptoms of dementia, in real time, using the nurses’ behavioural assistant (NBA) : A pilot site 'end-user attitudes’ trial
- Authors: Klein, Britt , Clinnick, Lisa , Chesler, Jessica , Stranieri, Andrew , Bignold, Adam , Dazeley, Richard , McLaren, Suzanne , Lauder, Sue , Balasubramanian, Venki
- Date: 2018
- Type: Text , Conference paper
- Relation: 2017 Global Telehealth Meeting, GT 201; Adelaide, Australia; 22nd-24th November 2017; published in Telehealth for our Ageing Society (part of the Studies in Health Technology and Informatics series) Vol. 246, p. 24-28
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- Description: Background: This regional pilot site ‘end-user attitudes’ study explored nurses’ experiences and impressions of using the Nurses’ Behavioural Assistant (NBA) (a knowledge-based, interactive ehealth system) to assist them to better respond to behavioural and psychological symptoms of dementia (BPSD) and will be reported here. Methods: Focus groups were conducted, followed by a four-week pilot site ‘end-user attitudes’ trial of the NBA at a regional aged care residential facility (ACRF). Brief interviews were conducted with consenting nursing staff. Results: Focus group feedback (N = 10) required only minor cosmetic changes to the NBA prototype. Post pilot site end-user interview data (N = 10) indicated that the regional ACRF nurses were positive and enthusiastic about the NBA, however several issues were also identified. Conclusions: Overall the results supported the utility of the NBA to promote a person centred care approach to managing BPSD. Slight modifications may be required to maximise its uptake across all ACRF nursing staff.
A Decentralized Patient Agent Controlled Blockchain for Remote Patient Monitoring
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2019
- Type: Text , Conference proceedings
- Relation: 15th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2019 Vol. 2019-October, p. 207-214
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- Description: Blockchain emerging for healthcare provides a secure, decentralized and patient driven record management system. However, the storage of data generated from IoT devices in remote patient management applications requires a fast consensus mechanism. In this paper, we propose a lightweight consensus mechanism and a decentralized patient software agent to control a remote patient monitoring (RPM) system. The decentralized RPM architecture includes devices at three levels; 1) Body Area Sensor Network-medical sensors typically on or in patient's body transmitting data to a Smartphone, 2) Fog/Edge, and 3) Cloud. We propose that a Patient Agent(PA) software replicated on the Smartphone, Fog and Cloud servers processes medical data to ensure reliable, secure and private communication. Performance analysis has been conducted to demonstrate the feasibility of the proposed Blockchain leveraged, distributed Patient Agent controlled remote patient monitoring system. © 2019 IEEE.
- Description: E1
A lightweight blockchain based framework for underwater ioT
- Authors: Uddin, Md , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2019
- Type: Text , Journal article
- Relation: Electronics (Switzerland) Vol. 8, no. 12 (2019), p.
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- Description: The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications, including underwater monitoring, where sensors are located at various depths, and data must be transmitted to surface base stations for storage and processing. Ensuring that data transmitted across hierarchical sensor networks are kept secure and private without high computational cost remains a challenge. In this paper, we propose a multilevel sensor monitoring architecture. Our proposal includes a layer-based architecture consisting of Fog and Cloud elements to process and store and process the Internet of Underwater Things (IoUT) data securely with customized Blockchain technology. The secure routing of IoUT data through the hierarchical topology ensures the legitimacy of data sources. A security and performance analysis was performed to show that the architecture can collect data from IoUT devices in the monitoring region efficiently and securely. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
An efficient selective miner consensus protocol in blockchain oriented iot smart monitoring
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 2019 IEEE International Conference on Industrial Technology, ICIT 2019; Melbourne; Australia; 13th-15th February 2019 Vol. 2019-February, p. 1135-1142
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- Description: Blockchains have been widely used in Internet of Things(IoT) applications including smart cities, smart home and smart governance to provide high levels of security and privacy. In this article, we advance a Blockchain based decentralized architecture for the storage of IoT data produced from smart home/cities. The architecture includes a secure communication protocol using a sign-encryption technique between power constrained IoT devices and a Gateway. The sign encryption also preserves privacy. We propose that a Software Agent executing on the Gateway selects a Miner node using performance parameters of Miners. Simulations demonstrate that the recommended Miner selection outperforms Proof of Works selection used in Bitcoin and Random Miner Selection.
