Ankle torque estimation for lower-limb robotic rehabilitation

• Ano de defesa: 2018
• Autor(a) principal: Campo Jaimes, Jonathan
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Algoritmos de estimação; Ankle torque; Control strategies; Estimation algoritms; Estratégias de controle; Human-robot interaction; Interação humano-robô; Reabilitação robótica; Robotic rehabilitation; Torque no tornozelo
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/18/18149/tde-08102018-164536/

In robotic rehabilitation therapies, knowledge of human joint torques is important for patient safety, to provide a reliable data for clinical assessment and to increase control performance of the device, nevertheless, its measurement can be complex or have a highcost implementation. The most of techniques for torque estimation have been developed for upper limb robotic rehabilitation devices, in addition, they typically require detailed anthropometric and musculoskeletal models. In this dissertation is presented the ankle torque estimation for the Anklebot robot, the estimation uses an ankle/Anklebot dynamic model that consider the ankle joint angular displacement and velocity measurement, its mechanical impedance parameters are obtained through a second-order modeled mechanical impedance of the ankle and an identification of frictional and gravitational torques. Three approaches for the ankle torque estimation were proposed to be implemented in the Anklebot robot, the Generalized Momentum, the Kalman filter and finally a combination of both the above mentioned approaches. The validation of such approaches was developed first on a physical mockup configured to reproduce the human ankle joint movement, by assessing its performances, the Kalman filter approach was selected to be implemented on a voluntary subject. A set of experiments were performed considering the physical activity that the subject may realize when interacting with the Anklebot, the developed ankle torque estimation proved to be successful for passive torque and in most of the proposed scenarios where active torque is performed.