Papers
7
Total Citations
414
H-Index
6
About
Vered Aharonson is a leading researcher at the intersection of affective computing, speech processing, and biomedical engineering. Her seminal work on the automatic classification of emotional user states, particularly through acoustic and linguistic feature analysis, has been foundational in the field. Her most-cited paper (189 citations) explores how low-level descriptors and functionals can classify emotional states from children interacting with a pet robot, while her follow-up study (146 citations) systematically identifies the most important feature types for detecting emotion-related states in speech. These contributions have shaped how machines interpret human emotion from voice, with direct applications in human-robot interaction and assistive technologies. Beyond emotion recognition, Aharonson has made notable strides in neuro-rehabilitation and assistive robotics. Her work on predicting response to robot-aided motor therapy for children with cerebral palsy (10 citations) and developing a robotic walking aid for elderly gait monitoring (10 citations) demonstrates her commitment to translating computational methods into real-world clinical tools. More recently, she has ventured into brain-computer interfaces, developing a four-class BCI system for discriminating wrist and finger movements (2021), promising to restore hand functionality for motor-impaired individuals. With a career spanning emotion classification, rehabilitation robotics, and neural interfaces, Aharonson’s interdisciplinary research continues to push boundaries in human-centered technology.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Patterns, prototypes, performance: classifying emotional user states41 citations · 2008
- 4
- 5
- 6Gait monitoring for the elderly using a robotic walking aid10 citations · 2010
- 7