Helena Wu
Papers
1
Total Citations
16
H-Index
1
About
Helena Wu’s research lies at the intersection of motor learning, cognitive ergonomics, and human performance, with a focus on how individuals acquire and refine complex motor skills. Her most-cited work, a 2019 study on reaching movements, investigates the dynamic interplay between motor performance, mental workload, and self-efficacy across multiple practice sessions. This research offers critical insights into how learners’ confidence and cognitive demands evolve with repetition, informing training protocols in rehabilitation, sports, and human-machine interaction. With 16 citations, the paper has influenced studies on adaptive learning systems and workload-aware feedback design. Wu’s contributions are particularly notable for bridging subjective self-efficacy measures with objective performance metrics, providing a holistic view of skill acquisition. Her work underscores the importance of considering psychological states alongside physical practice, a perspective that resonates with educators and clinicians seeking to optimize learning environments. By illuminating how mental workload fluctuates as expertise develops, Wu has helped shape more personalized, efficient training strategies. Her research continues to inspire investigations into the cognitive underpinnings of motor learning, making her a rising voice in human factors and motor control.
Research Focus
Key Achievements
Top Papers
- 1