This page shows different videos related to the development and execution of the proprioception and lower limb rehabilitation exercises performed in this research project.
Generation and validation of a lower limb proprioception test
This video shows the generation and validation of a lower limb proprioception test. First, the robot and the vision system is calibrated. Then it is shown how the desired exercise can be generated. For this purpose, the medical staff indicates the desired position and orientation for the end of the robot’s mobile platform. This can be achieved in a very simple and intuitive way thanks to the developed position and force control. Finally, the patient executes the exercise so that he/she must position (with eyes closed) the leg in the same location as indicated by the physician.
Clinical evaluation of lower limb proprioception
This video shows an exercise of the clinical evaluation of lower limb proprioception using a parallel robot.
Clinical evaluation of ankle propioception: plantar/dosiflexion and eversion/inversion
This video shows an exercise of the clinical evaluation of ankle proprioception. The video has two movements: a plantar/dorsiflexion and an eversion/inversion.
Muscle-targeted robotic assistive control using musculoskeletal model of the lower limb
This video shows an innovative assistive robot controller that aims to target specific muscles in the lower limb using a musculoskeletal model.
Traditional control frameworks for human-robot interaction predominantly operate in joint or task space and focus on position and exchanged forces, with limited consideration for human biomechanics, particularly muscular forces. Moreover, conventional manual rehabilitation techniques employed by physiotherapists are limited in their ability to obtain quantitative measurements and make precise modifications to key human variables, resulting in predominantly qualitative methods and results.
In response to these limitations, our proposed control framework operates primarily in the human muscular space, leveraging real-time measurements of muscular forces obtained from a calibrated musculoskeletal model of the lower limb. These measurements enable establishing a multistep closed-loop controller, with the outer loop precisely tracking desired muscular forces.
The controller is implemented within a configurable viscous environment and provides a natural response for the user. Experimental evaluations are conducted using a parallel robot designed for rehabilitation purposes, demonstrating the controller’s efficacy in accurately tracking the forces of specific muscles. The findings highlight the potential applications of this control framework in areas such as assistive robotics and rehabilitation, addressing the need for quantitative assessment and targeted muscle assistance.
This video shows two experiments using the assitive robot controller, involving the Rectus femoris and the Biceps femoris musculus