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A systematic review of smartphone-based human activity recognition methods for health research
Smartphones are now nearly ubiquitous; their numerous built-in sensors enable continuous
measurement of activities of daily living, making them especially well-suited for health …
measurement of activities of daily living, making them especially well-suited for health …
[HTML][HTML] Human activity recognition with smartphone-integrated sensors: A survey
Abstract Human Activity Recognition (HAR) is an essential area of research related to the
ability of smartphones to retrieve information through embedded sensors and recognize the …
ability of smartphones to retrieve information through embedded sensors and recognize the …
Human activity recognition with accelerometer and gyroscope: A data fusion approach
This paper compares the three levels of data fusion with the goal of determining the optimal
level of data fusion for multi-sensor human activity data. Using the data processing pipeline …
level of data fusion for multi-sensor human activity data. Using the data processing pipeline …
ARFDNet: An efficient activity recognition & fall detection system using latent feature pooling
This paper presents an efficient activity recognition and fall detection system (ARFDNet).
Here, the raw RGB videos are passed to a pose estimation network to extract skeleton …
Here, the raw RGB videos are passed to a pose estimation network to extract skeleton …
[HTML][HTML] Homogeneous data normalization and deep learning: A case study in human activity classification
One class of applications for human activity recognition methods is found in mobile devices
for monitoring older adults and people with special needs. Recently, many studies were …
for monitoring older adults and people with special needs. Recently, many studies were …
Fusion of smartphone sensor data for classification of daily user activities
New mobile applications need to estimate user activities by using sensor data provided by
smart wearable devices and deliver context-aware solutions to users living in smart …
smart wearable devices and deliver context-aware solutions to users living in smart …
Comparison of machine learning techniques for the identification of human activities from inertial sensors available in a mobile device after the application of data …
Human activity recognition (HAR) is a significant research area due to its wide range of
applications in intelligent health systems, security, and entertainment games. Over the past …
applications in intelligent health systems, security, and entertainment games. Over the past …
An efficient machine learning-based elderly fall detection algorithm
Falling is a commonly occurring mishap with elderly people, which may cause serious
injuries. Thus, rapid fall detection is very important in order to mitigate the severe effects of …
injuries. Thus, rapid fall detection is very important in order to mitigate the severe effects of …
Attention mechanism-based bidirectional long short-term memory for cycling activity recognition using smartphones
Bicycles are an ecofriendly mode of transportation, and cycling offers physical and mental
well-being. However, their increased use has resulted in frequent bicycle–human accidents …
well-being. However, their increased use has resulted in frequent bicycle–human accidents …
[HTML][HTML] Ensemble of RNN classifiers for activity detection using a smartphone and supporting nodes
Nowadays, sensor-equipped mobile devices allow us to detect basic daily activities
accurately. However, the accuracy of the existing activity recognition methods decreases …
accurately. However, the accuracy of the existing activity recognition methods decreases …