Mobile Acquisition and Monitoring System for Improved Diabetes Management Using Emergent Wireless and Web Technologies

2014 14th UK Workshop on Computational Intelligence (UKCI)

Al-Nuaimy

et al. 2014

Self Cite

Pattern recognition has been an effective approach to identifying glycaemic patterns within self-monitored blood glucose (BG) data in diabetes mellitus patients. This paper presents a new BG pattern mining algorithm for more targeted therapeutic decision support in diabetes self-management. Based on patients' BG readings which are collected via a handheld device and logged on a web-based health portal, the existing BG patterns are extracted in real-time and fed back to the patient along with appropriate therapeutic recommendations, educational modules and health care advice. The identified patterns help patients improve their blood glucose management and education about diabetes and its complications. A functional prototype of the proposed system is developed and its end-to-end functionality is successfully demonstrated. A pilot clinical study demonstrated positive user acceptability and interest in its decision support attributes for diabetes self-management, making this a promising avenue for further research.

Section: Resultsmentioning

confidence: 99%

“…The proposed algorithm is integrated into an existing Web-based health portal developed by the authors [18], [19] for diabetes selfmanagement support. The remainder of this paper is organised as follows: Section II provides an architecture and operation overview for the eHealth system under study.…”

Section: Introductionmentioning

confidence: 99%

Blood-glucose pattern mining algorithm for decision support in diabetes management

2014 14th UK Workshop on Computational Intelligence (UKCI)

Al-Nuaimy

et al. 2014

Self Cite

“…This interaction, which is performed by a humanoid robot on behalf and under control of the health care team, focuses on two important pillars; patients' empowerment and behavioural change support. Applications of this module are distributed between an existing health portal reported in [17] - [19] and a local patient's robot. The remote server applications are linked to the robot through a secured HTTP protocol, as shown in Fig.…”

Section: System Overviewmentioning

confidence: 99%

A Human-Robot Sub-dialogues Structure Using XML Document Object Model

2013 Sixth International Conference on Developments in eSystems Engineering

Philip

2013

Self Cite

Improving remote interactivity between patients and their health carers is a key requirement for emerging eHealth systems. This paper presents a new human-robot sub-dialogues structure based on the XML Document Object Model (DOM). The dialogue structure which aims at improving patient-carer interactivity enables both the patients and their carers to control behavior of humanoid robot locally through verbal instructions or tactile sensors as well as remotely through textual Web-based instructions. The textual instructions which are prepared in the form of interactive dialogues are converted to XML DOM and sent to the in-home robot via the Internet. The robot will then verbalize these dialogues and present them to the patient along with appropriate gesture/posture attributes. The XML DOM standard is adopted in this study to facilitate the structure and navigation flexibility between the internal nodes of the dialogue. Numerous human-robot interactions based on the proposed dialogue structure have been designed, built and successfully performed by the robot using both local and remote instructions. These dialogues are tailored to support diabetes self-management in children. The prototype evaluation results and observations showed (i) a seamless and accurate data transfer between the robot and a remote Web-based health portal, and (ii) a high level of navigation flexibility between different nodes of the experimented dialogues.

“…Nowadays, we are living the accelerated outburst of smartphone and portable technology within the context of e-health platforms and related applications, including mobile health and electronic medical records (Al-Taee and Abood, 2012;Al-Taee et al, 2011). Although computer integration into health care has been a fact in the past couple of decades, we believe that there are limitations which can be bypassed by smartphone applications.…”

Section: Introductionmentioning

confidence: 99%

Mobile‐based interpreter of arterial blood gases using knowledge‐based expert system

Zayed

Int J of Pervasive Comp & Comm

et al. 2013

Self Cite

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -An arterial blood gas (ABG) interpretation remains indispensable tool to assess and monitor critically ill patients in the intensive care unit or other critical care settings. This paper proposes a mobile-based interpreter for ABG tests with the aim of providing accurate diagnosis in face of multiple acid-base and oxygenation disorders. The paper aims to discuss these issues. Design/methodology/approach -A rule-based expert system is designed and implemented using interpretation knowledge gathered from specialist physicians and peer-reviewed medical literature. The gathered knowledge of ABG tests are organized into premise-explanation pairs to deliver reliable evaluation with the appropriate differential in a timely manner. Findings -Performance of the developed interpreter prototype was assessed using a dataset of 74 ABG tests gathered from medical literature and clinical practice. The obtained results demonstrated that the identified acid-base and oxygenation disorders and their differential diagnoses are accurately correlated with those assessed manually by consultant specialist physicians. Research limitations/implications -This application is foreseen to be an everyday tool for clinicians at various levels; however, further studies are needed to evaluate its eventual impact on patients' outcomes. Originality/value -The contribution of this paper is the development of a new ABG interpreter which combines both the acid-base and oxygenation disorders in a single application. Unlike existing ABG interpreters, it is comprehensive and capable of accurately identifying all kinds of acid-base disorders and their combinations. In addition, it utilizes urine electrolytes which are useful tools in the differential diagnosis of normal anion gap metabolic acidosis and metabolic alkalosis. The interpretation algorithm is also designed to be flexible for some clinical settings which lack some input test data.