Discovering new treatments and personalizing existing ones is one of the major goals of
modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the …

The last 20 years have seen ever-increasing research activity in the field of human activity
recognition. With activity recognition having considerably matured, so has the number of …

Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …

Human activity recognition (HAR) tasks have traditionally been solved using engineered
features obtained by heuristic processes. Current research suggests that deep convolutional …

Recently, deep learning (DL) methods have been introduced very successfully into human
activity recognition (HAR) scenarios in ubiquitous and wearable computing. Especially the …

Wearable devices have recently received considerable interest due to their great promise for
a plethora of applications. Increased research efforts are oriented towards a non-invasive …

In the age of digital technology, as teens seem to be constantly connected online, via social
media, and through mobile applications, it is no surprise that they increasingly turn to digital …

Purpose The purpose of this paper is to examine the determinants of user adoption of
smartphone fitness apps in context of an emerging economy. Design/methodology/approach …

The revolution of Internet of Things (IoT) is pervading many facets of our everyday life.
Among the multiple IoT application domains, well-being is becoming one of the popular …

Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable
ground from academia and industry. CMA is the state-of-the-art mobile augmentation model …