A Brain-Computer Interface as Input Channel for a Standard Assistive Technology Software

Zickler, Claudia; Riccio, Angela; Leotta, Francesco; Hillian-Tress, Sandra; Halder, Sebastian; Holz, Elisa Mira; Staiger-Sälzer, Pit; Hoogerwerf, Evert Jan; Desideri, Lorenzo; Mattia, Donatella; Kübler, Andrea

doi:10.1177/155005941104200409

Cited by 134 publications

(157 citation statements)

References 30 publications

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“…It may be acceptable to patients if the time needed to select a symbol or make a decision (e.g., yes or no) is in the order of minutes. In principle, detecting focused attention on one of the streams is sufficient to realize an ssBCI and thus, to control any kind of AT software or device that can be controlled by simple binary yes/no commands [15]. Therefore, since single-trial classification was not successful in patients but significant effects were found on average only, future modifications of the paradigm should aim at signal processing and classification methods involving averaging of many data segments.…”

Section: Discussionmentioning

confidence: 99%

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The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

Pokorny

Klobassa

Pichler

et al. 2013

Artificial Intelligence in Medicine

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Objective: Within this work an auditory P300 brain-computer interface (BCI) based on tone stream segregation, which allows for binary decisions, was developed and evaluated. Materials and methods: Two tone streams consisting of short beep tones with infrequently appearing deviant tones at random positions were used as stimuli. This paradigm was evaluated in 10 healthy subjects and applied to 12 patients in a minimally conscious state (MCS) at clinics in Graz, Würzburg, Rome, and Liège. A stepwise linear discriminant analysis (SWLDA) classifier with 10 × 10 cross-validation was used to detect the presence of any P300 and to investigate attentional modulation of the P300 amplitude. Results:The results for healthy subjects were promising and most classification results were better than random. However, for MCS patients only a small number of classification results were above chance level and none of the results were sufficient for communication purposes. Nevertheless, signs of consciousness were detected in most patients, not on a single-trial basis, but after averaging of corresponding data segments and computing significant differences. These significant results, however, strongly varied across sessions and conditions. Conclusion: This work shows the transition of a paradigm from healthy subjects to MCS patients. Promising results with healthy subjects are, however, no guarantee of good results with patients. Therefore, more investigations are required before any definite conclusions about the usability of this paradigm for MCS patients can be drawn. Nevertheless, this paradigm might offer an opportunity to support bedside clinical assessment of MCS patients and eventually, to provide them with a means of communication.

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Section: Discussionmentioning

confidence: 99%

“…Both requirements can be fulfilled by using a single-switch BCI (ssBCI) which reliably detects one specific brain pattern of the patient [13,14]. Consequently, any kind of assistive technology (AT) can be controlled by simple binary yes/no commands provided by the ssBCI [15].…”

Section: Introductionmentioning

confidence: 99%

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

Pokorny

Klobassa

Pichler

et al. 2013

Artificial Intelligence in Medicine

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“…Important factors in this include the patient's physical independence (defined as the physical and/or cognitive ability to fulfill tasks), and self-care management (defined as access to and the ability to use and control devices/resources supporting living in the community regardless of the patient's level of physical ability) [7]. Recent reports have shown that emerging technologies (technical innovations) may significantly and positively influence disabled people's quality of life [8][9][10][11].…”

Section: Integrated It Environments For People With Disabilities: Thementioning

confidence: 99%

Integrated IT environment for people with disabilities: a new concept

Mikołajewska

Mikołajewski²

2014

Open Medicine

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AbstractThis article evaluates the authors’ own concept of integrated IT environments for people with disabilities. Increasing numbers of disabled people and elderly people are affected by shortages of medical specialists and limited funding for medical care. Integrated IT environments for people with disabilities — through integration of various technical and medical solutions into one flexible system — are one way to provide increased independence and improved quality of life for disabled, elderly and severely ill people. The aim of this paper is to assess the extent to which the available possibilities in this area are being utilized, including the authors’ own concept. The implications of technological developments are discussed to lay the groundwork for further research.

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“…Numerous applications have been proven to work with various BCI paradigms such as spelling [7], Internet browsing [8], entertainment [9], environmental control [10], gaming [11][12], neuroprostheses [13], wheelchair control [14] and cognitive rehabilitation [15]. It is evident that BCI can now control a number of applications however little evidence of this is present beyond the laboratory and limited evaluations have been undertaken with participants that would benefit from the use of such a system on a daily basis.…”

Section: Introductionmentioning

confidence: 99%

P300 Brain Computer Interface Control after an Acquired Brain Injury

Daly¹,

Armstrong²,

Thomson³

et al. 2015

IJRITCC

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Abstract-Brain-Computer Interfaces (BCI) are systems that can be controlled by the user through harnessing their brain signals. Extensive research has been undertaken within a laboratory setting with healthy users to illustrate the usability of such systems. To bring these systems to users with severe disabilities it is necessary to develop simple, easy to use systems that can be operated b y non-experts outside of the lab and are evaluated by real end users preferably through a user centered design approach. This paper presents a user centered evaluation of a P300 BCI operated by non-expert users in a rehabilitation center with a control group of f i v e healthy participants w i t h o u t acquired brain injury ( A B I ) and five end users with ABI. Each participant aimed to complete the 30-ste p pr ot ocol three separate ti mes an d rate his or her satis fa cti on fr om 0 to 10 on the Visual Anal ogue S cale after each session. Participants then rated their satisfaction with the BCI on the extende d QUES T 2.0 and a customized usability questionnaire. The results indicated that end-users were able to achieve an average accuracy of 55% compared to the control group that reported an average of 78%. The findings indicated that participants were satisfied with the BCI but felt frustrated when it did not respond to their commands. This work was phase one of three to move the BCI system into end users homes. Key recommendations for advancing the P300 BCI towards an easy to use, home-based system were identified, including reducing the complexity of the setup, ensuring the system becomes more responsive and increasing the overall functionality.

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A Brain-Computer Interface as Input Channel for a Standard Assistive Technology Software

Cited by 134 publications

References 30 publications

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

Integrated IT environment for people with disabilities: a new concept

P300 Brain Computer Interface Control after an Acquired Brain Injury

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