Md Ferdous Wahid

Texas A&M University at Qatar

Papers

1

Total Citations

2

H-Index

1

About

Dr. Md Ferdous Wahid is a rising researcher at the intersection of biomedical signal processing and human-robot interaction, with a core focus on advancing assistive and rehabilitative technologies. His most notable contribution is the development of a novel Support Vector Machine-Long Short-Term Memory (SVM-LSTM) fusion model for enhanced joint angle estimation using Electromyography (EMG) signals. This work, published in 2024, directly addresses the critical challenge of accurately predicting human motor intention from non-invasive biological signals. By integrating the strengths of machine learning and deep learning, Dr. Wahid’s approach significantly improves the precision of real-time joint angle prediction, a cornerstone for intuitive control of prosthetics, exoskeletons, and collaborative robots. Although his work is recent, it has already garnered early citations, signaling its potential impact on fields ranging from clinical rehabilitation and ergonomics to sport science. Dr. Wahid’s research is paving the way for more seamless and responsive human-machine collaboration, making him a promising voice in the future of intelligent assistive systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Enhanced Joint Angle Estimation Using Support Vector Machine-Long Short-Term Memory Fusion with Electromyography Signals
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: Texas A&M University at Qatar

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago