Human Activity Recognition (HAR) has become an increasingly popular task for embedded
devices such as smartwatches. Most HAR systems for ultra-low power devices are based on …

Human Activity Recognition (HAR) based on inertial data is an increasingly diffused task on
embedded devices, from smartphones to ultra low-power sensors. Due to the high …

Human Activity Recognition (HAR) is the automatic detection and understanding of human
motion behavior based on data extracted from video camera, ambient sensors or wearable …

This chapter focuses on the problem of human activity recognition (HAR), in which inputs in
the form of multichannel time series signals are acquired from a set of body-worn wearable …

Bringing artificial intelligence to embedded devices has become a central research topic in
many scientific domains (environment, agriculture, sociology, health...). For Human Activity …

Recently, convolutional neural networks (CNNs) have set latest state-of-the-art on various
human activity recognition (HAR) datasets. However, deep CNNs often require more …

Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Human Activity Recognition (HAR) is becoming an essential part of human life care. Existing
HAR methods are usually developed using a two-level approach, wherein a first-level …

In recent years, real-time human activity recognition (HAR) has reached importance due to
its applications in various domains such as assistive services for the elderly in smart …

Deep convolutional neural networks (CNNs) achieve state-of-the-art performance in
wearable human activity recognition (HAR), which has become a new research trend in …