Ala Sungoor

Evaluation of a mobile phone telemonitoring system for glycaemic control in patients with diabetes.

We conducted a randomized controlled trial using mobile health technology in an ethnically diverse sample of 137 patients with complicated diabetes. Patients in the intervention group (n = 72) were trained to measure their blood glucose with a sensor which transmitted the readings to a mobile phone via a Bluetooth wireless link. Clinicians were then able to examine and respond to the readings which were viewed with a web-based application. Patients in the control arm of the study (n = 65) did not transmit their readings and received care with their usual doctor in the outpatient and/or primary care setting. The mean follow-up period was 9 months in each group. The default rate was higher in the patients in the intervention arm due to technical problems. In an intention-to-treat analysis there were no differences in HbA1c between the intervention and control groups. In a sub-group analysis of the patients who completed the study, the telemonitoring group had a lower HbA1c than those in the control group: 7.76% and 8.40%, respectively (P = 0.06).

The potential of Internet of m-health Things “m-IoT” for non-invasive glucose level sensing

An amalgamated concept of Internet of m-health Things (m-IoT) has been introduced recently and defined as a new concept that matches the functionalities of m-health and IoT for a new and innovative future (4G health) applications. It is well know that diabetes is a major chronic disease problem worldwide with major economic and social impact. To-date there have not been any studies that address the potential of m-IoT for non-invasive glucose level sensing with advanced opto-physiological assessment technique and diabetes management. In this paper we address the potential benefits of using m-IoT in non-invasive glucose level sensing and the potential m-IoT based architecture for diabetes management. We expect to achieve intelligent identification and management in a heterogeneous connectivity environment from the mobile healthcare perspective. Furthermore this technology will enable new communication connectivity routes between mobile patients and care services through innovative IP based networking architectures.

Mobile telemonitoring for achieving tighter targets of blood pressure control in patients with complicated diabetes: a pilot study

BACKGROUND Hypertension is a major risk factor for the long-term complications of diabetes. Mobile, self-measurement of blood pressure is emerging as a method to manage blood pressure in general, but its impact in patients with diabetes is unclear. METHODS We randomized 137 patients with diabetes and hypertension to either mobile telemonitoring (n = 72) or usual care (n = 65). Clinic blood pressure was recorded at baseline and after 6 months. Patients in the intervention arm transmitted weekly blood pressure readings wirelessly, using adapted sensors via mobile phones to a central server. Clinicians received the data in real-time and using a web-based application provided management advice to the patient and their physicians. RESULTS Systolic blood pressure fell significantly in the patients in the intervention group (mean [95% confidence interval], -6.5 [-0.8 to -12.2] mm Hg; P = 0.027) and remained unchanged in the control group (2.1 [9.3 to -5.0] mm Hg; P = 0.57). Patients within the intervention arm of African origin seemed to benefit more from the intervention. In addition, those who achieved a systolic blood pressure of <120 mm Hg had lower average blood sugars than those with higher readings (7.8 [SD 1.6] vs. 8.9 [SD 2.2] mmol/L; P = 0.02). CONCLUSIONS In patients with diabetes, mobile telemonitoring has potential for delivering intensified care to improve blood pressure control, and its use may be associated with reduced exposure to hyperglycemia.

UK and Canadian perspectives of the effectiveness of mobile diabetes management systems

The use of mobile technologies for self-monitoring of blood glucose and blood pressure for diabetes patients is becoming increasingly popular worldwide. This is propelled by the proliferation of the wider usage of mobile phones and other wireless technologies and computing platforms in the healthcare sector. Such technologies can play a pivotal role in chronic disease management and patient self-care. There have been several clinical trials in recent years on mobile diabetes management in UK and Canada. However, no studies to date have addressed and correlated the technological and clinical outcomes concerning the use of mobile chronic disease management systems for diabetes from the UK and Canadian perspectives. In this paper we address some of these correlative issues based on similar clinical trials on mobile type-2 diabetes management systems deployed in these two countries. In particular, the outcomes of these trials supported the use of telemonitoring for effective blood pressure control, but telemonitoring was less effective at managing blood glucose control. Some of the clinical results and challenges are presented together with future work and suggestions that aim to validate a generic platform for mobile diabetes management.