- Description: Proceedings of the IEEE International Conference on Industrial Technology
Are ERP simulation games assisting students to be job-ready? An Australian universities’ perspective
- Authors: Faisal, Nadia , Chadhar, Mehmood , Goriss-Hunter, Anitra , Stranieri, Andrew
- Date: 2019
- Type: Text , Conference paper
- Relation: 30th Australiasian Conference on Information Systems (ACIS), 9-11 December 2019, Perth, Australia
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- Description: Deep and rapid changes in digital enterprise technology exceed the ability of traditional teaching methods to prepare students for challenges encountered in modern enterprises. Researchers proposed different pedagogical approaches to teach ERP (Enterprise Resource Planning) concepts such as ERPsim games to enhance students’ learning and job-readiness. Although the ERPsim studies verified the role of these games in enhancing students’ learning, whether these games contribute to student’s job readiness still needs to be explored. Using the mixed-method approach, this research-in-progress is designed to fill this gap by investigating the role of ERPsim game in increasing skills, learning levels, and job-readiness among university students in Australia. The findings from this study can contribute to the improvement of ERP pedagogical techniques. In addition, this research-in-progress will provide a concrete mapping to align learning outcomes/skills with ICT industry competencies standards as defined in SFIA (Skills framework for Information Age) and AQF (Australian Qualifications Framework).
Blockchain leveraged task migration in body area sensor networks
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 25th Asia-Pacific Conference on Communications, APCC 2019 p. 177-184
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- Description: Blockchain technologies emerging for healthcare support secure health data sharing with greater interoperability among different heterogeneous systems. However, the collection and storage of data generated from Body Area Sensor Net-works(BASN) for migration to high processing power computing services requires an efficient BASN architecture. We present a decentralized BASN architecture that involves devices at three levels; 1) Body Area Sensor Network-medical sensors typically on or in patient's body transmitting data to a Smartphone, 2) Fog/Edge, and 3) Cloud. We propose that a Patient Agent(PA) replicated on the Smartphone, Fog and Cloud servers processes medical data and execute a task offloading algorithm by leveraging a Blockchain. Performance analysis is conducted to demonstrate the feasibility of the proposed Blockchain leveraged, distributed Patient Agent controlled BASN. © 2019 IEEE.
- Description: E1
Comparing Pixel N-grams and bag of visual word features for the classification of diabetic retinopathy
- Authors: Kulkarni, Pradnya , Stranieri, Andrew , Jelinek, Herbert
- Date: 2019
- Type: Text , Conference proceedings
- Relation: ACSW 2019: Australasian Computer Science Week 2019;Sydney NSW Australia; January 29 - 31, 2019; published in Proceedings of the Australasian Computer Science Week Multiconference p. 1-7
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- Description: The extraction of Bag of Visual Words (BoVW) features from retinal images for automated classification has been shown to be effective but computationally expensive. Histogram and co-variance matrix features do not generally result in models that have the same predictive accuracy as BoVW and are still computationally expensive. The discovery of features that result in accurate image classification on computationally constrained devices such as smartphones would enable new and promising applications for image classification. For example, smartphone retinal cameras can conceivably make diabetic retinopathy widely available and potentially reduce undiagnosed retinopathy if it could be achieved with computationally simple classification algorithms. A novel image feature extraction technique inspired by N-grams in text mining, called 'Pixel N-grams' is described that can serve this purpose. Results on mammogram and texture classification have shown high accuracy despite the reduced computational complexity. However retinal scan classification results using Pixel N-grams lag behind BoVW approaches. An explanation for the relative poor performance of Pixel N-grams with diabetic retinopathy that draws on concepts associated with the No Free Lunch theorem are presented.
