Decoding Upper Limb Trajectory Based on Invasively and Non-invasively Measured Electrical Activity of the Brain

Student: Monina Maria

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Applied Mathematics (Bachelor)

Year of Graduation: 2019

This paper presents results and analysis of two methods of experiment to obtain data on the trajectory of the upper limb by measuring the electrical activity of the working human brain. The main purpose is to investigate the possibility of decoding kinematic parameters of finger movement by two measurement types of human brain activity. Likewise, it is aimed to understand which research method is more accurate: invasive or non-invasive ones. The following technologies are employed: magnetoencephalography and electrocorticography processes using the Brainstorm package and Python algorithms for visual and matrix representation of the model. Based on an analysis of two data acquisition methods, the results are compared with each other, and the active area is demonstrated.

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