Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share By
Protocol for State-Based Decoding of Hand Movement Parameters Using Neural Signals Publisher Pubmed



Ghodrati MT1 ; Aghababaei S1 ; Mirfathollahi A1, 2 ; Shalchyan V1 ; Zarrindast MR2, 3 ; Daliri MR1, 2
Authors

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
Other Related Docs
4. A Robust Beamforming Approach for Early Detection of Readiness Potential With Application to Brain-Computer Interface Systems, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society# EMBS (2017)