Pub Date : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858149
Min-Hee Ahn, Byoung-Kyong Min
Brain machine interfaces (BMIs) enable us to control external devices using our brain signals. Using a grid-shaped flickering line-array and a shrink-rLDA classifier, top-down information could recently be decoded in a steady-state visual evoked potential (SSVEP)-based BMI paradigm. The present study tested its feasibility in online implementation. We found that within reasonable computing time (0.114 s on average) its online system was successfully accomplished with a decoding accuracy of 53.7% on average. The accuracy was 3.2 times significantly higher than the accuracy by random-shuffled data (16.7%). Therefore, using the grid-shaped SSVEP-based BMI, one's multiclass (at least 6 classes) intention can be online decoded and subsequently control external devices.
{"title":"Online implementation of top-down SSVEP-BMI","authors":"Min-Hee Ahn, Byoung-Kyong Min","doi":"10.1109/IWW-BCI.2017.7858149","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858149","url":null,"abstract":"Brain machine interfaces (BMIs) enable us to control external devices using our brain signals. Using a grid-shaped flickering line-array and a shrink-rLDA classifier, top-down information could recently be decoded in a steady-state visual evoked potential (SSVEP)-based BMI paradigm. The present study tested its feasibility in online implementation. We found that within reasonable computing time (0.114 s on average) its online system was successfully accomplished with a decoding accuracy of 53.7% on average. The accuracy was 3.2 times significantly higher than the accuracy by random-shuffled data (16.7%). Therefore, using the grid-shaped SSVEP-based BMI, one's multiclass (at least 6 classes) intention can be online decoded and subsequently control external devices.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124207698","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 : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858175
Yongkoo Park, Wonzoo Chung
The timbre of audio signals has not been clearly defined mathematically. It has been speculated that the time-frequency structure of audio signals is contributed to the timbre property. In this paper, we construct covariance matrix from the multi-band filter bank output signals of an audio signals and apply Common Spatial Pattern (CSP) filter to characterize timbre of audio signals. Simulation results confirms that the covariance matrix from the multi-band audio signals and CSP filter can be used as a potential feature of timbre classification.
{"title":"Timbre classification method based on the Common Spatial Pattern filter","authors":"Yongkoo Park, Wonzoo Chung","doi":"10.1109/IWW-BCI.2017.7858175","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858175","url":null,"abstract":"The timbre of audio signals has not been clearly defined mathematically. It has been speculated that the time-frequency structure of audio signals is contributed to the timbre property. In this paper, we construct covariance matrix from the multi-band filter bank output signals of an audio signals and apply Common Spatial Pattern (CSP) filter to characterize timbre of audio signals. Simulation results confirms that the covariance matrix from the multi-band audio signals and CSP filter can be used as a potential feature of timbre classification.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127375256","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 : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858176
Donghwa Jeong, Jaeseung Jeong, Yongwook Chae, H. Choi
Conventional EEG devices have limitations for the use of Brain-Computer Interface (BCI) because they are uncomfortable to wear in daily life. Since most smartphone users use earphones, a novel Earphone-shaped EEG device, which measures EEG signals in the ear canal while maintaining functions of the earphone, can be powerful tools for BCI. In this report, the attention state recorded from in-ear EEG was discriminated from the resting state to use simple application of one-button menu selection. Power spectral densities (PSD) in eye-closed state, eye-open state, and attention state were compared using autoregressive (AR) Burg method. Using selected features from Fisher ratio, attention state was successfully classified from resting state with support vector machine (SVM). Based on this study, prototypes for stable recording and sound delivery are developing and real-time BCI application using earphone-shaped EEG device will be researched.
{"title":"Identification of Attention State for Menu-Selection using In-Ear EEG Recording","authors":"Donghwa Jeong, Jaeseung Jeong, Yongwook Chae, H. Choi","doi":"10.1109/IWW-BCI.2017.7858176","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858176","url":null,"abstract":"Conventional EEG devices have limitations for the use of Brain-Computer Interface (BCI) because they are uncomfortable to wear in daily life. Since most smartphone users use earphones, a novel Earphone-shaped EEG device, which measures EEG signals in the ear canal while maintaining functions of the earphone, can be powerful tools for BCI. In this report, the attention state recorded from in-ear EEG was discriminated from the resting state to use simple application of one-button menu selection. Power spectral densities (PSD) in eye-closed state, eye-open state, and attention state were compared using autoregressive (AR) Burg method. Using selected features from Fisher ratio, attention state was successfully classified from resting state with support vector machine (SVM). Based on this study, prototypes for stable recording and sound delivery are developing and real-time BCI application using earphone-shaped EEG device will be researched.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130784138","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 : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858170
N. Zhang, Yadong Liu, Zongtan Zhou
In this paper, a brain-computer interface (BCI) paradigm based on steady-state visually evoked potentials (SSVEP) with stimulus targets' number change is designed to simulate the effects of BCI when used in the field of moving objects recognition and tracking. Stimulus' number, path and the target are created at random in each trial. Experimental results show that the paradigm is usable, and there is no a clear decline in the correct rate. This provides a basis for study of the target detection in real environments, and raise a desired for new evaluating indicator.
{"title":"A SSVEP-BCI with random moving stimuli in simulation environment","authors":"N. Zhang, Yadong Liu, Zongtan Zhou","doi":"10.1109/IWW-BCI.2017.7858170","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858170","url":null,"abstract":"In this paper, a brain-computer interface (BCI) paradigm based on steady-state visually evoked potentials (SSVEP) with stimulus targets' number change is designed to simulate the effects of BCI when used in the field of moving objects recognition and tracking. Stimulus' number, path and the target are created at random in each trial. Experimental results show that the paradigm is usable, and there is no a clear decline in the correct rate. This provides a basis for study of the target detection in real environments, and raise a desired for new evaluating indicator.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124951083","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 : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858152
Dong-Ok Won, Han-Jeong Hwang, K. Müller, Seong-Whan Lee
Most of event-related potential (ERP)-based brain-computer interface (BCI) spellers are limited practical value for paralyzed patients with severe oculomotor impairments. Recently, a gaze-independent BCI speller was proposed that uses rapid serial visual presentation (RSVP), but it is difficult to recognize targets because of the rapid presentation of characters. We developed two ERP-based BCI spellers using RSVP with motion, and non-motion stimulation. We evaluated the effect of the two different stimulus conditions on the performance of the speller system with eight participants. The stimulation methods that employ motion stimulation inside the foveal vision demonstrate not only gaze-independence but also higher performance than method that uses non-motion stimulation (88.9% for non-motion RSVP, 90.3% for motion RSVP). The performance of the different stimulation methods was susceptible to ERP latency and amplitudes. As a result, motion-type RSVP stimulation condition (i.e., motion RSVP) had shorter latency and higher amplitudes than the non-motion RSVP stimulation condition. It is expected that the proposed motion RSVP stimulation method could be used for developing a gaze independent BCI system with high performance.
{"title":"Shifting stimuli for brain computer interface based on rapid serial visual presentation","authors":"Dong-Ok Won, Han-Jeong Hwang, K. Müller, Seong-Whan Lee","doi":"10.1109/IWW-BCI.2017.7858152","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858152","url":null,"abstract":"Most of event-related potential (ERP)-based brain-computer interface (BCI) spellers are limited practical value for paralyzed patients with severe oculomotor impairments. Recently, a gaze-independent BCI speller was proposed that uses rapid serial visual presentation (RSVP), but it is difficult to recognize targets because of the rapid presentation of characters. We developed two ERP-based BCI spellers using RSVP with motion, and non-motion stimulation. We evaluated the effect of the two different stimulus conditions on the performance of the speller system with eight participants. The stimulation methods that employ motion stimulation inside the foveal vision demonstrate not only gaze-independence but also higher performance than method that uses non-motion stimulation (88.9% for non-motion RSVP, 90.3% for motion RSVP). The performance of the different stimulation methods was susceptible to ERP latency and amplitudes. As a result, motion-type RSVP stimulation condition (i.e., motion RSVP) had shorter latency and higher amplitudes than the non-motion RSVP stimulation condition. It is expected that the proposed motion RSVP stimulation method could be used for developing a gaze independent BCI system with high performance.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116389485","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 : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858173
Byung Hyung Kim, Sungho Jo
This paper examines the effect of physiological asymmetry on affective stimuli. Particularly, this study aims to investigate the efficacy of inter-hemispheric asymmetry for recognizing human emotions while walking in a building. Causal and temporal asymmetry over the frontal cortex are analyzed empirically. The results suggest that the temporal asymmetry of causal dependence at shorter time scale keeps its asymmetry under contamination of motion artifacts. Further, information asymmetry in motion affects the relationship between hemispheric activation and emotional reactivity. The key contribution of this work is to provide an empirical study of how brain asymmetry is influenced by motion artifacts generated in real-life experiments.
{"title":"An empirical study on effect of physiological asymmetry for affective stimuli","authors":"Byung Hyung Kim, Sungho Jo","doi":"10.1109/IWW-BCI.2017.7858173","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858173","url":null,"abstract":"This paper examines the effect of physiological asymmetry on affective stimuli. Particularly, this study aims to investigate the efficacy of inter-hemispheric asymmetry for recognizing human emotions while walking in a building. Causal and temporal asymmetry over the frontal cortex are analyzed empirically. The results suggest that the temporal asymmetry of causal dependence at shorter time scale keeps its asymmetry under contamination of motion artifacts. Further, information asymmetry in motion affects the relationship between hemispheric activation and emotional reactivity. The key contribution of this work is to provide an empirical study of how brain asymmetry is influenced by motion artifacts generated in real-life experiments.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127972405","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 : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858178
Hoon-Hee Kim, Jaeseung Jeong
In EEG-BMI systems, how to represent user's intention is a most important question. The motor imagery method has used to represent directions where user want machine to move. However, the motor imagery method is just mapping the parts of bodies to directions such as a left hand means moving left. We study novel methods for representations of directions not using the motor imagery. First, we record the EEG signals when a user thought direction where want to move. Second, we used echo state networks paradigm which is one of Reservoir computing method for analysis and classification of non-linear time series. Third, we designed winner-take-all readouts for representations of user's intended directions. These winner-take-all readouts are perfectly classified directions of user's intention using EEG signals.
{"title":"Representations of directions in EEG-BMI using winner-take-all readouts","authors":"Hoon-Hee Kim, Jaeseung Jeong","doi":"10.1109/IWW-BCI.2017.7858178","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858178","url":null,"abstract":"In EEG-BMI systems, how to represent user's intention is a most important question. The motor imagery method has used to represent directions where user want machine to move. However, the motor imagery method is just mapping the parts of bodies to directions such as a left hand means moving left. We study novel methods for representations of directions not using the motor imagery. First, we record the EEG signals when a user thought direction where want to move. Second, we used echo state networks paradigm which is one of Reservoir computing method for analysis and classification of non-linear time series. Third, we designed winner-take-all readouts for representations of user's intended directions. These winner-take-all readouts are perfectly classified directions of user's intention using EEG signals.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"892 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131735519","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 : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858172
Hwi-Jae Kim, Seul-Ki Yeom, K. Seo, Hyun Jeong Kim, Seong-Whan Lee
Distinction of loss and recovery of consciousness is an important component in consciousness study. To find transitions in and out unconsciousness, monitoring depth of anesthesia (DOA) should be reliably assessed. Previous studies have proposed several methods for measuring DOA, and one of the significant methods to identify between awaked and anesthetized state is global filed synchrony (GFS). GFS used the coherence information from the global electroencephalogram (EEG) channels by using the effects of phase and amplitude relationship simultaneously. However, most recent work showed that there were specific independent EEG amplitude as a biomarker of consciousness while changing the transition into and out unconsciousness. In this paper, we proposed a GFS based feature extraction technique, using coefficients of multi-dimensional channels in interest frequency range in repeated sedation condition. It allows to extract significant spatial and spectral features. We classified the ‘wakefulness’ and ‘unconsciousness’ from midazolam-induced sedation and linear discriminant analysis (LDA). As a result, classification performance in 25 subjects represented 97.09%. Also, it showed that the proposed method was an efficient feature extraction method for classification of ‘wakefulness’ and ‘unconsciousness’.