Technical and compliance considerations for mobile health self-monitoring of glucose and blood pressure for patients with diabetes

Self-monitoring of blood glucose is an integral part of diabetes care which may be extended to other biometrics. Cellular and short range communication technologies will be important for the routine usage of these systems. However, the issues of follow-up and patient compliance with these emerging systems have not been yet studied evaluated but could be critical to the adoption of these technologies. We evaluated the impact of mobile telemonitoring on the intensification of care on blood pressure control and exposure to hyperglycaemia in patients with diabetes. We randomised 137 patients with diabetes to either mobile telemonitoring (n = 3D72) or usual care patients (n = 3D65) for 9 months. In this paper we present some of the clinical results with focus on blood pressure control hypertension and highlight some of the technical and compliance issues that were encountered.

Web-of-Things inspired e-Health platform for integrated diabetes care management

Integration of physical objects (or things) within the Web has become a goal for current and future health care systems. In this paper, we propose a new e-Health platform driven by the needs of integrated diabetes care management. Architecture of this platform that is designed to be consistent with the concepts of Web-of-Things (WoT) comprises a physical sensors layer linked to a health Web-portal layer via an existing network infrastructure. The physical layer incorporates wireless nodes; each of which comprises a set of medical sensors linked wirelessly to a humanoid robot. Unlike existing e-Health systems, the proposed system is designed to support self-management of Type 1 diabetes mellitus (TIDM) not only through remote data collection and monitoring of patients data, but also through offering a support platform for real-time decisions and long-term social and behavioral change. These support services are delivered to the patients over a distance through daily patient-robot interactions that are either automatically generated be the system or assigned by specialist physicians. A prototype e-health platform which incorporates all these healthcare attributes is designed, implemented, and its end-to-end functionality is tested successfully with the aid of NHS collaborators.

Comparative Analysis of Genomic Signal Processing for Microarray Data Clustering

Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

An intelligent mobile diabetes management and educational system for Saudi Arabia: System architecture

This paper presents an intelligent mobile diabetes management and educational system for patients in Saudi Arabia with type 2 diabetes (SAED). The SAED system consists of two main components: (1) the SAED mobile patient/healthcare provider component and (2) the SAED intelligent diabetes management component. The SAED mobile patient/healthcare provider component includes two units (i) the patients unit and (ii) the specialist diabetic unit, which communicate for data exchange. The SAED intelligent diabetes management component includes (i) a database module; (ii) an intelligent decision support module based on fuzzy logic concepts; (iii) a SAED SMS reminder module and (iv) a diabetes educational module. In general, SAED is a system capable of storing clinical data on diabetes management, such as daily blood glucose and blood pressure measurements and hypoglycaemia events. These stored records and the incorporated decision support system will allow the clinician to monitor patients remotely. Furthermore, the decision support system will provide the physician with recommendations for each patient using fuzzy logic theory.

A Study on Perception of Managing Diabetes Mellitus through Social Networking in the Kingdom of Saudi Arabia

The Kingdom of Saudi Arabia (KSA) has the seventh highest prevalence of diabetes in the world with estimates of 20% of the populations diagnosed with diabetes. Furthermore, there is a lack of good educational and management programs of diabetes in the kingdom. In parallel to this major health problem, there is an increasing trend of smart mobile phone usage and access to social networking in the Kingdom, especially in the younger population. In this paper, we conducted a preliminary study on the perception of managing diabetes mellitus through mobile technologies and social networking in the kingdom of Saudi Arabia. A mixed method design with interviews and a survey were used to gather data. Most of the participants were younger users aged between (10-30 years). The key outcomes of this study indicate the high percentage acceptance of using smart phone technologies and social networking within the participation.

The potential of m-health systems for diabetes management in post conflict regions a case study from Iraq.

The recent developments of m-health technologies particularly in the developing world are increasing sharply due to the importance and accelerated adoption of these technologies in the developing countries. However, there are few if any studies on the effectiveness of mobile health in post conflict regions especially in the Middle East region. In this paper we describe the design, implementation and clinical outcomes of a feasibility study on mobile diabetes management in Basra, Southern Iraq as an exemplar for the effectiveness of mobile health technologies for improved healthcare delivery in similar post conflict regions. The key clinical outcome of this study indicated the lowering of HbA1C levels in the mobile health group indicating the potential of deploying such technologies in these regions where health resources are limited and challenging.