Author

Mohammed Alnusayri

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Open access Sep 2026

Accurate human locomotion and localization using hybrid features and deep networks on smartphones

Human locomotion and localization recognition are of critical importance in the development of intelligent systems with the capability of monitoring, analyzing, and responding to human behavior in the real world. This research proposes a robust yet computationally efficient approach by exploiting the sensors of a smart...

Mohammed Alnusayri, I. Abro, Hadeel Alsolai et al. · PeerJ Computer Science · 0 citations

Open access Sep 2026

Asymmetric Dual-Stream Transformers for AI-Driven Vision-Based Human Movement Assessment via Deep Features and GAT Classifier

The integration of AI vision-based sensing and human motion analysis has grown to be a key element of intelligent perception systems, which now allow for automated interpretation of human movement, activity patterns, and complex visual behaviors. However, accurate functional movement assessment from monocular aerial an...

Bader Aldughayfiq, Rehana Bibi, Hisham Allahem et al. · Symmetry · 0 citations

Open access Sep 2026

Hybrid Multi-Domain ECG Feature Learning with mRMR and CNN–Transformer for Cardiac Disease Classification

Cardiovascular disease diagnosis requires accurate and timely analysis of electrocardiogram (ECG) signals to support reliable clinical decision-making. However, ECG signals are inherently non-stationary, exhibit substantial inter-patient variability, and may share similar morphological patterns across different cardiac...

Mohammed Alnusayri, Sara Mumtaz, Bader Aldughayfiq et al. · Bioengineering · 0 citations