Upper-limb Rehabilitation and Assistance

VR-Enabled Human-Robot Interaction Control for Upper-limb Rehabilitation Using Robotic Manipulators

In this project, our main goal is to develop a robotic platform for upper limb rehabilitation of post-stroke patients by incorporating a robotic manipulator and an intelligent control system. This robotic rehabilitation system will be a multipurpose and cost-effective platform while being adaptive to various therapeutic practices.

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HAPTIC-3D: A Reproducible 3-DOF Haptic Robot for Upper-limb Rehabilitation

The objective of the project is the development of the Haptic3D, an interactive robot with 3 degrees of freedom (DOF), for the rehabilitation of movements of the upper limb. The haptic capabilities are added to this device through adaptive impedance/admittance-based control. The system is expandable to incorporate more sensing and actuation modalities, and its integration with VR technology.

Robot-Assisted Study of Human Motor Adaptation in Upper Limbs

In this project, we want to take a closer look at the adaptation of motor learning when an environmental disturbance occurs, particularly when the individual is subjected to a force field applied by a 6-DOF robot. We are interested to learn how the cognitive-motor processes evolve in an environment where the force field evolves.

EMG-Based Control of Assistive Manipulator Robots via Reinforcement Learning

This work uses a continuous actor-critic Reinforcement Learning method for optimizing the control of an assistive robot using myoelectric interface. The RL agent uses a sparse human-delivered training signal, without requiring detailed knowledge about the task domain. This reinforcement-based machine learning framework is well suited for use by both patients and clinical staff, and may be easily adapted to different application domains and the needs of individual amputees.

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Muscle-Activity Sensing and Signal Acquisition

Development of a Wearable EMG Acquisition System

In this project, a customizable EMG acquisition sleeve has been developed using four EMG sensors to detect upper-limb muscle activation, filter them and record them in real-time to be used for robotic systems.