Papers
6
Total Citations
44
H-Index
5
About
Rami Alazrai is a researcher whose work sits at the intersection of human-computer interaction, robotics, and biomedical signal processing. His primary research areas include emotion recognition, human action identification, and the control of prosthetic devices. Alazrai’s major contributions include developing a real-time emotion recognition system (RTERS) for socially intelligent robots, which achieved 13 citations, and a Nonlinear AutoRegressive with eXogenous input (NARX)-based approach for identifying emotions from video, cited 11 times. He has also made significant strides in assistive technology, proposing an ensemble-based regression method for continuously estimating wrist and finger movements from surface electromyography (sEMG) signals, a work with 7 citations that aims to improve the control of robotic hands for amputees. Additionally, his connectionist-based human action recognition system (CHARS) and wavelet-based sEMG analysis for hand joint angle estimation further demonstrate his impact. With a total of over 44 citations across his top papers, Alazrai’s work is foundational for developing empathetic robots and advanced prosthetics, blending machine learning with real-world applications to enhance human-robot interaction and quality of life.
Research Focus
Key Achievements
Top Papers
- 1Real-time emotion identification for socially intelligent robots13 citations · 2012
- 2An NARX-based approach for human emotion identification11 citations · 2012
- 3
- 4A connectionist-based approach for human action identification6 citations · 2012
- 5
- 6