Robot-aided rehabilitation task design for inner shoulder muscles

Robot-aided motion planning for knee joint rehabilitation with two robot-manipulators

In this paper, we propose a simultaneous design method of motion and external force trajectories for knee joint rehabilitation based on the biomechanical analysis of the lower limb. In this method we assume to use two robots manipulators which provide forces and moments at shank and thigh. We developed a 7 degree of freedom musculoskeletal model of lower limb with 19 muscles. The valuation function of rehabilitation efficiency e has been maximized by Genetic Algorithm (GA) that refers to the musculoskeletal model and tunes motion trajectory of the robots and forces acting on the shank and thigh.

Admittance control scheme for implementing model-based assistance-as-needed on a robot

A model-based assistance-as-needed paradigm has been developed to govern the assistance provided by an assistive robot to its operator. This paradigm has advantages over existing methods of providing assistance-as-needed for applications such as robotic rehabilitation. However, implementation of the model-based paradigm requires a control scheme to be developed which controls the robot so as to provide the assistance calculated by the model-based paradigm to its operator. In this paper an admittance control scheme for providing model-based assistance-as-needed is presented. It is developed considering its suitability for human-robot interaction, and its role within the model-based assistance-as-needed framework. Results from the control implemented on an example robot showed it is capable of providing the operator with the desired level of assistance as governed by the model-based paradigm. This is an essential requirement for the paradigm to be capable of providing efficacious assistance-as-needed in applications such as robotic rehabilitation.

Experimental evaluation of a model-based assistance-as-needed paradigm using an assistive robot

In robotic rehabilitation a promising paradigm is assistance-as-needed. This is because it promotes patient active participation which is essential for neuro-rehabilitation. A model-based assistance-as-needed paradigm has been developed which utilizes a musculoskeletal model representing the subject to calculate their assistance needs. In this paper we experimentally evaluate this model-based paradigm to control an assistive robot and provide a subject with assistance-as-needed at the muscular level. A subject with impairments defined in specific muscle groups performs a number of upper limb tasks, whilst receiving assistance from a robotic exoskeleton. The paradigm is evaluated on its ability to provide assistance only as the subject needs, depending on the tasks being performed and the impairments defined. Results show that the model-based assistance-as-needed paradigm was relatively successful in providing assistance when it was needed.