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Brain-Machine Interfaces for Motor Functionality : An Introduction

ABSRACT Brain-Machine Interfaces (BMI) for motor functions are used in an attempt to generate actions based on impulse from the primary motor projection area of the cerebral cortex. The neural signals are captured via invasive or non-invasive methods and processed to determine the intended response. Invasive methods capture the action potentials directly, while noninvasive methods use electroencephalograms (EEGs) to capture the electromagnetic fields of the action potentials instead. Since the pertinent information of an action potential is whether it exists, a spike detection algorithm is used to process and sort the information. BMI technology using invasive and noninvasive means has been used with success with primates and rats to control both neuroprosthetics and other objects. Additionally, controlling a robot in an indoor environment has been successful using an EEG on human subjects. Future research in this field will include additional sensory feedback mechanisms, especially tactile senses, and working in conjunction with Functional Electrical Stimulation (FES) to control a subject's body after damage to the neural system, rather than an artificial system. Present BMI systems have developed the underlying framework. However, advanced research in creating higher density electrode arrays and advances in non-invasive techniques is still necessary to develop a more realistic experience for the user.