Effect of Mental Training on BCI Performance

Tan, Lee-Fan; Jansari, Ashok; Keng, Shian‐Ling; Goh, Sing-Yau

doi:10.1007/978-3-642-02577-8_69

Cited by 12 publications

(9 citation statements)

References 4 publications

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“…Furthermore, it is interesting to note that this was achieved with BCIs which were not optimised for individuals with CP. Training sessions with the users -either BCI training or training at meditation -could improve the performance of BCI control with a number of users and, potentially, allow more users to achieve significant levels of control (Tan et al, 2009;Mahmoudi et al, 2006). However, it's important to note that statistically significant levels of accuracy do not mean usable BCI control may be achieved.…”

Section: Discussionmentioning

confidence: 99%

On the control of brain-computer interfaces by users with cerebral palsy

Daly

Billinger

Laparra-Hernández³

et al. 2013

Clinical Neurophysiology

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Highlights1. We conduct a feasibility study with 14 individuals with cerebral palsy (CP) to evaluate their control of two online Brain-computer interfaces. 2. Eight of the individuals with CP were able to control at least one of the BCIs at a statistically significant level of accuracy. 3. Analysis of the results reveals that BCIs may be controlled by some individuals with CP. Abstract ObjectiveBrain-computer interfaces (BCIs) have been proposed as a potential assistive device for individuals with cerebral palsy (CP) to assist with their communication needs. However, it is unclear how well-suited BCIs are to individuals with CP. Therefore, this study aims to investigate to what extent these users are able to gain control of BCIs. MethodsThis study is conducted with 14 individuals with CP attempting to control two standard online BCIs (1) based upon sensorimotor rhythm modulations, and (2) based upon steady state visual evoked potentials.Email address: reinhold.scherer@tugraz.at (Reinhold Scherer*) Preprint submitted to Clinical NeurophysiologyMarch 27, 2013 ResultsOf the 14 users, 8 are able to use one or other of the BCIs, online, with a statistically significant level of accuracy, without prior training. Classification results are driven by neurophysiological activity and not seen to correlate with occurrences of artifacts. However, many of these users' accuracies, while statistically significant, would require either more training or more advanced methods before practical BCI control would be possible. ConclusionsThe results indicate that BCIs may be controlled by individuals with CP but that many issues need to be overcome before practical application use may be achieved. SignificanceThis is the first study to assess the ability of a large group of different individuals with CP to gain control of an online BCI system. The results indicate that six users could control a sensorimotor rhythm BCI and three a steady state visual evoked potential BCI at statistically significant levels of accuracy (SMR accuracies; mean ± STD, 0.821 ± 0.116, SSVEP accuracies; 0.422 ± 0.069).

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Section: Discussionmentioning

confidence: 99%

On the control of brain-computer interfaces by users with cerebral palsy

Daly

Billinger

Laparra-Hernández³

et al. 2013

Clinical Neurophysiology

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“…It was observed that control of the relaxed mental state is more unstable, so one of the possible ways to improve control should be to promote the capacity to hold that state, as shown by several studies (Eskandari and Erfanian, 2008;Mahmoudi and Erfanian, 2006;Tan et al, 2009). The reliability of this control is the key to develop more complex asynchronous interfaces with a greater freedom of movement.…”

Section: Discussionmentioning

confidence: 99%

Brain-computer interface: Proposal of a shaping-based training. Psychology technique in BCI system

Silva-Sauer

Aguayo

Velasco-Álvarez

et al. 2013

RBEB

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“…Second, the R 2 value used as a measure of strength of brain signal modulation may just be considered as an indication of control of a BCI and may not result in actual control; link to actual BCI control must be tested. Systems like the mu-based BCI used in this study often require weeks of training to achieve higher levels of accuracy (Tan et al, 2009;Wolpaw & McFarland, 1994;Wolpaw et al, 1991). Additional factors, such as user interface design and motivation, may also have a significant impact on performance.…”

Section: Discussionmentioning

confidence: 97%

“…The effectiveness of BCIs is, however, limited by the ability of users to provide distinguishable changes in their electrophysiological input, also known as BCI illiteracy if done so ineffectively (Sannelli, Braun, Tangermann, & Müller, 2008), in conjunction with usability of the provided control interface (Nam, Jeon, Li, Kim, & Yoon, 2009). Various factors affect this ability and range from the person's current fatigue level to physiological makeup (Tan, Jansari, Keng, & Goh, 2009).…”

Section: Introductionmentioning

confidence: 99%

Individual Characteristics and Their Effect on Predicting Mu Rhythm Modulation

Randolph

Jackson

Karmakar

2010

International Journal of Human-Computer Interaction

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Brain-computer interfaces (BCIs) offer users with severe motor disabilities a nonmuscular input channel for communication and control but require that users achieve a level of literacy and be able to harness their appropriate electrophysiological responses for effective use of the interface. There is currently no formalized process for determining a user's aptitude for control of various BCIs without testing on an actual system. This study presents how basic information captured about users may be used to predict modulation of mu rhythms, electrical variations in the motor cortex region of the brain that may be used for control of a BCI. Based on data from 55 able-bodied users, we found that the interaction of age and daily average amount of hand-and-arm movement by individuals correlates to their ability to modulate mu rhythms induced by actual or imagined movements. This research may be expanded into a more robust model linking individual characteristics and control of various BCIs.

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Effect of Mental Training on BCI Performance

Cited by 12 publications

References 4 publications

On the control of brain-computer interfaces by users with cerebral palsy

On the control of brain-computer interfaces by users with cerebral palsy

Brain-computer interface: Proposal of a shaping-based training. Psychology technique in BCI system

Individual Characteristics and Their Effect on Predicting Mu Rhythm Modulation

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