A rehabilitation robot with force-position hybrid fuzzy controller: hybrid fuzzy control of rehabilitation robot

Abstract

The goal of this study was to design a robot system for assisting in the rehabilitation of patients with neuromuscular disorders by performing various facilitation movements. The robot should be able to guide patient's wrist to move along planned linear or circular trajectories. A hybrid position/force controller incorporating fuzzy logic was developed to constrain the movement in the desired direction and to maintain a constant force along the moving direction. The controller was stable in the application range of movements and forces. Offline analyses of data were used to quantitatively assess the progress of rehabilitation. The results show that the robot could guide the upper limbs of subjects in linear and circular movements under predefined external force levels and apply a desired force along the tangential direction of the movements.

Robot-assisted humanized passive rehabilitation training based on online assessment and regulation

“…In clinical therapy, the actual physical state of training impaired-limb (PSTIL) is dynamically changed due to the uncertain internal or external disturbances [11]. Moreover, the planned training range and speed is usually adjusted in real time according to the subject's state of the illness and training performances.…”

“…Thus, in a sense, the uncertain internal or external disturbances affect the control performances of the motion training [11], which is usually reflected on the position-velocity tracking performances during the passive training. In our previous work [15], we adopted the position-velocity tracking features to assess the PSTIL, which is combined with the fuzzy logic reasoning.…”

“…Currently, the existing robot-assisted passive training is usually executed with tracking the predefined trajectory using various developed motion control methods, and the predefined trajectory is changeless during the training [11,16]. In this research, based on clinical application, we proposed a system design method for robot-assisted humanization passive training, which online regulates the training motion parameters with developed real-time assessing-and-regulating section.…”

“…For passive training, one control system is usually designed to control the robot smoothly and stably to draw the impaired limb moving along a predefined trajectory with the designed position controller. Thus, in passive training mode, the existing investigations mainly focus on developing control strategies based on position control and planning trajectory [11,12]. O'Malley, et al designed a PD trajectory controller with fixed gain to mange the Rice Wrist to serve the passive training [13].…”

Nuevo Enfoque para la Clasificación de Señales EEG usando la Varianza de la Diferencia entre las Clases de un Clasificador Bayesiano

“…Generalmente, la rehabilitación se basa en la experiencia y en las habilidades del fisioterapeuta. Sin embargo, debido al gran número de pacientes y al tiempo que debe invertirse en las terapias, el hecho de contar con un robot para asistir en el tratamiento representa un gran avance (Ju et al, 2005). Varios controladores digitales pueden proyectarse para el control de un robot para rehabilitación basado en la predicción del movimiento.…”