The most significant barrier to success in human activity recognition is extracting and
selecting the right features. In traditional methods, the features are chosen by humans …

Human activity recognition has been widely used in healthcare applications such as elderly
monitoring, exercise supervision, and rehabilitation monitoring. Compared with other …

Human physical activity recognition based on wearable sensors has applications relevant to
our daily life such as healthcare. How to achieve high recognition accuracy with low …

Continuous human activity recognition from inertial signals is performed by splitting these
temporal signals into time windows and identifying the activity in each window. Defining the …

Human activity recognition (HAR) remains a challenging yet crucial problem to address in
computer vision. HAR is primarily intended to be used with other technologies, such as the …

Human Activity Recognition (HAR) has been widely used for various applications, such as
smart homes, healthcare, security and human-robot interaction. In this paper, a novel deep …

The feature extraction of human activity recognition (HAR) based on sensor data has been
studied as a hand-crafted method. The significant feature extraction ability is a key factor in …

A variety of real-life mobile sensing applications are becoming available, especially in the
life-logging, fitness tracking and health monitoring domains. These applications use mobile …

Human activity recognition (HAR) is one of the important research areas in pervasive
computing. Among HAR, sensor-based activity recognition refers to acquiring a high-level …

Human activity recognition (HAR) is an essential component of ambient assistive living. HAR
has traditionally relied on computer vision techniques. However, it has several drawbacks …