{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T20:11:39Z","timestamp":1774901499516,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,6,3]],"date-time":"2020-06-03T00:00:00Z","timestamp":1591142400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Substantial developments have been established in the past few years for enhancing the performance of brain\u2013computer interface (BCI) based on steady-state visual evoked potential (SSVEP). The past SSVEP-BCI studies utilized different target frequencies with flashing stimuli in many different applications. However, it is not easy to recognize user\u2019s mental state changes when performing the SSVEP-BCI task. What we could observe was the increasing EEG power of the target frequency from the user\u2019s visual area. BCI user\u2019s cognitive state changes, especially in mental focus state or lost-in-thought state, will affect the BCI performance in sustained usage of SSVEP. Therefore, how to differentiate BCI users\u2019 physiological state through exploring their neural activities changes while performing SSVEP is a key technology for enhancing the BCI performance. In this study, we designed a new BCI experiment which combined working memory task into the flashing targets of SSVEP task using 12 Hz or 30 Hz frequencies. Through exploring the EEG activity changes corresponding to the working memory and SSVEP task performance, we can recognize if the user\u2019s cognitive state is in mental focus or lost-in-thought. Experiment results show that the delta (1\u20134 Hz), theta (4\u20137 Hz), and beta (13\u201330 Hz) EEG activities increased more in mental focus than in lost-in-thought state at the frontal lobe. In addition, the powers of the delta (1\u20134 Hz), alpha (8\u201312 Hz), and beta (13\u201330 Hz) bands increased more in mental focus in comparison with the lost-in-thought state at the occipital lobe. In addition, the average classification performance across subjects for the KNN and the Bayesian network classifiers were observed as 77% to 80%. These results show how mental state changes affect the performance of BCI users. In this work, we developed a new scenario to recognize the user\u2019s cognitive state during performing BCI tasks. These findings can be used as the novel neural markers in future BCI developments.<\/jats:p>","DOI":"10.3390\/s20113169","type":"journal-article","created":{"date-parts":[[2020,6,4]],"date-time":"2020-06-04T04:36:09Z","timestamp":1591245369000},"page":"3169","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Exploration of User\u2019s Mental State Changes during Performing Brain\u2013Computer Interface"],"prefix":"10.3390","volume":"20","author":[{"given":"Li-Wei","family":"Ko","sequence":"first","affiliation":[{"name":"Department of Biological Science and Technology, College of Biological Science and Technology, National Chiao Tung University, Hsinchu 300, Taiwan"},{"name":"Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), National Chiao Tung University, Hsinchu 300, Taiwan"},{"name":"Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu 300, Taiwan"},{"name":"Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung 807, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rupesh Kumar","family":"Chikara","sequence":"additional","affiliation":[{"name":"Department of Biological Science and Technology, College of Biological Science and Technology, National Chiao Tung University, Hsinchu 300, Taiwan"},{"name":"Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), National Chiao Tung University, Hsinchu 300, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi-Chieh","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National Chiao Tung University, Hsinchu 300, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen-Chieh","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National Chiao Tung University, Hsinchu 300, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,3]]},"reference":[{"key":"ref_1","first-page":"213","article-title":"Brain computer interfacing: Applications and challenges","volume":"16","author":"Sarah","year":"2015","journal-title":"Egypt. Inf. J."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tong, J., Lin, Q., Xiao, R., and Ding, L. (2016). Combining multiple features for error detection and its application in brain-computer interface. Biomed. Eng. Online, 15\u201317.","DOI":"10.1186\/s12938-016-0134-9"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1136\/bjo.74.4.255-a","article-title":"Human brain electrophysiology: Evoked-potentials and evoked magnetic-fields in science and medicine","volume":"74","author":"Galloway","year":"1990","journal-title":"Br. J. Ophthalmol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1475","DOI":"10.1364\/JOSA.67.001475","article-title":"Steady-state evoked potentials","volume":"67","author":"Regan","year":"1977","journal-title":"J. Opt. Soc. Am."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1007\/BF01135443","article-title":"Steady-state visually evoked potential topography associated with a visual vigilance task","volume":"3","author":"Richard","year":"1990","journal-title":"Brain Topogr."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.neuroimage.2014.05.060","article-title":"Dissociable mechanisms underlying individual differences in visual working memory capacity","volume":"99","author":"Gulbinaite","year":"2014","journal-title":"Neuroimage"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1037\/0033-2909.132.6.946","article-title":"The restless mind","volume":"132","author":"Smallwood","year":"2006","journal-title":"Psychol. Bull."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1126\/science.1131295","article-title":"Wandering minds: The default network and stimulus-independent thought","volume":"315","author":"Mason","year":"2007","journal-title":"Science"},{"key":"ref_9","unstructured":"Carlstedt, R.A. (2010). Handbook of Integrative Clinical Psychology, Psychiatry, and Behavioral Medicine: Perspectives, Practices, and Research, Springer Publishing Company."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1885","DOI":"10.1016\/j.clinph.2006.01.017","article-title":"Vigilance, alertness, or sustained attention: Physiological basis and measurement","volume":"117","author":"Oken","year":"2006","journal-title":"Clin. Neurophysiol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Kane, M.J., Jarrold, C., Kane, M., Miyake, A., and Towse, J. (2007). Variation in Working Memory Capacity as Variation in Executive Attention and Control, Oxford University Press.","DOI":"10.1093\/acprof:oso\/9780195168648.003.0002"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1002\/hbm.20131","article-title":"N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies","volume":"25","author":"Owen","year":"2005","journal-title":"Hum. Brain Mapp."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4770","DOI":"10.1073\/pnas.93.10.4770","article-title":"Selective attention to stimulus location modulates the steady-state visual evoked potential","volume":"93","author":"Morgan","year":"1996","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/S0926-6410(97)00036-0","article-title":"Effects of spatial selective attention on the steady-state visual evoked potential in the 20\u201328 Hz range","volume":"6","author":"Muller","year":"1998","journal-title":"Brain Res. Cogn. Brain Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1038\/2865","article-title":"The time course of cortical facilitation during cued shifts of spatial attention","volume":"1","author":"Muller","year":"1998","journal-title":"Nat. Neurosci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1038\/nature01812","article-title":"Sustained division of the attentional spotlight","volume":"424","author":"Muller","year":"2003","journal-title":"Nature"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1167\/2.9.1","article-title":"Neural correlates of object-based attention","volume":"2","author":"Pei","year":"2002","journal-title":"J. Vis."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/0013-4694(94)00189-R","article-title":"Steady-state visually evoked potential topography during the Wisconsin card sorting test","volume":"96","author":"Silberstein","year":"1995","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1073\/pnas.95.3.781","article-title":"Event-related brain potentials in the study of visual selective attention","volume":"95","author":"Hillyard","year":"1998","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Xie, S., Liu, C., Klaus, O., Zhu, F., Wang, L., Xie, X., and Wang, W. (2016). Stimulator selection in ssvep-based spatial selective attention study. Comput. Intell. Neurosci., 9.","DOI":"10.1155\/2016\/6410718"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Evain, A., Argelaguet, F., Roussel, N., Casiez, G., and Lecuyer, A. (2017, January 6\u201311). Can I Think of Something Else when Using a BCI? Cognitive demand of an SSVEP-based BCI. Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI \u201917), Denver, CA, USA.","DOI":"10.1145\/3025453.3026037"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1038\/349061a0","article-title":"Localization of a human system for sustained attention by positron emission tomography","volume":"349","author":"Pardo","year":"1991","journal-title":"Nature"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/S0149-7634(01)00063-X","article-title":"Brain imaging of the central executive component of working memory","volume":"26","author":"Collette","year":"2002","journal-title":"Neurosci. Biobehav. Rev."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2657","DOI":"10.1152\/jn.1998.80.5.2657","article-title":"Cortical fMRI activation produced by attentive tracking of moving targets","volume":"80","author":"Culham","year":"1998","journal-title":"J. Neurophysiol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1523\/JNEUROSCI.5228-04.2006","article-title":"Tactile spatial attention enhances gamma-band activity in somatosensory cortex and reduces low-frequency activity in parieto-occipital areas","volume":"26","author":"Bauer","year":"2006","journal-title":"J. Neurosci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3040","DOI":"10.1016\/j.neuroimage.2010.10.008","article-title":"Lost in thoughts: Neural markers of low alertness during mind wandering","volume":"54","author":"Braboszcz","year":"2011","journal-title":"Neuroimage"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"48912","DOI":"10.1109\/ACCESS.2019.2910737","article-title":"Binocular