Human activity recognition in artificial intelligence framework: a narrative review
Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …
acquisition devices such as smartphones, video cameras, and its ability to capture human …
Application of raw accelerometer data and machine-learning techniques to characterize human movement behavior: a systematic scoping review
A Narayanan, F Desai, T Stewart… - … of Physical Activity …, 2020 - journals.humankinetics.com
Background: Application of machine learning for classifying human behavior is increasingly
common as access to raw accelerometer data improves. The aims of this scoping review are …
common as access to raw accelerometer data improves. The aims of this scoping review are …
LSTM-CNN architecture for human activity recognition
K Xia, J Huang, H Wang - IEEE Access, 2020 - ieeexplore.ieee.org
In the past years, traditional pattern recognition methods have made great progress.
However, these methods rely heavily on manual feature extraction, which may hinder the …
However, these methods rely heavily on manual feature extraction, which may hinder the …
HARTH: a human activity recognition dataset for machine learning
Existing accelerometer-based human activity recognition (HAR) benchmark datasets that
were recorded during free living suffer from non-fixed sensor placement, the usage of only …
were recorded during free living suffer from non-fixed sensor placement, the usage of only …
AHAR: Adaptive CNN for energy-efficient human activity recognition in low-power edge devices
N Rashid, BU Demirel… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Human activity recognition (HAR) is one of the key applications of health monitoring that
requires continuous use of wearable devices to track daily activities. This article proposes an …
requires continuous use of wearable devices to track daily activities. This article proposes an …
A fast and robust deep convolutional neural networks for complex human activity recognition using smartphone
As a significant role in healthcare and sports applications, human activity recognition (HAR)
techniques are capable of monitoring humans' daily behavior. It has spurred the demand for …
techniques are capable of monitoring humans' daily behavior. It has spurred the demand for …
Human action recognition using deep learning methods on limited sensory data
In recent years, due to the widespread usage of various sensors action recognition is
becoming more popular in many fields such as person surveillance, human-robot interaction …
becoming more popular in many fields such as person surveillance, human-robot interaction …
Human activity classification using Decision Tree and Naive Bayes classifiers
With rapid development in wireless sensor networks and continuous improvements in
developing artificial intelligence-based scientific solutions, the concept of ambient assisted …
developing artificial intelligence-based scientific solutions, the concept of ambient assisted …
Sensor-driven achieving of smart living: A review
P Leelaarporn, P Wachiraphan, T Kaewlee… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
This comprehensive review mainly analyzes and summarizes the recently published works
on IEEExplore in sensor-driven smart living contexts. We have gathered over 150 research …
on IEEExplore in sensor-driven smart living contexts. We have gathered over 150 research …
Adaptive Bayesian inference system for recognition of walking activities and prediction of gait events using wearable sensors
U Martinez-Hernandez, AA Dehghani-Sanij - Neural Networks, 2018 - Elsevier
In this paper, a novel approach for recognition of walking activities and gait events with
wearable sensors is presented. This approach, called adaptive Bayesian inference system …
wearable sensors is presented. This approach, called adaptive Bayesian inference system …