Platform for Multimodal Signal Acquisition for the Control of Lower Limb Rehabilitation Devices

Patients with some sort of motor disability may benefit from robotic rehabilitation since it can provide more control, accuracy and variety of training modes. This enhances the efficiency of the rehabilitation and, therefore, the recovery of the patient. Assistive devices, like exoskeletons or orthoses, can make use of physiological data, such as electromyography (EMG) and electroencephalography (EEG), in order to detect the movement intention. Combination of data can potentially improve the adaptability of assistive devices with respect to the individual demands. Different methods can be applied depending on the neuromuscular disorder, therapy or assistive device. In this work, we present a multimodal interface which integrates EEG, EMG and inertial sensors (IMU) signals. Experiments were conducted with healthy subjects performing lower limb motor tasks. The aim of the proposed system is to analyze the movement intention (EEG signal), the muscle activation (EMG signal) and the limb motion onset (IMU signal). An experimental protocol is proposed. The results obtained showed that the system is capable to acquire and process the biological signals synchronously. Results indicated that the system is able to identify the movement intention, based on the EEG signal, the movement anticipation, based on the muscle activation, and the limb motion onset.