Jessica Lanini
Papers
2
Total Citations
100
H-Index
2
About
Jessica Lanini’s research sits at the intersection of neurorehabilitation, biomechanics, and human-robot interaction, with a focus on restoring mobility after neurological injury. Her major contributions include the development of a multidirectional gravity-assist algorithm that enhances locomotor control in patients with stroke or spinal cord injury—a breakthrough that leverages gravity-dependent gait interactions to promote active, adaptive learning. This work, cited 59 times, has been instrumental in rethinking how robotic exoskeletons and rehabilitation devices can foster natural recovery by engaging the body’s own mechanics. Lanini also advanced the field of physical human-robot interaction by framing human intention detection as a multiclass classification problem, enabling robots to recognize a partner’s movement goals during collaborative walking tasks, such as carrying an object with a humanoid. Her 2018 paper on this topic, with 41 citations, has shaped how researchers design more intuitive, responsive robotic systems for rehabilitation and assistive contexts. Through these achievements, Lanini has demonstrated how integrating biomechanical principles with machine learning can create smarter, safer, and more effective technologies for restoring and augmenting human movement.
Research Focus
Key Achievements
Top Papers
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- 2