Surface electromyography and artificial intelligence for human activity recognition-A systematic review on methods, emerging trends applications, challenges, and …

GJ Rani, MF Hashmi, A Gupta - IEEE Access, 2023 - ieeexplore.ieee.org
Human activity recognition (HAR) has become increasingly popular in recent years due to its
potential to meet the growing needs of various industries. Electromyography (EMG) is …

Headar: Sensing Head Gestures for Confirmation Dialogs on Smartwatches with Wearable Millimeter-Wave Radar

X Yang, X Wang, G Dong, Z Yan, M Srivastava… - Proceedings of the …, 2023 - dl.acm.org
Nod and shake of one's head are intuitive and universal gestures in communication. As
smartwatches become increasingly intelligent through advances in user activity sensing …

[PDF][PDF] Abnormal Behavior Detection in Video Surveillance Using Inception-v3 Transfer Learning Approaches

SA Jebur, KA Hussein, HK Hoomod - Iraqi Journal of Computers …, 2023 - iasj.net
The use of video surveillance systems has increased due to security concerns and their
relatively low cost. Researchers are working to create intelligent Closed Circuit Television …

Classification of wheelchair related shoulder loading activities from wearable sensor data: A machine learning approach

WHK de Vries, S Amrein, U Arnet, L Mayrhuber… - Sensors, 2022 - mdpi.com
Shoulder problems (pain and pathology) are highly prevalent in manual wheelchair users
with spinal cord injury. These problems lead to limitations in activities of daily life (ADL) …

Electromyography (EMG) Signal based Knee Abnormality Prediction using XGBoost Machine Learning Algorithm

GJ Rani, MF Hashmi - 2023 IEEE 2nd International Conference …, 2023 - ieeexplore.ieee.org
When diagnosing illness, assessing sports injuries, and rehabilitating patients, Surface
Electromyography (sEMG) signals play a crucial role. In this study, we use the machine …

Home Activity Recognition for Rural Elderly Based on Deep Learning and Smartphone Sensors

Y Zhang, G Tong, C Lin - Journal of Organizational and End User …, 2024 - igi-global.com
With the exacerbation of the rural aging population trend, home-based health monitoring for
the rural elderly has become a societal focal point, demanding an effective technological …

[PDF][PDF] Unveiling Patterns of Nomophobia Using Data Mining Techniques

H Jabar, MS Abd, SF Behadili, I Ali - Iraqi Journal of Science, 2024 - iasj.net
Nowadays, almost everyone is glued to their phones. It turns out that the fear of being
without your phone has a fancy name: nomophobia. Researchers can now analyze our …

Real-Time Motion Up and Down Activity Recognition Based on Smart Phone and Smart Watch Sensors

RM Afram, GS Abd Al-Muhsen, YH Ali… - … on Current Research …, 2022 - ieeexplore.ieee.org
Human activity recognition has been active research in the last few years. It can be used
effectively in different applications such as fitness, games, indoor localization, healthcare …

Anomaly Detection from Crowded Video by Convolutional Neural Network and Descriptors Algorithm: Survey.

AA Hussan Altalbi, SH Shaker… - International Journal of …, 2023 - search.ebscohost.com
Depending on the context of interest, an anomaly is defined differently. In the case when a
video event isn't expected to take place in the video, it is seen as anomaly. It can be difficult …

Localization of Strangeness for Real Time Video in Crowd Activity Using Optical Flow and Entropy.

AA Hussan Altalbi, SH Shaker… - International Journal of …, 2023 - search.ebscohost.com
Anomaly detection, which is also referred to as novelty detection or outlier detection, is
process of identifying unusual occurrences, observations, or events which considerably …