Rapid growth of the aged population has caused an immense increase in the demand for
healthcare services. Generally, the elderly are more prone to health problems compared to …

Smartphones are considered as one of the most essential and highly personal devices of
individuals in our current world. Due to the popularity of context-aware technology and …

The deep learning model has been used to predict the variation rule of the target series of
multivariate time series data. Based on the attention mechanism, the influence information of …

Real-life mobile phone data may contain noisy instances, which is a fundamental issue for
building a prediction model with many potential negative consequences. The complexity of …

Change Point Detection (CPD) is the problem of discovering time points at which the
behavior of a time series changes abruptly. In this paper, we present a novel real-time …

Continuous in-home monitoring of older adults living alone aims to improve their quality of
life and independence, by detecting early signs of illness and functional decline or …

Federated Learning marks a turning point in the implementation of decentralized machine
learning (especially deep learning) for wireless devices by protecting users' privacy and …

Chronic disease management and follow-up are vital for realizing sustained patient well-
being and optimal health outcomes. Recent advancements in wearable technologies …

Recent advances in attention networks have gained enormous interest in time series data
mining. Various attention mechanisms are proposed to soft-select relevant timestamps from …

With the recent advancement in wearable computing, sensor technologies, and data
processing approaches, it is possible to develop smart clothing that integrates sensors into …