Human activity recognition (HAR) using inertial motion data has gained a lot of momentum
in recent years both in research and industrial applications. From the abstract perspective …

Detection and localization of activities in a human-centric manufacturing assembly operation
will help improve manufacturing process optimization. Through the human-in-loop …

Recent advances in egocentric video understanding models are promising, but their heavy
computational expense is a barrier for many real-world applications. To address this …

Sensor-based human activity recognition with wearable devices has captured the attention
of researchers in the last decade. The possibility of collecting large sets of data from various …

Human activity recognition (HAR) is an important subfield of pervasive computing and
pattern recognition. While researchers have achieved remarkable results in feature …

The real-time monitoring of assembly operations in manufacturing industries can be used for
manufacturing process optimization, which is crucial to manufacturers. It helps to improve …

Gait recognition is significant in the fields of disease diagnosis and rehabilitation training by
studying the characteristics of human gait with different terrain. To address the problem that …

With their automatic feature extraction capabilities, deep learning models have become
more widespread in sensor-based human activity recognition, particularly on larger …

Human locomotion is an imperative topic to be conversed among researchers. Predicting
the human motion using multiple techniques and algorithms has always been a motivating …

Exoskeletons designed for rehabilitation and movement assistance are essential for
addressing the physiological issues of aging in the elderly. Recognizing locomotion …