Albara Ah Ramli

University of California, Davis

Papers

1

Total Citations

64

H-Index

1

About

Albara Ah Ramli is a researcher at the intersection of healthcare, artificial intelligence, and wearable technology, with a primary focus on human activity recognition (HAR). His most cited work, "An Overview of Human Activity Recognition Using Wearable Sensors: Healthcare and Artificial Intelligence" (2022), has garnered 64 citations, establishing him as a key voice in this rapidly evolving field. In this comprehensive review, Ramli synthesizes advances in sensor-based HAR, demonstrating how AI-driven analysis of wearable data can transform patient monitoring, rehabilitation, and chronic disease management. His contributions bridge the gap between raw sensor signals and actionable health insights, emphasizing the critical role of deep learning and feature engineering in improving recognition accuracy. Beyond this seminal paper, Ramli's research explores robust, real-world deployment of HAR systems, addressing challenges like data variability and energy efficiency. His work has significant implications for personalized medicine and remote healthcare, making him a notable figure in the push toward intelligent, non-invasive health monitoring. For students and researchers, Ramli exemplifies how interdisciplinary approaches—combining signal processing, machine learning, and clinical needs—can drive impactful innovation in digital health.

Research Focus

Key Achievements

1
H-Index
1
Papers
64
Total Citations
64
Avg Citations/Paper
🏆 Most Cited Paper
An Overview of Human Activity Recognition Using Wearable Sensors: Healthcare and Artificial Intelligence
64 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of California, Davis

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago