RESUMEN
Lower extremity function recovery is one of the most important goals in stroke rehabilitation. Many paradigms and technologies have been introduced for the lower limb rehabilitation over the past decades, but their outcomes indicate a need to develop a complementary approach. One attempt to accomplish a better functional recovery is to combine bottom-up and top-down approaches by means of brain-computer interfaces (BCIs). In this study, a BCI-controlled robotic mirror therapy system is proposed for lower limb recovery following stroke. An experimental paradigm including four states is introduced to combine robotic training (bottom-up) and mirror therapy (top-down) approaches. A BCI system is presented to classify the electroencephalography (EEG) evidence. In addition, a probabilistic model is presented to assist patients in transition across the experiment states based on their intent. To demonstrate the feasibility of the system, both offline and online analyses are performed for five healthy subjects. The experiment results show a promising performance for the system, with average accuracy of 94% in offline and 75% in online sessions.
Asunto(s)
Electroencefalografía , Interfaces Cerebro-Computador , Humanos , Extremidad Inferior , Robótica , Rehabilitación de Accidente CerebrovascularRESUMEN
An estimated of 2,000,000 acute ankle sprains occur annually in the United States. Furthermore, ankle disabilities are caused by neurological impairments such as traumatic brain injury, cerebral palsy and stroke. The virtually interfaced robotic ankle and balance trainer (vi-RABT) was introduced as a cost-effective platform-based rehabilitation robot to improve overall ankle/balance strength, mobility and control. The system is equipped with 2 degrees of freedom (2-DOF) controlled actuation along with complete means of angle and torque measurement mechanisms. Vi-RABT was used to assess ankle strength, flexibility and motor control in healthy human subjects, while playing interactive virtual reality games on the screen. The results suggest that in the task with 2-DOF, subjects have better control over ankle's position vs. force.
Asunto(s)
Tobillo/fisiología , Actividad Motora/fisiología , Robótica/métodos , Fenómenos Biomecánicos , Humanos , Rango del Movimiento Articular , Interfaz Usuario-ComputadorRESUMEN
Stroke is a leading cause of serious long-term disability in the United States. There is a need for new technological adjuncts to expedite patients' scheduled discharge from hospital and pursue rehabilitation procedure at home. SQUID is a low-cost, smart shirt that incorporates a six-channel electromyography (EMG) and heart rate data acquisition module to deliver objective audiovisual and haptic biofeedback to the patient. The sensorized shirt is interfaced with a smartphone application, for the subject's usage at home, as well as the online database, for the therapist's remote supervision from hospital. A single healthy subject was recruited to investigate the system functionality during improperly performed exercise. The system can potentially be used in automated, remote monitoring of variety of physical therapy exercises, rooted in strength or coordination training of specific muscle groups.
Asunto(s)
Teléfono Celular , Ejercicio Físico , Servicios de Atención de Salud a Domicilio , Monitoreo Fisiológico/instrumentación , Interfaz Usuario-Computador , Electromiografía , Humanos , Accidente Cerebrovascular/fisiopatología , Rehabilitación de Accidente CerebrovascularRESUMEN
Ankle impairment and lower limb asymmetries in strength and coordination are common symptoms for individuals with selected musculoskeletal and neurological impairments. The virtual reality augmented cycling kit (VRACK) was designed as a compact mechatronics system for lower limb and mobility rehabilitation. The system measures interaction forces and cardiac activity during cycling in a virtual environment. The kinematics measurement was added to the system. Due to the constrained problem definition, the combination of inertial measurement unit (IMU) and Kalman filtering was recruited to compute the optimal pedal angular displacement during dynamic cycling exercise. Using a novel benchmarking method the accuracy of IMU-based kinematics measurement was evaluated. Relatively accurate angular measurements were achieved. The enhanced VRACK system can serve as a rehabilitation device to monitor biomechanical and physiological variables during cycling on a stationary bike.