Recently, electromyogram (EMG) has been proposed for addressing some key limitations of
current biometrics. Wrist-worn wearable sensors can provide a non-invasive method for …

Mainstream unsupervised anomaly detection algorithms often excel in academic datasets,
yet their real-world performance is restricted due to the controlled experimental conditions …

Multivariate signals are prevalent in various domains, such as healthcare, transportation
systems, and space sciences. Modeling spatiotemporal dependencies in multivariate …

This work provides a complete dataset containing surface electromyography (sEMG) signals
acquired from the forearm with a sampling frequency of 1000 Hz. The dataset is named …

Abstract Recently, electromyogram (EMG), the electrical activity of skeletal muscles, has
been proposed as a novel biometric trait to address the limitations of current biometrics …

Time series data are prevalent in many medical domains. Two major types of medical time
series data are (a) biosignals and (b) longitudinal electronic health record (EHR) data …