Critical Retrospection of Performance of Emerging Mobile Technologies in Health Data Management

Abstract

The recent advancement in mobile technologies has led to opening a new paradigm in the field of medical healthcare systems. The development of WBAN sensors, wearable devices, and 5G/6G wireless technology has made real-time monitoring and telecare of the patient feasible. The complex framework to secure sensitive data of the patient and healthcare professionals is critical. The fast computation of health data generated is crucial for disease prediction and trauma-related services; the security of data and financial transactions is also a major concern. Various models, algorithms, and frameworks have been developed to tame critical issues related to healthcare services. The efficiency of these frameworks and models depends on energy and time consumption. Thus, the review of recent emerging technologies in respect of energy and time consumption is required. This paper reviews the developments in recent mobile technologies, their application, and the comparative analysis of their performance parameters to explicitly understand the utility, capacity, and limitations. This will help to understand the shortcomings of the recent technologies for the development of better frameworks with higher performance capabilities as well as higher quality of services.

[Retracted] Monitoring Cardiovascular Problems in Heart Patients Using Machine Learning

“…Some cardiac arrhythmias, on the other hand, can be painful and even fatal. A person's heart might well be rapid or sluggish for a myriad of purposes [ 13 , 14 ]. For example, the pulse may rise during exercise and fall during sleep.…”

A latent profile analysis of residents' knowledge, attitude, and practice toward common chronic diseases among ethnic minority area in China

“…First, there is a clear knowledge-practice gap in the I.T. group, and applying the behavioral economics framework to the field of health education can reveal potential barriers to translating knowledge into practice and entry points for interventions by clinicians and public health professionals ( 28 ); furthermore, the development of mobile health technologies, especially the availability of wearable devices and 5G/6G wireless technologies, has made real-time monitoring and telehealth possible ( 29 ), facilitating the implementation of behavioral interventions. Second, we argue that the same ethnic minorities still have different health needs; for example, the B.P.…”

MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data

“…Missing evaluations can lead to technical roadblocks, since systems that are difficult to use for domain experts, such as healthcare workers, discourage them from using them [ 24 ]. Ultimately, this hinders the translation of developed systems to domain experts or end-users, for example in the domains of sports and health [ 11 , 25 , 26 ].…”