With the latest advances in deep learning-based generative models, it has not taken long to
take advantage of their remarkable performance in the area of time series. Deep neural …

Human activity recognition (HAR) is a very active yet challenging and demanding area of
computer science. Due to the articulated nature of human motion, it is not trivial to detect …

Currently, identification of complex human activities is experiencing exponential growth
through the use of deep learning algorithms. Conventional strategies for recognizing human …

Among the numerous work-related risk factors, construction workers are often exposed to
awkward working postures that may lead them to develop work-related musculoskeletal …

Abstract Human Activity Recognition (HAR) is an important research area that has profound
applications in healthcare, security and surveillance. Starting from traditional machine …

Despite having a very different kinesthetic sensibility from smartphone sensors, human
bodies assess variations and address specific sensor values. Human Activity Recognition …

Human activity recognition (HAR) based on multimodal wearable motion sensors is a
valuable technology, and gymnastics action recognition is one of its important application …

Abstract Time Series Classification (TSC) in data mining is gradually developing as an
important research direction. Many researchers have developed an extensive interest in …

Older adults are more vulnerable to falling due to normal changes due to aging, and their
falls are a serious medical risk with high healthcare and societal costs. However, there is a …

Sensor-based Human Activity Recognition (HAR) is widely used in daily life and is the basic-
level bridge to virtual healthcare in the metaverse. The current challenge is the low …