The increased development and use of ubiquitous digital services reinforce the trend where health-related data is generated everywhere. Data usage in different areas introduces different terms for the same or similar concepts. This adds to the confusion of what these terms represent. We aim to provide an overview of concepts and terms used in connection with digital twins and in a healthcare context.

Accelerometers objectively monitor physical activity, and ongoing research suggests they can also detect patterns of body movement. However, different types of signal (uniaxial, captured by older studies, vs. the newer triaxial) and or/device (validated Actigraph used by older studies, vs. others) may lead to incomparability of results from different time periods. Standardization is desirable. We ...

A unified active power control scheme is devised for the grid-integrated permanent magnet synchronous generator-based wind power system (WPS) to follow the Indian electricity grid code requirements. The objective of this paper is to propose control schemes to ensure the continuous integration of WPS into the grid even during a higher percentage of voltage dip. In this context, primarily a constructive ...

In this paper, a strategy to deal with high-dimensional reliability systems with multiple correlated components is proposed. The goal is to construct a state function that enables the classification of the states of components in one of two categories, that is, failure and operative, in case of dealing with a large number of units in the system. To this end, it is proposed a new algorithm that ...

Researchers and researched populations are actively involved in participatory epidemiology. Such studies collect many details about an individual. Recent developments in statistical inferences can lead to sensitive information leaks from seemingly insensitive data about individuals. Typical safeguarding mechanisms are vetted by ethics committees; however, the attack models are constantly evolving. ...

Patient-gathered self-management data and shared decision-making are touted as the answer to improving an individual’s health situation as well as collaboration between patients and their providers leading to more effective treatment plans. However, there is a gap between this ideal and reality – a lack of data-sharing technology. Here, we present the impact that the FullFlow System for sharing ...

Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from medical examinations. Such models have the potential to provide fast and accurate medical diagnoses. However, the high complexity makes deep neural networks and their predictions difficult to understand. Providing model explanations can be a way ...

The rapid improvement in mobile health technologies revolutionized what and how people can self-record and manage data. This massive amount of information accumulated by these technologies has potentially many applications beyond personal need, i.e. for public health. A challenge with collecting this data is to motivate people to share this data for the benefit of all. The purpose of this study is ...

The amount of content available for consumption online is increasing tremendously. This make the job of recommender systems more important, and at the same time, more demanding. Context-aware recommender systems might be a solution to this problem. This work set out to discover user contexts dynamically by collecting contextual information from user actions and perform cluster analysis on the ...

Most of todays Internet users are registered to one or more social media applications. As so many are registered to multiple application, it has become difficult to locate friends, former colleagues, peers and acquaintances. Reasons for this include private profiles, name collisions, multiple usernames, lack of profile attributes and profile picture. The system designed and implemented in this ...