phase-coded visual stimuli for SSVEP-based BCI","volume":"7","author":"Kramberger","year":"2019","journal-title":"IEEE Access"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.neuroimage.2017.08.057","article-title":"On the contribution of motor planning to the retroactive cuing benefit in working memory: Evidence by mu and beta oscillatory activity in the EEG","volume":"162","author":"Schneider","year":"2017","journal-title":"Neuroimage"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/0013-4694(93)90064-3","article-title":"Lapses in alertness: Coherence of fluctuations in performance and EEG spectrum","volume":"86","author":"Makeig","year":"1993","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0306-4522(01)00309-8","article-title":"The boundary between wakefulness and steep: Quantitative electroencephalographic changes during the sleep onset period","volume":"107","author":"Ferrara","year":"2001","journal-title":"Neuroscience"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/S1388-2457(02)00283-3","article-title":"Body posture affects electroencephalographic activity and psychomotor vigilance task performance in sleep-deprived subjects","volume":"114","author":"Caldwell","year":"2003","journal-title":"Clin. Neurophysiol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"27","DOI":"10.3389\/fnhum.2018.00027","article-title":"Monetary Reward and Punishment to Response Inhibition Modulate Activation and Synchronization Within the Inhibitory Brain Network","volume":"12","author":"Chikara","year":"2018","journal-title":"Front. Hum. Neurosci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1037\/h0057431","article-title":"Cerebral states during sleep, as studied by human brain potential","volume":"21","author":"Loomis","year":"1937","journal-title":"J. Exp. Psychol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/0013-4694(61)90008-6","article-title":"The clinical and theoretical importance of EEG rhythms corresponding to states of lowered vigilance","volume":"13","author":"Roth","year":"1961","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.neuroimage.2018.08.001","article-title":"Modeling brain dynamic state changes with adaptive mixture independent component analysis","volume":"183","author":"Hsu","year":"2018","journal-title":"Neuroimage"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.jneumeth.2003.10.009","article-title":"EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis","volume":"134","author":"Delorme","year":"2004","journal-title":"J. Neurosci. Methods"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Szafir, D.B., and Mutlu, B. (2012, January 5\u201310). Pay attention! Designing adaptive agents that monitor and improve user engagement, in CHI \u201912. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Austin, TX, USA.","DOI":"10.1145\/2207676.2207679"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1408","DOI":"10.1016\/j.neuroimage.2006.02.002","article-title":"Where the BOLD signal goes when alpha EEG leaves","volume":"31","author":"Laufs","year":"2006","journal-title":"Neuroimage"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"13170","DOI":"10.1073\/pnas.0700668104","article-title":"Electrophysiological signatures of resting state networks in the human brain","volume":"104","author":"Mantini","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"391","DOI":"10.3389\/fnhum.2017.00391","article-title":"Tradeoff between user experience and BCI classification accuracy with frequency modulated steady-state visual evoked potentials","volume":"11","author":"Dreyer","year":"2017","journal-title":"Front. Hum. Neurosci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1016\/j.neuroimage.2018.03.039","article-title":"Mapping working memory retrieval in space and in time: A combined electroencephalography and electrocorticography approach","volume":"174","author":"Zhang","year":"2018","journal-title":"Neuroimage"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Mathieu, B.B., Emmanuelle, D.D., Tina, M., and Martin, L. (2010). The bank of standardized stimuli (BOSS), a new set of 480 normative photos of objects to be used as visual stimuli in cognitive research. PLoS ONE, 5.","DOI":"10.1371\/journal.pone.0010773"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1016\/j.neuroimage.2018.04.019","article-title":"Enhanced perceptual processing of self-generated motion: Evidence from steady-state visual evoked potentials","volume":"175","author":"Wen","year":"2018","journal-title":"Neuroimage"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.clinph.2019.06.234","article-title":"International federation of clinical neurophysiology (IFCN)-EEG research workgroup: Recommendations on frequency and topographic analysis of resting state EEG rhythms. Part 1: Applications in clinical research studies","volume":"131","author":"Claudio","year":"2020","journal-title":"Clin. Neurophysiol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.cnp.2017.07.002","article-title":"A revised glossary of terms most commonly used by clinical electroencephalographers and updated proposal for the report format of the EEG findings. Revision 2017","volume":"2","author":"Nick","year":"2017","journal-title":"Clin. Neurophysiol. Pr."