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Real-time decoding of different levels of force Parkinson's disease (PD) patients implanted with deep brain stimulation (DBS) electrodes in the Subthalamic Nucleus (STN) brain area attempts to extend the leg with 3 different force levels (0%, 33%, 66% of maximum force) while sitting. The decoder takes local field potentials (LFP) signals from the STN and predicts the intended force level in real time while the patient is executing the action. Offline decoding of walking and freezing of gait PD patients implanted with DBS electrodes in STN area of the brain walks with two different lengths of stride. Occasionally, the patient exhibits freezing of gait (FoG). The decoder takes as input the LFP signals from STN to classify different states of walking and FoG. Brain signal dynamics while walking PD patients implanted with DBS electrodes attempts in the STN brain area walks on the ground with different strides and their corresponding brain dynamics are reflected on LFP signals. Non-invasive real-time decoding of human brain signals A paraplegic subject attempts to move his own paralyzed legs. His intention is recognized and feedback for the corresponding leg is shown in real time. Brain-controlled lower-limb exoskeleton 5 able-bodied subjects perform a 3-way control (front, turn left & right) of a powered lower-limb exoskeleton using motor imagery. Hierarchical task representation learning The computer learns hierarchical representation of a task by observing human demonstrator performing a series of actions. |