Decoding human intent using a wearable system and multi-modal sensor data

Despite the phenomenal advances in the computational power of electronic systems, human-machine interaction has been largely limited to simple control panels, such as keyboards and mice, which only use physical senses. Consequently, these systems either rely critically on close human guidance or operate almost independently. A richer experience can be achieved if cognitive inputs are used in addition to the physical senses. Towards this end, this paper introduces a simple wearable system that consists of a motion processing unit and brain-machine interface. We show that our system can successfully employ cognitive indicators to predict human activity.