Criteria to measure social media value in health care settings : narrative literature review
- Authors: Ukoha, Chukwuma , Stranieri, Andrew
- Date: 2019
- Type: Text , Journal article , Review
- Relation: Journal of Medical Internet Research Vol. 21, no. 12 (2019), p.
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- Description: Background: With the growing use of social media in health care settings, there is a need to measure outcomes resulting from its use to ensure continuous performance improvement. Despite the need for measurement, a unified approach for measuring the value of social media used in health care remains elusive. Objective: This study aimed to elucidate how the value of social media in health care settings can be ascertained and to taxonomically identify steps and techniques in social media measurement from a review of relevant literature. Methods: A total of 65 relevant articles drawn from 341 articles on the subject of measuring social media in health care settings were qualitatively analyzed and synthesized. The articles were selected from the literature from diverse disciplines including business, information systems, medical informatics, and medicine. Results: The review of the literature showed different levels and focus of analysis when measuring the value of social media in health care settings. It equally showed that there are various metrics for measurement, levels of measurement, approaches to measurement, and scales of measurement. Each may be relevant, depending on the use case of social media in health care. Conclusions: A comprehensive yardstick is required to simplify the measurement of outcomes resulting from the use of social media in health care. At the moment, there is neither a consensus on what indicators to measure nor on how to measure them. We hope that this review is used as a starting point to create a comprehensive measurement criterion for social media used in health care. © 2019 Chukwuma Ukoha, Andrew Stranieri.
Integrating biological heuristics and gene expression data for gene regulatory network inference
- Authors: Zarnegar, Armita , Jelinek, Herbert , Vamplew, Peter , Stranieri, Andrew
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 2019 Australasian Computer Science Week Multiconference, ACSW 2019; Sydney, Australia; 29th-31st January 2019 p. 1-10
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- Description: Gene Regulatory Networks (GRNs) offer enhanced insight into the biological functions and biochemical pathways of cells associated with gene regulatory mechanisms. However, obtaining accurate GRNs that explain gene expressions and functional associations remains a difficult task. Only a few studies have incorporated heuristics into a GRN discovery process. Doing so has the potential to improve accuracy and reduce the search space and computational time. A technique for GRN discovery that integrates heuristic information into the discovery process is advanced. The approach incorporates three elements: 1) a novel 2D visualized coexpression function that measures the association between genes; 2) a post-processing step that improves detection of up, down and self-regulation and 3) the application of heuristics to generate a Hub network as the backbone of the GRN. Using available microarray and next generation sequencing data from Escherichia coli, six synthetic benchmark GRN datasets were generated with the neighborhood addition and cluster addition methods available in SynTReN. Results of the novel 2D-visualization co-expression function were compared with results obtained using Pearson's correlation and mutual information. The performance of the biological genetics-based heuristics consisting of the 2D-Visualized Co-expression function, post-processing and Hub network was then evaluated by comparing the performance to the GRNs obtained by ARACNe and CLR. The 2D-Visualized Co-expression function significantly improved gene-gene association matching compared to Pearson's correlation coefficient (t = 3.46, df = 5, p = 0.02) and Mutual Information (t = 4.42, df = 5, p = 0.007). The heuristics model gave a 60% improvement against ARACNe (p = 0.02) and CLR (p = 0.019). Analysis of Escherichia coli data suggests that the GRN discovery technique proposed is capable of identifying significant transcriptional regulatory interactions and the corresponding regulatory networks.
