Mobile health (m-Health) for diabetes management

Diabetes is a major health challenge with a global impact regardless of age, country or economic condition. The increased prevalence of diabetes is reaching alarming levels. The necessity and urgency to find innovative care delivery solutions is becoming more important, particularly in the digital age. It is expected in the near future that more people with diabetes, especially the younger generations will be empowered by their smartphones and relevant mobile health (m-Health) innovations, to take more responsibility of their condition. Clinicians and healthcare providers are increasingly likely to assume the role of ‘navigators’ and ‘advisors’ rather than simply the medical gatekeeper for their patients. In this article, we describe the general architecture of current m-Health systems and applications for diabetes management. We also discuss the clinical evidence for impact from these important and innovative approaches to diabetes self-care and management and likely future trends in their usage. The latest statistics indicate that there are more than 1200 diabetes smartphone ‘apps’ and this area is growing exponentially in terms of ideas, technologies, devices and the associated industry. M-Health for diabetes care is now a major business stream for the medical device, mobile phone and IT telecommunication industries with high expectations arising from the potential benefits to be gained by both patients and healthcare providers. However, this potential has not yet been fully developed on the clinical side. This may be due to many factors including the reluctance of clinicians to engage with these technologies due to the lack of clinical evidence for their efficacy, poor adherence of people with diabetes to long-term use of these apps and the reluctance of healthcare funders to reimburse mobile diabetes

Microarray image enhancement by denoising using stationary wavelet transform

Microarray imaging is considered an important tool for large scale analysis of gene expression. The accuracy of the gene expression depends on the experiment itself and further image processing. It's well known that the noises introduced during the experiment will greatly affect the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Traditionally, statistical methods are used to estimate the noises while the microarray images are being processed. In this paper, we present a new approach to deal with the noise inherent in the microarray image processing procedure. That is, to denoise the image noises before further image processing using stationary wavelet transform (SWT). The time invariant characteristic of SWT is particularly useful in image denoising. The testing result on sample microarray images has shown an enhanced image quality. The results also show that it has a superior performance than conventional discrete wavelet transform and widely used adaptive Wiener filter in this procedure

Mobile Health (m-Health) in Retrospect: The Known Unknowns

For nearly two decades, mobile health or (m-Health) was hailed as the most innovative and enabling area for the digital transformation of healthcare globally. However, this profound vision became a fleeting view since the inception and domination of smart phones, and the reorientation of the concept towards the exclusivity of global smart phone application markets and services. The global consumerization of m-Health in numerous disciplines of healthcare, fitness and wellness areas is unprecedented. However, this divergence between ‘mobile health capitalism’ and the ‘science of mobile health’ led to the creation of the ‘m-Health schism’. This schism was sustained by the continued domination of the former on the expense of the latter. This also led to increased global m-Health inequality and divide between the much-perceived health and patient benefits and the markets of m-Health. This divergence was more evident in low and middle income (LMIC) countries compared to the developed world. This powerful yet misguided evolution of the m-Health was driven essentially by complex factors. These are presented in this paper as the ‘known unknowns’ or ‘the obvious but sanctioned facts’ of m-Health. These issues had surreptitiously contributed to this reorientation and the widening schism of m-Health. The collateral damage of this process was the increased shift towards understanding ‘digital health’ as a conjecture term associated with mobile health. However, to date, no clear or scientific views are discussed or analyzed on the actual differences and correlation aspects between digital and mobile health. This particular ‘known unknown’ is presented in detail in order to provide a rapprochement framework of this correlation and valid presentations between the two areas. The framework correlates digital health with the other standard ICT for the healthcare domains of telemedicine, telehealth and e-health. These are also increasingly used in conjunction with digital health, without clear distinctions between these terms and digital health. These critical issues have become timelier and more important to discuss and present, particularly after the world has been caught off guard by the COVID-19 pandemic. The much hyped and the profiteering digital health solutions developed in response of this pandemic provided a modest impact, and the benefits were mostly inadequate in mitigating the massive health, human, and economic impact of this pandemic. This largely commercial reorientation of mobile health was unable not only to predict the severity of the pandemic, but also unable to provide adequate digital tools or effective pre-emptive digital epidemiological shielding and guarding mechanisms against this devastating pandemic. There are many lessons to be learnt from the COVID-19 pandemic from the mobile and digital health perspectives, and lessons must be learnt from the past and to address the critical aspects discussed in this paper for better understanding of mobile health and effective tackling of future global healthcare challenges

m-Health: fundamentals and applications

Addresses recent advances from both the clinical and technological perspectives to provide a comprehensive presentation of m-Health. This book introduces the concept of m-Health, first coined by Robert S. H. Istepanian in 2003. The evolution of m-Health since then—how it was transformed from an academic concept to a global healthcare technology phenomenon—is discussed. Afterwards the authors describe in detail the basics of the three enabling scientific technological elements of m-Health (sensors, computing, and communications), and how each of these key ingredients has evolved and matured over the last decade. The book concludes with detailed discussion of the future of m-Health and presents future directions to potentially shape and transform healthcare services in the coming decades