A review of wearable sensors based monitoring with daily physical activity to manage type 2 diabetes

Globally, the aging and the lifestyle lead to rabidly increment of the number of type two diabetes (T2D) patients. Critically, T2D considers as one of the most challenging healthcare issue. Importantly, physical activity (PA) plays a vital role of improving glycemic control T2D. However, daily monitoring of T2D using wearable devices/ sensors have a crucial role to monitor glucose levels in the blood. Nowadays, daily physical activity (PA) and exercises have been used to manage T2D. The main contribution of the proposed study is to review the literature about managing and monitoring T2D with daily PA through wearable devices and sensors. Finally, challenges and future trends are also highlighted

Smartphone-based personalized blood glucose prediction

AbstractEffective blood glucose control is essential for patients with diabetes. However, individual patients may not be able to monitor their blood glucose level regularly because of all manner of real-life interference. In this paper, we propose a personalized diabetes prediction mechanism that leverages smartphone-collected patient data and population data to drive personalized prediction. Unlike existing predictive models, this model utilizes pooled population data and captures patient similarities, and eventually produces a personalized blood glucose prediction for an individual. We have implemented the proposed model as a mobile application and have performed extensive experiments to evaluate its performance. The experimental results demonstrate that the proposed prediction mechanism can improve the prediction accuracy and remedy the problem of sparse data in the existing approaches

DRUG-RELATED PROBLEMS IN HOSPITALIZED GERIATRIC PATIENTS WITH DIABETES MELLITUS

Objective: This study aimed at analyzing drug-related problems (DRPs) in hospitalized geriatric patients with diabetes mellitus.Methods: We prospectively collected data of 26 hospitalized geriatric patients at the Gatot Soebroto Army Hospital (age, >60 year) who underwentinpatient treatment for at least 1 month between February and April 2015. Readable data were obtained from prescriptions, medical records, andindex card/nurses records. We obtained data on 299 drug treatments for 26 patients and identified 166 DRPs. These were analyzed based on thePharmaceutical Care Network Europe Version 6.2.Results: The percentage of treatment effectiveness (50.6%) and adverse drug reactions (49.4%) was predominantly due to an inappropriate drug–drug or drug–food combination, including the incidence of drug interactions (20.4%)

Newer Modalities in the Treatment of Type 2 Diabetes Mellitus: Focus on Technology

This chapter will focus on the technological advances for individuals with Type 2 diabetes mellitus and their effect on treatment, control of blood glucoses and possible improvement in lifestyle and decreasing complications. This is a general overview of technological improvements and not an outline for specific patient care. Various technologies will be discussed and the outlook for future improvements outlined

2016 European Society of Hypertension guidelines for the management of high blood pressure in children and adolescents

Increasing prevalence of hypertension (HTN) in children and adolescents has become a significant public health issue driving a considerable amount of research. Aspects discussed in this document include advances in the definition of HTN in 16 year or older, clinical significance of isolated systolic HTN in youth, the importance of out of office and central blood pressure measurement, new risk factors for HTN, methods to assess vascular phenotypes, clustering of cardiovascular risk factors and treatment strategies among others. The recommendations of the present document synthesize a considerable amount of scientific data and clinical experience and represent the best clinical wisdom upon which physicians, nurses and families should base their decisions. In addition, as they call attention to the burden of HTN in children and adolescents, and its contribution to the current epidemic of cardiovascular disease, these guidelines should encourage public policy makers to develop a global effort to improve identification and treatment of high blood pressure among children and adolescents

Intelligent Remote Monitoring and Management system for Type1 Diabetes

The work presented in this thesis focuses on developing a telemedicine system for better management of type1 diabetes in children and teenagers. The research and development of the system is motivated by the inadequate communication in the current system of management of the disease, which results in non-compliance of patients following the regimen. This non-compliance generally results in uncontrolled blood glucose levels, which can result in hypoglycaemia, hyperglycaemia and later life health complications. This further results in an increase in health care costs. In this context, the thesis presents a novel end-to-end, low cost telemedicine system, WithCare+, developed in close collaboration between the University of Sheffield (Electronics & Electrical Engineering) and Sheffield Children’s Hospital. The system was developed to address the challenges of implementing modern telemedicine in type 1 diabetic care with particular relevance to National Health Service children’s clinics in the United Kingdom, by adopting a holistic care driven approach (involving all stakeholders) based on specific key enabler technologies such as low cost and reconfigurable design. However, one of the major issues with current telemedicine system is non-compliance of the patients due to invasive procedure of the glucose measurement which could be clearly addressed by non-invasive method of glucose measurement. Hence, the thesis also makes a contribution towards non-invasive glucose measurement using Near Infrared spectroscopy in terms of addressing the calibration challenge; two methods are proposed to improve the calibration of the Near Infrared instrument. The first method combines locally weighted regression and partial least square regression and the second method combines digital band pass filtering with support vector regression. The efficacy of the proposed methods is validated in experiments carried out in a non-controlled environment and the results obtained demonstrate that the proposed methods improved the performance of the calibration model in comparison to traditional calibration techniques such as Principal Component Regression and Partial Least Squares regression