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. 2018 Nov 5;12:751. doi: 10.3389/fnins.2018.00751

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Copyright © 2018 Vaskov, Irwin, Nason, Vu, Nu, Bullard, Hill, North, Patil and Chestek.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Decoding methods. (A) The initial Kalman filter estimates fingertip kinematics based on summed threshold crossings from either the current 50 ms time bin or an optimally chosen time lag (dashed lines show 50 ms lag). (B) Finger motion was characterized in 1 DOF per finger group such that a position of 0 corresponds full extension and 100 corresponds full flexion. Intention estimation was applied to the online kinematics of the initial Kalman filter by taking incorrect decoder velocities (blue arrow) and flipping them (green arrow) to point toward the desired target (red circle), on-target velocities are set to zero. Intention estimation is only applied to estimate parameters for the ReFIT decoder, no knowledge of target locations is used during online control.