Pub Date : 2022-08-08DOI: 10.1080/2326263x.2022.2109855
Farzana Khanam, A. A. Hossain, Mohiudding Ahmad
{"title":"Electroencephalogram-based cognitive load level classification using wavelet decomposition and support vector machine","authors":"Farzana Khanam, A. A. Hossain, Mohiudding Ahmad","doi":"10.1080/2326263x.2022.2109855","DOIUrl":"https://doi.org/10.1080/2326263x.2022.2109855","url":null,"abstract":"","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"24 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82574215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.1080/2326263x.2022.2057757
Joseph B. Humphries, Daniela J. S. Mattos, J. Rutlin, Andy G. S. Daniel, Kathleen Rybczynski, Theresa Notestine, J. Shimony, H. Burton, A. Carter, E. Leuthardt
{"title":"Motor Network Reorganization Induced in Chronic Stroke Patients with the Use of a Contralesionally-Controlled Brain Computer Interface","authors":"Joseph B. Humphries, Daniela J. S. Mattos, J. Rutlin, Andy G. S. Daniel, Kathleen Rybczynski, Theresa Notestine, J. Shimony, H. Burton, A. Carter, E. Leuthardt","doi":"10.1080/2326263x.2022.2057757","DOIUrl":"https://doi.org/10.1080/2326263x.2022.2057757","url":null,"abstract":"","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"75 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74568609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-21DOI: 10.1080/2326263x.2022.2068324
Silvio Da Col, Eunsik Kim, A. Sanna
{"title":"Human performance and mental workload in augmented reality: brain computer interface advantages over gestures","authors":"Silvio Da Col, Eunsik Kim, A. Sanna","doi":"10.1080/2326263x.2022.2068324","DOIUrl":"https://doi.org/10.1080/2326263x.2022.2068324","url":null,"abstract":"","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"4 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85724679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-11DOI: 10.1080/2326263x.2022.2057758
Kevin M. Pitt, Miechelle McKelvey, K. Weissling
{"title":"The perspectives of augmentative and alternative communication experts on the clinical integration of non-invasive brain-computer interfaces","authors":"Kevin M. Pitt, Miechelle McKelvey, K. Weissling","doi":"10.1080/2326263x.2022.2057758","DOIUrl":"https://doi.org/10.1080/2326263x.2022.2057758","url":null,"abstract":"","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"49 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86014774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-04DOI: 10.1080/2326263x.2022.2054606
D. A. Blanco-Mora, A. Aldridge, C. Jorge, A. Vourvopoulos, P. Figueiredo, S., Bermúdez I Badia
There are many factors outlined in the signal processing pipeline that impact brain–computer interface (BCI) performance, but some methodological factors do not depend on signal processing. Nevertheless, there is a lack of research assessing the effect of such factors. Here, we investigate the impact of VR, immersiveness, age, and spatial resolution on the classifier performance of a Motor Imagery (MI) electroencephalography (EEG)-based BCI in naïve participants. We found significantly better performance for VR compared to non-VR (15 electrodes: VR 77.48 ± 6.09%, non-VR 73.5 ± 5.89%, p = 0.0096; 12 electrodes: VR 73.26 ± 5.2%, non-VR 70.87 ± 4.96%, p = 0.0129; 7 electrodes: VR 66.74 ± 5.92%, non-VR 63.09 ± 8.16%, p = 0.0362) and better performance for higher electrode quantity, but no significant differences were found between immersive and non-immersive VR. Finally, there was not a statistically significant correlation found between age and classifier performance, but there was a direct relation found between spatial resolution (electrode quantity) and classifier performance (r = 1, p = 0.0129, VR; r = 0.99, p = 0.0859, non-VR).
