Papers

3

Total Citations

60

H-Index

3

About

Heba Aly is a pioneering researcher at the intersection of neural engineering and human-computer interaction, whose work bridges the gap between advanced bio-signal processing and accessible technology. Her primary research areas encompass Brain-Computer Interfaces (BCIs), deep learning for motion classification, and digital privacy education for vulnerable populations. Aly’s most impactful contribution is her development of a hybrid BCI system that fuses EEG and EMG signals to control upper limb prostheses, offering amputees intuitive, residual-function-based control. Her 2021 paper on a deep learning model for motion classification using EEG and EMG signal fusion has garnered 38 citations, underscoring its influence in bio-robotics. In a notable pivot, Aly’s recent 2024 work explores the perceived trustworthiness of human versus AI instructors in digital privacy education for older adults, revealing that seniors prefer human-led instruction—a finding with critical implications for inclusive technology design. With a growing citation record and a portfolio that spans from neural signal processing to ethical AI deployment, Aly is shaping the future of assistive technologies and human-centered computing.

Research Focus

Key Achievements

3
H-Index
3
Papers
60
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Bio-signal based motion control system using deep learning models: a deep learning approach for motion classification using EEG and EMG signal fusion
38 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Arab Academy for Science, Technology, and Maritime Transport, Clemson University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago