Author(s): Nakanishi, M (Nakanishi, Masaki); Xu, MP (Xu, Minpeng); Wang, YJ (Wang, Yijun); Chiang, KJ (Chiang, Kuan-Jung); Han, J (Han, Jin); Jung, TP (Jung, Tzyy-Ping)
Source: IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING Volume: 28 Issue: 4 Pages: 1042-1043 DOI: 10.1109/TNSRE.2020.2974272 Published: APR 2020
Abstract: This commentary presents a replication study to verify the effectiveness of a sum of squared correlations (SSCOR)-based steady-state visual evoked potentials (SSVEPs) decoding method proposed by Kumar et al.. We implemented the SSCOR-based method in accordance with their descriptions and estimated its classification accuracy using a benchmark SSVEP dataset with cross validation. Our results showed significantly lower classification accuracy compared with the ones reported in Kumar et al.'s study. We further investigated the sources of performance discrepancy by simulating data leakage between training and test datasets. The classification performance of the simulation was remarkably similar to those reported by Kumar et al.. We, therefore, question the validity of evaluation and conclusions drawn in Kumar et al.'s study.
Accession Number: WOS:000527793800030
PubMed ID: 32078554
ISSN: 1534-4320
eISSN: 1558-0210
Full Text: https://ieeexplore.ieee.org/document/9000718/