Nima Akhlaghi

George Mason University

Papers

1

Total Citations

159

H-Index

1

About

Nima Akhlaghi is a leading researcher at the intersection of biomedical engineering and human-machine interaction, whose work is redefining how we sense and interpret muscle activity. His primary contributions lie in advancing non-invasive sensing techniques for prosthetic control and rehabilitation robotics, moving beyond traditional surface electromyography (sEMG). Akhlaghi’s most influential work, “Real-Time Classification of Hand Motions Using Ultrasound Imaging of Forearm Muscles” (2015, 159 citations), pioneered the use of ultrasound to capture the mechanical deformation of muscles during movement. This approach offers a more robust and stable signal than electrical methods, enabling finer, real-time classification of hand gestures. By demonstrating that ultrasound imaging can decode complex motor intent with high accuracy, Akhlaghi has opened a new pathway for more intuitive and reliable myoelectric prostheses. His research has been instrumental in shifting the field toward multimodal sensing, combining mechanical and electrical data to create more resilient muscle-computer interfaces. With a growing citation impact, Akhlaghi’s work continues to inspire engineers and clinicians seeking to restore natural movement for individuals with limb loss.

Research Focus

Key Achievements

1
H-Index
1
Papers
159
Total Citations
159
Avg Citations/Paper
🏆 Most Cited Paper
Real-Time Classification of Hand Motions Using Ultrasound Imaging of Forearm Muscles
159 citations · 2015
📈 Most Prolific Year: 2015 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: George Mason University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago