Fluctuations in Frequency Composition of Neural Activity Observed by Portable Brain Intention Detection Device

Abstract:

As part of the goal of developing wearable sensor technologies, we have continued the development of a headset system for monitoring activity across the primary motor cortex of the brain. Through the combination of electroencephalography (EEG) and near-infrared spectroscopy (NIRS), the headsets are capable of monitoring event-related potentials and hemodynamic activity, which are wirelessly transmitted to a computer for real-time processing to generate control signals for a motorized prosthetic limb or a virtual embodiment of one or more limbs. This paper focuses on recent observations that have been made regarding the frequency content of EEG data, which we believe is responsible for the high performance we have previously reported using artificial neural networks to infer user’s intentions. While the inference engine takes advantage of frequency content from 0-128 Hertz (Hz), distinct fluctuations in alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-100 Hz) frequency bands are human-observable across varying upper limb motor exercises when observed at the group level. In addition to prosthetic limbs, this technology is continuing to be investigated for application in areas including pain treatment, robotic arm control, lie detection, and more general brain-computer interfaces.

• Periodical: Advances in Science and Technology (Volume 96)
• Pages: 89-94
• DOI: https://doi.org/10.4028/www.scientific.net/AST.96.89
• Online since: October 2014
• Authors: Rahmat A. Shoureshi*, Christopher M. Aasted
• Keywords: Artificial Limb Control, Artificial Neural Network (ANN), Electroencephalography, Near Infrared Spectroscopy (NIRS)

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