activity
20242026
most citedRobot-mediated physical Human-Human Interaction in Neurorehabilitation: a position paper

1 citations · 1 across the 3 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Therapist-Exoskeleton-Patient Interaction for Gait Therapy

Emek Barış Küçüktabak, Matthew R. Short, Lorenzo Vianello +4

Following a stroke, individuals often experience mobility and balance impairments due to lower-limb weakness and loss of independent joint control. Gait recovery is a key goal of r…

cs.RO2026

Learning Therapist Policy from Therapist-Exoskeleton-Patient Interaction

Grayson Snyder, Lorenzo Vianello, Levi Hargrove +2

Post-stroke rehabilitation is often necessary for patients to regain proper walking gait. However, the typical therapy process can be exhausting and physically demanding for therap…

cs.RO2026

Proximal powered knee placement: a case study

Kyle R. Embry, Lorenzo Vianello, Jim Lipsey +8

Lower limb amputation affects millions worldwide, leading to impaired mobility, reduced walking speed, and limited participation in daily and social activities. Powered prosthetic…

cs.RO20251 cited

Robot-mediated physical Human-Human Interaction in Neurorehabilitation: a position paper

Lorenzo Vianello, Matthew Short, Julia Manczurowsky +25

Neurorehabilitation conventionally relies on the interaction between a patient and a physical therapist. Robotic systems can improve and enrich the physical feedback provided to pa…

cs.RO2025

Deep-Learning Control of Lower-Limb Exoskeletons via simplified Therapist Input

Lorenzo Vianello, Clément Lhoste, Emek Barış Küçüktabak +3

Partial-assistance exoskeletons hold significant potential for gait rehabilitation by promoting active participation during (re)learning of normative walking patterns. Typically, t…

cs.RO2024

Deep-Learning Estimation of Weight Distribution Using Joint Kinematics for Lower-Limb Exoskeleton Control

Clément Lhoste, Emek Barış Küçüktabak, Lorenzo Vianello +4

In the control of lower-limb exoskeletons with feet, the phase in the gait cycle can be identified by monitoring the weight distribution at the feet. This phase information can be…