区分意识的丧失与恢复是意识研究的一个重要组成部分。为了发现昏迷状态的过渡，应可靠地评估麻醉监测深度(DOA)。以往的研究提出了几种测量DOA的方法，其中全局场同步(global field synchronization, GFS)是识别清醒和麻醉状态的重要方法之一。GFS同时利用相位和振幅关系的影响，利用了全局脑电信号通道的相干性信息。然而，最近的研究表明，在进入和退出无意识的过程中，有特定的独立脑电图振幅作为意识的生物标志物。本文提出了一种基于GFS的特征提取技术，利用重复镇静状态下兴趣频率范围内的多维通道系数进行特征提取。它允许提取重要的空间和光谱特征。我们从咪达唑仑诱导的镇静和线性判别分析(LDA)中分类了“清醒”和“无意识”。结果，25名受试者的分类成绩占97.09%。结果表明，该方法是一种有效的“清醒”和“无意识”分类特征提取方法。
{"title":"Classification of midazolam-induced sedation depth based on spatial and spectral analysis","authors":"Hwi-Jae Kim, Seul-Ki Yeom, K. Seo, Hyun Jeong Kim, Seong-Whan Lee","doi":"10.1109/IWW-BCI.2017.7858172","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858172","url":null,"abstract":"Distinction of loss and recovery of consciousness is an important component in consciousness study. To find transitions in and out unconsciousness, monitoring depth of anesthesia (DOA) should be reliably assessed. Previous studies have proposed several methods for measuring DOA, and one of the significant methods to identify between awaked and anesthetized state is global filed synchrony (GFS). GFS used the coherence information from the global electroencephalogram (EEG) channels by using the effects of phase and amplitude relationship simultaneously. However, most recent work showed that there were specific independent EEG amplitude as a biomarker of consciousness while changing the transition into and out unconsciousness. In this paper, we proposed a GFS based feature extraction technique, using coefficients of multi-dimensional channels in interest frequency range in repeated sedation condition. It allows to extract significant spatial and spectral features. We classified the ‘wakefulness’ and ‘unconsciousness’ from midazolam-induced sedation and linear discriminant analysis (LDA). As a result, classification performance in 25 subjects represented 97.09%. Also, it showed that the proposed method was an efficient feature extraction method for classification of ‘wakefulness’ and ‘unconsciousness’.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125077139","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 : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858171
Seokyun Ryun, J. Kim, Eunjeong Jeon, C. Chung
Neural activation in high-gamma range (>50 Hz) is robustly observed in sensorimotor area. Previous neurophysiological studies have indicated that there are dominant sensorimotor high-gamma power changes during active movement. Here, we demonstrate that two different movement types (hand grasping and elbow flection) can be discriminated at single-trial conditions with high accuracy using the spatial dynamics of high-gamma features from primary motor cortex. Based on our results, we propose that sensorimotor high-gamma activities during active movement can be a powerful feature for on-going movement classification, and their characteristics mainly represent the instant movement states.
{"title":"Movement classification using ECoG high-gamma powers from human sensorimotor area during active movement","authors":"Seokyun Ryun, J. Kim, Eunjeong Jeon, C. Chung","doi":"10.1109/IWW-BCI.2017.7858171","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858171","url":null,"abstract":"Neural activation in high-gamma range (>50 Hz) is robustly observed in sensorimotor area. Previous neurophysiological studies have indicated that there are dominant sensorimotor high-gamma power changes during active movement. Here, we demonstrate that two different movement types (hand grasping and elbow flection) can be discriminated at single-trial conditions with high accuracy using the spatial dynamics of high-gamma features from primary motor cortex. Based on our results, we propose that sensorimotor high-gamma activities during active movement can be a powerful feature for on-going movement classification, and their characteristics mainly represent the instant movement states.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127946782","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 : 1900-01-01DOI: 10.1109/IWW-BCI.2017.7858160
G. Müller-Putz, P. Ofner, A. Schwarz, J. Pereira, A. Pinegger, C. Dias, Lea Hehenberger, Reinmar J. Kobler, A. Sburlea
Restoring the ability to reach and grasp can dramatically improve quality of life for people with cervical spinal cord injury (SCI). The main challenge in restoring independent reaching and grasping in patients is to develop assistive technologies with intuitive and non-invasive user interfaces. We believe that this challenge can be met by directly translating movement-related brain activity into control signals. During the last decade, we have conducted research on EEG-based brain-computer interfaces (BCIs) for the decoding of movement parameters, such as trajectories and targets. Although our findings are promising, the control is still unnatural. Therefore, we surmise that natural and intuitive control of neuroprostheses could be achieved by developing a novel control framework that incorporates detection of goal directed movement intention, movement decoding, identifying the type of grasp, error potentials detection and delivery of feedback.
{"title":"Towards non-invasive EEG-based arm/hand-control in users with spinal cord injury","authors":"G. Müller-Putz, P. Ofner, A. Schwarz, J. Pereira, A. Pinegger, C. Dias, Lea Hehenberger, Reinmar J. Kobler, A. Sburlea","doi":"10.1109/IWW-BCI.2017.7858160","DOIUrl":"https://doi.org/10.1109/IWW-BCI.2017.7858160","url":null,"abstract":"Restoring the ability to reach and grasp can dramatically improve quality of life for people with cervical spinal cord injury (SCI). The main challenge in restoring independent reaching and grasping in patients is to develop assistive technologies with intuitive and non-invasive user interfaces. We believe that this challenge can be met by directly translating movement-related brain activity into control signals. During the last decade, we have conducted research on EEG-based brain-computer interfaces (BCIs) for the decoding of movement parameters, such as trajectories and targets. Although our findings are promising, the control is still unnatural. Therefore, we surmise that natural and intuitive control of neuroprostheses could be achieved by developing a novel control framework that incorporates detection of goal directed movement intention, movement decoding, identifying the type of grasp, error potentials detection and delivery of feedback.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114984952","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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