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Efron, B., and Tibshirani, R.J. (1994). An Introduction to the Bootstrap: Monographs on Statistics & Applied Probability, CRC press.","DOI":"10.1201\/9780429246593"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: A practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Ser. B Methodol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1088\/1741-2560\/4\/2\/R01","article-title":"A review of classification algorithms for EEG-based brain-computer interfaces","volume":"4","author":"Lotte","year":"2007","journal-title":"J. Neural Eng."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1088\/1741-2560\/3\/2\/008","article-title":"Different classification techniques considering brain computer interface applications","volume":"3","author":"Rezaei","year":"2006","journal-title":"J. Neural Eng."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1016\/S0896-6273(01)00499-8","article-title":"Attention response functions: Characterizing brain areas using fMRI activation during parametric variations of attentional load","volume":"32","author":"Culham","year":"2001","journal-title":"Neuron"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.neuroimage.2018.04.006","article-title":"Representation of steady-state visual evoked potentials elicited by luminance flicker in human occipital cortex: An electrocorticography study","volume":"175","author":"Wittevrongel","year":"2018","journal-title":"Neuroimage"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1016\/j.neuroimage.2005.04.014","article-title":"Frontal midline EEG dynamics during working memory","volume":"27","author":"Onton","year":"2005","journal-title":"Neuroimage"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1395","DOI":"10.1046\/j.1460-9568.2002.01975.x","article-title":"Frontal theta activity in humans increases with memory load in a working memory task","volume":"15","author":"Jensen","year":"2002","journal-title":"Eur. J. Neurosci."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/S0167-8760(96)00053-0","article-title":"EEG delta activity: An indicator of attention to internal processing during performance of mental tasks","volume":"24","author":"Harmony","year":"1996","journal-title":"Int. J. Psychophysiol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1850050","DOI":"10.1142\/S0129065718500508","article-title":"Temporal modulation of steady-state visual evoked potentials","volume":"29","author":"Labecki","year":"2019","journal-title":"Int. J. Neural. Syst."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Chikara, R.K., and Ko, L.W. (2019). Neural Activities Classification of Human Inhibitory Control Using Hierarchical Model. Sensors, 19.","DOI":"10.3390\/s19173791"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1850018","DOI":"10.1142\/S0129065718500181","article-title":"Control of a 7-DOF robotic arm system with an SSVEP-based BCI","volume":"28","author":"Chen","year":"2018","journal-title":"Int. J. Neural. Syst."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"46010","DOI":"10.1088\/1741-2552\/aabb82","article-title":"A study on dynamic model of steady-state visual evoked potentials","volume":"15","author":"Zhang","year":"2018","journal-title":"J. Neural Eng."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"36021","DOI":"10.1088\/1741-2552\/aaae73","article-title":"A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance","volume":"15","author":"Astrand","year":"2018","journal-title":"J. Neural Eng."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1002\/dir.10063","article-title":"Internet advertising: Is anybody watching?","volume":"17","author":"Dreze","year":"2003","journal-title":"J. Interact. Market."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Malheiros, M., Jennett, C., Patelm, S., Brostoff, S., and Angela, M. (2012, January 5). Too close for comfort: A study of the effectiveness and acceptability of rich-media personalized advertising. Proceedings of the CHI \u201912, SIGCHI Conference on Human Factors in Computing Systems, Austin, TX, USA.","DOI":"10.1145\/2207676.2207758"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1016\/j.neuroimage.2016.04.030","article-title":"Structural and functional correlates of motor imagery BCI performance: Insights from the patterns of fronto-parietal attention network","volume":"134","author":"Zhang","year":"2016","journal-title":"Neuroimage"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"185","DOI":"10.3389\/fnhum.2016.00185","article-title":"Neural Mechanisms of Inhibitory Response in a Battlefield Scenario: A Simultaneous fMRI-EEG Study","volume":"10","author":"Ko","year":"2016","journal-title":"Front. Hum. Neurosci."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/11\/3169\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:35:16Z","timestamp":1760175316000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/11\/3169"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,3]]},"references-count":63,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["s20113169"],"URL":"https:\/\/doi.org\/10.3390\/s20113169","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,3]]}}}