A systematic review of smartphone-based human activity recognition methods for health research

M Straczkiewicz, P James, JP Onnela - NPJ Digital Medicine, 2021‏ - nature.com
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 …

[HTML][HTML] Human activity recognition with smartphone-integrated sensors: A survey

V Dentamaro, V Gattulli, D Impedovo… - Expert Systems with …, 2024‏ - Elsevier
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 …

Human activity recognition with accelerometer and gyroscope: A data fusion approach

M Webber, RF Rojas - IEEE Sensors Journal, 2021‏ - ieeexplore.ieee.org
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 …

ARFDNet: An efficient activity recognition & fall detection system using latent feature pooling

SK Yadav, A Luthra, K Tiwari, HM Pandey… - Knowledge-based …, 2022‏ - Elsevier
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 …

[HTML][HTML] Homogeneous data normalization and deep learning: A case study in human activity classification

IM Pires, F Hussain, NM Garcia, P Lameski… - Future Internet, 2020‏ - mdpi.com
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 …

Fusion of smartphone sensor data for classification of daily user activities

G Şengül, E Ozcelik, S Misra, R Damaševičius… - Multimedia Tools and …, 2021‏ - Springer
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 …

Comparison of machine learning techniques for the identification of human activities from inertial sensors available in a mobile device after the application of data …

IM Pires, F Hussain, G Marques, NM Garcia - Computers in Biology and …, 2021‏ - Elsevier
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 …

An efficient machine learning-based elderly fall detection algorithm

F Hussain, MB Umair, M Ehatisham-ul-Haq… - arxiv preprint arxiv …, 2019‏ - arxiv.org
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 …

Attention mechanism-based bidirectional long short-term memory for cycling activity recognition using smartphones

VS Nguyen, H Kim, D Suh - IEEE Access, 2023‏ - ieeexplore.ieee.org
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 …

[HTML][HTML] Ensemble of RNN classifiers for activity detection using a smartphone and supporting nodes

M Bernaś, B Płaczek, M Lewandowski - Sensors, 2022‏ - mdpi.com
Nowadays, sensor-equipped mobile devices allow us to detect basic daily activities
accurately. However, the accuracy of the existing activity recognition methods decreases …