Protocol for State-Based Decoding of Hand Movement Parameters Using Neural Signals Publisher Pubmed



Ghodrati MT¹ ; Aghababaei S¹ ; Mirfathollahi A^{1, 2} ; Shalchyan V¹ ; Zarrindast MR^{2, 3} ; Daliri MR^{1, 2} Show Affiliations
Source: STAR Protocols Published:2024

Abstract

We present a protocol for decoding kinematic and kinetic parameters from the primary somatosensory cortex during active and passive hand movements in a center-out reaching task using state-based and conventional decoders. We describe steps for preparing data and using the state-based model to classify movement directions into states via feature extraction and predict parameters with regression models (partial least squares and multilinear regression) trained per state. This state-based approach outperforms conventional methods, enhancing accuracy for brain-computer interface applications. For complete details on the use and execution of this protocol, please refer to Mirfathollahi et al.1 © 2024 The Authors