Behavioral changes in daily home activities may be linked with health problems. Therefore,
anomaly detection on sequence pattern of home activities is important for healthcare …

Electrical anomalies in residential buildings represent a serious problem that can
unpredictably change the power profiles of end-users, causing a sub-optimal energy …

Heart rate is one of the most important indicators of health status. In place of conventional
contact-based devices, contactless vital sensing methods that utilize radio waves have been …

In recent years, biometric radar has gained increasing attention in the field of non-touch vital
sign monitoring due to its high accuracy and strong ability to detect fine-grained movements …

Electrocardiogram (ECG) analysis is widely used in the diagnosis of cardiovascular
diseases. This article proposes an explainable rule-mining strategy for prioritizing abnormal …

Automatic diagnosis of cardiac events is a current problem of interest in which deep learning
has shown promising success. We have earlier reported the use of Long Short Term …

Anomaly detection is a fundamental problem that consists of identifying irregular patterns
that do not conform to the expected behavior of a system or the generated data. Many …

Given a large-scale rhythmic time series containing mostly normal data segments (or
'beats'), can we learn how to detect anomalous beats in an effective yet efficient way? For …

Over the past decade, there has been an explosion of consumer devices for the purposes of
health and fitness tracking. The wearable technology market, composed of devices that …

Monitoring a patient's vital signs is considered one of the most challenging problems in
telehealth systems, especially when patients reside in remote locations. Companies now …