Human-centered applications using wearable sensors in combination with machine learning
have received a great deal of attention in the last couple of years. At the same time …

The partial discharge (PD) classification for electric power equipment based on machine
learning algorithms often leads to insufficient generalization ability and low recognition …

Human emotion recognition is an important research problem in various fields like human-
computer interactions, learning, marketing etc. Physiological signals like galvanic skin …

AI techniques have recently been put under the spotlight for analyzing electrocardiograms
(ECGs). However, the performance of AI-based models relies on the accumulation of large …

Collection of biosignals data from wearable devices for machine learning tasks can
sometimes be expensive and time-consuming and may violate privacy policies and …

Background: Atrial arrhythmias, particularly atrial fibrillation (AF), are prevalent
cardiovascular disorders characterized by irregular heart rhythms originating from the atria …

We propose cross-modal attentive connections, a new dynamic and effective technique for
multimodal representation learning from wearable data. Our solution can be integrated into …

Stock price prediction remains a critical aspect of financial market analysis, with deep
learning techniques gaining significant attention for handling complex data patterns. This …