@article{scholars15846,
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
         journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},
           pages = {597--606},
            year = {2021},
           title = {Optimizing mental workload estimation by detecting baseline state using vector phase analysis approach},
            note = {cited By 4},
          volume = {29},
             doi = {10.1109/TNSRE.2021.3062117},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101768113&doi=10.1109\%2fTNSRE.2021.3062117&partnerID=40&md5=713cebec3c95897381ad2e2a210dffce},
        keywords = {Brain computer interface; Near infrared spectroscopy, Functional near infrared spectroscopy; Hemodynamic response; Hemodynamic signals; Hemoglobin concentration; Mental arithmetic; Mental workload; Optimal baselines; Phase analysis, Infrared devices, Article; behavior; clinical article; deoxygenation; functional near-infrared spectroscopy; hemodynamic parameters; hemodynamics; hemoglobin determination; human; human experiment; normal human; optimal baseline block; primary motor cortex; raw baseline block; suboptimal baseline block; vector phase analysis; working memory; workload; brain computer interface; hemodynamics; mathematics; near infrared spectroscopy, Brain-Computer Interfaces; Hemodynamics; Humans; Mathematics; Spectroscopy, Near-Infrared; Workload},
        abstract = {Improper baseline return from the previous task-evoked hemodynamic response (HR) can contribute to a large variation in the subsequent HR, affecting the estimation of mental workload in brain-computer interface systems. In this study, we proposed a method using vector phase analysis to detect the baseline state as being optimal or suboptimal. We hypothesize that selecting neuronal-related HR as observed in the optimal-baseline blocks can lead to an improvement in estimating mental workload. Oxygenated and deoxygenated hemoglobin concentration changes were integrated as parts of the vector phase. The proposed method was applied to a block-design functional near-infrared spectroscopy dataset (total blocks = 1384), measured on 24 subjects performing multiple difficulty levels of mental arithmetic task. Significant differences in hemodynamic signal change were observed between the optimal- and suboptimal-baseline blocks detected using the proposed method. This supports the effectiveness of the proposed method in detecting baseline state for better estimation of mental workload. The results further highlight the need of customized recovery duration. In short, the proposed method offers a practical approach to detect task-evoked signals, without the need of extra probes. {\^A}{\copyright} 2001-2011 IEEE.},
          author = {Lim, L. G. and Ung, W. C. and Chan, Y. L. and Lu, C.-K. and Funane, T. and Kiguchi, M. and Tang, T. B.},
            issn = {15344320}
}