Exoskeleton-Mediated Physical Human-Human Interaction for a Sit-to-Stand Rehabilitation Task

TL;DR

This work addresses the challenge of Sit-to-Stand rehabilitation after stroke by introducing a framework where two overground lower-limb exoskeletons mediate therapist–patient interaction through virtual spring–damper couplings and a real-time, constrained quadratic controller. The approach combines a double-stance exoskeleton model with a sparsely constrained balancing strategy based on the Divergent Component of Motion (DCM) to maintain stability while enabling active participation and motor learning. Key innovations include dual interaction modalities (joint-space and CoM-space couplings), a safety-critical OSQP-based optimization that enforces dynamics and joint/CoM bounds, and a protocol to evaluate dyadic performance with different reference tasks. Preliminary results show that haptic coupling improves tracking accuracy in dyadic tasks and that balancing and vertical assistance influence movement patterns and fatigue, suggesting potential for enhanced safety, engagement, and learning in StS rehabilitation and tele-rehabilitation contexts. Future work aims to validate the framework in healthy and clinical populations, assess usability for therapists and patients, and integrate machine learning to handle variability and networking delays.

Abstract

Sit-to-Stand (StS) is a fundamental daily activity that can be challenging for stroke survivors due to strength, motor control, and proprioception deficits in their lower limbs. Existing therapies involve repetitive StS exercises, but these can be physically demanding for therapists while assistive devices may limit patient participation and hinder motor learning. To address these challenges, this work proposes the use of two lower-limb exoskeletons to mediate physical interaction between therapists and patients during a StS rehabilitative task. This approach offers several advantages, including improved therapist-patient interaction, safety enforcement, and performance quantification. The whole body control of the two exoskeletons transmits online feedback between the two users, but at the same time assists in movement and ensures balance, and thus helping subjects with greater difficulty. In this study we present the architecture of the framework, presenting and discussing some technical choices made in the design.

Figures (6)

• Figure 1: Sit-to-Stand rehabilitative framework: two exoskeletons are used to mediate the interaction between two users performing a tracking task in which the position of the two Center of Masses is used as a reference. The controller of the two exoskeletons produces a threefold function: 1) they virtually connect the movements of the two users; 2) they produce vertical assistance on the two by limiting fatigue; and 3) they preserve balancing.
• Figure 2: Balancing constraint for the StS task: Fig. (A) shows how the pose (position and orientation) of the CoM is constrained in both the horizontal and vertical planes; Fig. (B) shows how the position is constrained in the forward movement to avoid falling; Fig. (C) shows how the backward movement is constrained but still leaves the possibility of performing the StS task.
• Figure 3: Composition of trials with different visual feedback profiles: each trial consists of an equal time (30 s) of performing the motion alone, resting, and performing the motion while subjected to virtual interaction. Three types of reference were tested: (A) simple sine, (B) composite sine, and (C) discrete tasks in the range of motion.
• Figure 4: Tracking performance improved when two pilot users were coupled via joint space connection compared to no connection. The left panel shows the total error across repetitions of the StS exercise (mean $\pm$ SD) for two users during solo and dyad trials under two connection stiffnesses. Right panels show the error separated into bias and random across conditions.
• Figure 5: Distribution of Sit-to-Stand motion: (A) task space ($z_{CoM}$) movement distribution under different interaction conditions; (B) task space ($z_{CoM}$) movement distribution while both exoskeletons produce an upward assistance component; (C) joint space ($\bm{q}$) movement distribution of the right knee angle.