Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …

Human activity recognition (HAR) has become a significant area of research in human
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …

Sensor-based activity recognition seeks the profound high-level knowledge about human
activities from multitudes of low-level sensor readings. Conventional pattern recognition …

Increased life expectancy coupled with declining birth rates is leading to an aging
population structure. Aging-caused changes, such as physical or cognitive decline, could …

Due to the wide application of human activity recognition (HAR) in sports and health, a large
number of HAR models based on deep learning have been proposed. However, many …

There has been an upsurge recently in investigating machine learning techniques for activity
recognition (AR) problems as they have been very effective in extracting and learning …

This paper presents a deep learning model'PP-Net'which is the first of its kind, having the
capability to estimate the physiological parameters: Diastolic blood pressure (DBP), Systolic …

Decoding human activity accurately from wearable sensors can aid in applications related to
healthcare and context awareness. The present approaches in this domain use recurrent …

In this paper, we present a deep learning framework “Rehab-Net” for effectively classifying
three upper limb movements of the human arm, involving extension, flexion, and rotation of …