Recognition of human locomotor activities is crucial for monitoring the motion patterns.
Current studies for human locomotor activities recognition focused on detecting basic motion …

In recent years, human activity recognition (HAR) technologies in e-health have triggered
broad interest. In literature, mainstream works focus on the body's spatial information (ie …

Human activity recognition (HAR) plays a pivotal role in various domains, including
healthcare, sports, robotics, and security. With the growing popularity of wearable devices …

Recent advancements in edge computing devices motivate us to develop a sustainable and
reliable technique for multiple gait activities recognition using wearable sensors. This …

Using smartphone sensors to recognize human activity may be advantageous due to the
abundant volume of data that can be obtained. In this paper, we propose a sensor data …

Along with the advancement of several emerging computing paradigms and technologies,
such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of …

Rapid development in detection and recognition of human activity (HAR) based on wearable
sensor data has been witnessed in the recent past and it has become one of the significant …

Human activity recognition (HAR) uses sensor-based technology to predict human activity
using sensor-generated time-series data. According to recent studies, researchers have …

This study introduces a novel convolutional neural network (CNN) architecture,
encompassing both single and multi-head designs, developed to identify a user's …

Human motion analysis using a smartphone-embedded accelerometer sensor provided
important context for the identification of static, dynamic, and complex sequence of activities …