Human activity recognition (har) using deep learning: Review, methodologies, progress and future research directions
P Kumar, S Chauhan, LK Awasthi - Archives of Computational Methods in …, 2024 - Springer
Human activity recognition is essential in many domains, including the medical and smart
home sectors. Using deep learning, we conduct a comprehensive survey of current state …
home sectors. Using deep learning, we conduct a comprehensive survey of current state …
An ensemble deep learning model for human activity analysis using wearable sensory data
Lately, the continuous temporal data from motion sensors in wearable devices has been
great interest for the research community due to its demand for analyzing human activities in …
great interest for the research community due to its demand for analyzing human activities in …
The applications of metaheuristics for human activity recognition and fall detection using wearable sensors: A comprehensive analysis
In this paper, we study the applications of metaheuristics (MH) optimization algorithms in
human activity recognition (HAR) and fall detection based on sensor data. It is known that …
human activity recognition (HAR) and fall detection based on sensor data. It is known that …
A smart e-health framework for monitoring the health of the elderly and disabled
A Yazici, D Zhumabekova, A Nurakhmetova… - Internet of Things, 2023 - Elsevier
The healthcare sector is experiencing a significant transformation due to the widespread
adoption of IoT-based systems, especially in the care of elderly and disabled individuals …
adoption of IoT-based systems, especially in the care of elderly and disabled individuals …
[HTML][HTML] A DCNN-LSTM based human activity recognition by mobile and wearable sensor networks
Abstract Systems for recognizing human activities are being developed as part of a larger
framework that will allow for continuous monitoring of human behavior in intelligent home …
framework that will allow for continuous monitoring of human behavior in intelligent home …
Human activity recognition from multiple sensors data using deep CNNs
Smart devices with sensors now enable continuous measurement of activities of daily living.
Accordingly, various human activity recognition (HAR) experiments have been carried out …
Accordingly, various human activity recognition (HAR) experiments have been carried out …
Newborn cry-based diagnostic system to distinguish between sepsis and respiratory distress syndrome using combined acoustic features
Z Khalilzad, A Hasasneh, C Tadj - Diagnostics, 2022 - mdpi.com
Crying is the only means of communication for a newborn baby with its surrounding
environment, but it also provides significant information about the newborn's health …
environment, but it also provides significant information about the newborn's health …
An efficient human activity recognition using hybrid features and transformer model
Human activity recognition is a challenging and active research topic in computer science
due to its applications in video surveillance, health monitoring, rehabilitation, human-robot …
due to its applications in video surveillance, health monitoring, rehabilitation, human-robot …
A Systematic Evaluation of Feature Encoding Techniques for Gait Analysis Using Multimodal Sensory Data
This paper addresses the problem of feature encoding for gait analysis using multimodal
time series sensory data. In recent years, the dramatic increase in the use of numerous …
time series sensory data. In recent years, the dramatic increase in the use of numerous …
Dual attention-based deep learning for construction equipment activity recognition considering transition activities and imbalanced dataset
Y Shen, J Wang, C Feng, Q Wang - Automation in Construction, 2024 - Elsevier
With the advancement of sensor and data acquisition technology, the development of multi-
sensor integrated construction equipment has become increasingly prominent. Activity …
sensor integrated construction equipment has become increasingly prominent. Activity …