Patient-empowered electronic health records
- Authors: Sahama, Tony , Stranieri, Andrew , Butler-Henderson, Kerryn
- Date: 2019
- Type: Text , Conference proceedings
- Relation: MEDINFO 2019: Health and Wellbeing e-Networks for All Vol. 264, p. 1765
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- Description: Electronic Health Records (EHRs) constitute evidence of online health information management. Critical healthcare information technology (HIT) infrastructure facilitates health information exchange of 'modern' health systems. The growth and implementation of EHRs are progressing in many countries while the adoption rate is lagging and lacking momentum amidst privacy and security concerns. This paper uses an interrupted time series (ITS) analysis of OECD data related to EHRs from many countries to make predictions about EHR adoption. The ITS model can be used to explore the impact of various HIT on adoption. Assumptions about the impact of Information Accountability are entered into the model to generate projections if information accountability technologies are developed. In this way, the OECD data and ITS analysis can be used to perform simulations for improving EHR adoption.
Personalised measures of obesity using waist to height ratios from an Australian health screening program
- Authors: Jelinek, Herbert , Stranieri, Andrew , Yatsko, Anderw , Venkatraman, Sitalakshmi
- Date: 2019
- Type: Text , Journal article
- Relation: Digital Health Vol. 5, no. (2019), p. 1-8
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- Description: Objectives The aim of the current study is to generate waist circumference to height ratio cut-off values for obesity categories from a model of the relationship between body mass index and waist circumference to height ratio. We compare the waist circumference to height ratio discovered in this way with cut-off values currently prevalent in practice that were originally derived using pragmatic criteria. Method Personalized data including age, gender, height, weight, waist circumference and presence of diabetes, hypertension and cardiovascular disease for 847 participants over eight years were assembled from participants attending a rural Australian health review clinic (DiabHealth). Obesity was classified based on the conventional body mass index measure (weight/height(2)) and compared to the waist circumference to height ratio. Correlations between the measures were evaluated on the screening data, and independently on data from the National Health and Nutrition Examination Survey that included age categories. Results This article recommends waist circumference to height ratio cut-off values based on an Australian rural sample and verified using the National Health and Nutrition Examination Survey database that facilitates the classification of obesity in clinical practice. Gender independent cut-off values are provided for waist circumference to height ratio that identify healthy (waist circumference to height ratio >= 0.45), overweight (0.53) and the three obese (0.60, 0.68, 0.75) categories verified on the National Health and Nutrition Examination Survey dataset. A strong linearity between the waist circumference to height ratio and the body mass index measure is demonstrated. Conclusion The recommended waist circumference to height ratio cut-off values provided a useful index for assessing stages of obesity and risk of chronic disease for improved healthcare in clinical practice.
Semi-invasive system for detecting and monitoring dementia patients
- Authors: Yamsanwar, Yash , Patankar, Amol , Kulkarni, Siddhivinayak , Stratton, David , Stranieri, Andrew
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 5th IEEE International Conference for Convergence in Technolog, I2CT 2019
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- Description: Dementia is one of the most prevalent conditions faced by the elderly caused by specific brain cell damage. Various effects of dementia include a loss of memory, reduction in problem solving ability, analytical skills, and decision making capability. Few systems have been developed for the early detection of dementia. Existing systems depend largely on hardware e.g. sensors, gateways. Factors like maintainability and sustainability compromise the efficiency of such systems. This paper presents a novel approach towards the early detection of dementia and aims at eliminating some of the challenges posed by these systems. It also provides a comparati ve study of the cognitive abilities of healthy old-age people and those afflicted by dementia. © 2019 IEEE.
- Description: E1
Blockchain leveraged decentralized IoT eHealth framework
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2020
- Type: Text , Journal article
- Relation: Internet of Things Vol. 9, no. March 2020 p. 100159
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- Description: Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentral- ized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, care- ful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer –Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer –Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR pro- cessing layer –Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reli- able, secure and private communication. The PA executes a lightweight Blockchain consen- sus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure pa- tient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the pro- cessing and storage of RPM data.