{"title":"Impact of age, VR, immersion, and spatial resolution on classifier performance for a MI-based BCI","authors":"D. A. Blanco-Mora, A. Aldridge, C. Jorge, A. Vourvopoulos, P. Figueiredo, S., Bermúdez I Badia","doi":"10.1080/2326263x.2022.2054606","DOIUrl":"https://doi.org/10.1080/2326263x.2022.2054606","url":null,"abstract":"There are many factors outlined in the signal processing pipeline that impact brain–computer interface (BCI) performance, but some methodological factors do not depend on signal processing. Nevertheless, there is a lack of research assessing the effect of such factors. Here, we investigate the impact of VR, immersiveness, age, and spatial resolution on the classifier performance of a Motor Imagery (MI) electroencephalography (EEG)-based BCI in naïve participants. We found significantly better performance for VR compared to non-VR (15 electrodes: VR 77.48 ± 6.09%, non-VR 73.5 ± 5.89%, p = 0.0096; 12 electrodes: VR 73.26 ± 5.2%, non-VR 70.87 ± 4.96%, p = 0.0129; 7 electrodes: VR 66.74 ± 5.92%, non-VR 63.09 ± 8.16%, p = 0.0362) and better performance for higher electrode quantity, but no significant differences were found between immersive and non-immersive VR. Finally, there was not a statistically significant correlation found between age and classifier performance, but there was a direct relation found between spatial resolution (electrode quantity) and classifier performance (r = 1, p = 0.0129, VR; r = 0.99, p = 0.0859, non-VR).","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"28 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90466322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-13DOI: 10.1080/2326263x.2022.2050513
Mehrnoosh Neghabi, H. Marateb, A. Mahnam
{"title":"Novel frequency-based approach for detection of steady-state visual evoked potentials for realization of practical brain computer interfaces","authors":"Mehrnoosh Neghabi, H. Marateb, A. Mahnam","doi":"10.1080/2326263x.2022.2050513","DOIUrl":"https://doi.org/10.1080/2326263x.2022.2050513","url":null,"abstract":"","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"69 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89110657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-02DOI: 10.1080/2326263x.2022.2041294
Yiyuan Han, P. Ziebell, A. Riccio, S. Halder
The ideal brain–computer interface (BCI) adapts to the user’s state to enable optimal BCI performance. Two methods of BCI adaptation are commonly applied: User-centered design (UCD) responds to individual user needs and requirements. Passive BCIs can adapt via online analysis of electrophysiological signals. Despite similar goals, these methods are rarely discussed in combi-nation. Hence, we organized a workshop for the 8th International BCI Meeting 2021 to discuss the combined application of both methods. Here we expand upon the workshop by discussing UCD in more detail regarding its utility for end-users as well as non-end-user-based early-stage BCI development. Furthermore, we explore electrophysiology-based online user state adaptation concerning consciousness and pain detection. The integration of the numerous BCI user state adaptation methods into a unified process remains challenging. Yet, further systematic accumula- tion of specific knowledge about assessment and integration of internal user states bears great potential for BCI optimization.
{"title":"Two sides of the same coin: adaptation of BCIs to internal states with user-centered design and electrophysiological features","authors":"Yiyuan Han, P. Ziebell, A. Riccio, S. Halder","doi":"10.1080/2326263x.2022.2041294","DOIUrl":"https://doi.org/10.1080/2326263x.2022.2041294","url":null,"abstract":"The ideal brain–computer interface (BCI) adapts to the user’s state to enable optimal BCI performance. Two methods of BCI adaptation are commonly applied: User-centered design (UCD) responds to individual user needs and requirements. Passive BCIs can adapt via online analysis of electrophysiological signals. Despite similar goals, these methods are rarely discussed in combi-nation. Hence, we organized a workshop for the 8th International BCI Meeting 2021 to discuss the combined application of both methods. Here we expand upon the workshop by discussing UCD in more detail regarding its utility for end-users as well as non-end-user-based early-stage BCI development. Furthermore, we explore electrophysiology-based online user state adaptation concerning consciousness and pain detection. The integration of the numerous BCI user state adaptation methods into a unified process remains challenging. Yet, further systematic accumula- tion of specific knowledge about assessment and integration of internal user states bears great potential for BCI optimization.","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"140 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80000024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-14DOI: 10.1080/2326263x.2022.2033073
Camille Benaroch, M. Yamamoto, A. Roc, Pauline Dreyer, C. Jeunet, F. Lotte
{"title":"When should MI-BCI feature optimization include prior knowledge, and which one?","authors":"Camille Benaroch, M. Yamamoto, A. Roc, Pauline Dreyer, C. Jeunet, F. Lotte","doi":"10.1080/2326263x.2022.2033073","DOIUrl":"https://doi.org/10.1080/2326263x.2022.2033073","url":null,"abstract":"","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"2016 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89350222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-12DOI: 10.1080/2326263x.2022.2029308
C. D. Guerrero-Méndez, A. F. Ruiz-Olaya
{"title":"Coherence-based connectivity analysis of EEG and EMG signals during reach-to-grasp movement involving two weights","authors":"C. D. Guerrero-Méndez, A. F. Ruiz-Olaya","doi":"10.1080/2326263x.2022.2029308","DOIUrl":"https://doi.org/10.1080/2326263x.2022.2029308","url":null,"abstract":"","PeriodicalId":45112,"journal":{"name":"Brain-Computer Interfaces","volume":"86 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90335575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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