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Table 3 BCI feature extraction and classification

From: Brain–computer interface robotics for hand rehabilitation after stroke: a systematic review

Study

Pre-processing

Feature extraction

Classification

Hand task

Ang et al. [75]

Band-pass (0.05–40 Hz)

Filter Bank Common Spatial Pattern (FBCSP) algorithm [105]

Calibration model (unspecified)

MI vs rest

Barsotti et al. [76]

Band-pass (8–24 Hz)

ERD (β and µ-decrease), CSP

SVM with linear kernel

MI vs rest

Bauer et al. [97]

Band-pass (6–16 Hz using zero-phase lag FIR

ERD (β-decrease)

Linear autoregressive model based on Burg Algorithm

MI vs rest

Bundy et al. [77]

Unspecified

ERD (β and µ-decrease)

Linear autoregressive model

MI (affected, unaffected) vs rest

Chowdhury et al. [78]

Band-pass (0.1 Hz-100 Hz), Notch (50 Hz)

CSP Covariance-based, ERD/ERS (β and µ-change)

SVM with linear kernel, Covariate Shift Detection (CSD)-based Adaptive Classifier

left vs right MI

Coffey et al. [92]

Band-pass (0.5 Hz-30 Hz), Notch (50 Hz)

CSP Covariance-based

Linear Discriminant Analysis (LDA) classifier

MI vs rest

Diab et al. [103]

Unspecified

Time epochs (unspecified)

Artificial Neural Network (ANN)-based Feed Forward Back Propagation

Non-MI open vs closed

Frolov al. [80]

Band-pass (5–30 Hz), FIR (order 101), IIR notch Chebyshev type I filter (50 Hz)

Time epochs

(10 s)

Bayesian-based EEG covariance classifier [106]

MI (affected, unaffected) vs rest

Ono et al. [81]

Band-pass (0.5–30 Hz), notch (50 or 60 Hz)

Time epochs (700 ms), ERD (µ-decrease)

Linear Discriminant Analysis (LDA) classifier

MI vs rest

Ramos-Murguialday et al. [95]

Unspecified

Time epochs (5 s), Spatial filter, ERD/ERS (β and µ-change)

Linear autoregressive model

MI vs rest

Vukelic and Gharabaghi [99]

High-pass (unspecified)

ERD (β-decrease)

Linear autoregressive model based on Burg Algorithm

MI vs rest

Witkowski et al. [101]

Band-pass (0.4–70 Hz), Laplacian filter

ERD/ERS (β and µ-change)

Linear autoregressive model based on Yule-Walker algorithm

MI vs rest

  1. SVM Support Vector Machines, FIR Finite Impulse Response, IIR Infinite Impulse Response