This article proposes an automatic fall detection method for a wearable device that can
promptly alert caregivers when a fall is detected, which could reduce the injuries of elder …

The escalating use of security cameras has resulted in a surge in images requiring analysis,
a task hindered by the inefficiency and error-prone nature of manual monitoring. In …

Gait analysis is a standard practice used by clinicians and researchers to identify
abnormalities, examine disease progression, or assess the success of interventions …

Delivering health care at home emerged as a key advancement to reduce healthcare costs
and infection risks, as during the SARS-Cov2 pandemic. In particular, in motor training …

With the development of 5G vertical applications, a huge amount of unlabeled network data
can be collected, which can be employed for evaluating the user experience and network …

Detecting anomalies in human gait could be used as indicators of human fall risk or other
underlying health or psychological issues. This would require collecting reliable gait data …

Abstract Gait Abnormality Detection (GAD) plays an important role in diagnosing diseases
associated with abnormal gait patterns. However, existing works are limited in …

Dictionary methods for system identification typically rely on one set of measurements to
learn governing dynamics of a system. In this paper, we investigate how fusion of output …

Multivariate time series anomaly detection is crucial in many applications, including finance,
healthcare, transportation, power grids, and water treatment plants. However, due to the …

In recent years, artificial intelligence chatbots have attracted more and more attention. The
stability and accuracy of automatic speech recognition (ASR) have been improved, making …