A brain–computer interface tool to assess cognitive functions in completely paralyzed patients with amyotrophic lateral sclerosis

Iversen, Iver H.; Ghanayim, Nimr; Kübler, Andrea; Neumann, Nicola; Birbaumer, Niels; Kaiser, Jochen

doi:10.1016/j.clinph.2008.07.001

Cited by 67 publications

(54 citation statements)

References 33 publications

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“…Non-invasive BCI methods have been utilized more extensively than invasive methods for people with disabilities (Birbaumer & Cohen, 2007;Birbaumer et al, 2008;Gerven et al, 2009): unfortunately, whereas PALS and other patients in "locked-in" conditions have motivated research in this area, very few systems have been successfully used -such as that reported by Townsend and co-workers (2010). It has been postulated that some forms of cognitive impairment and changes in EEG signatures in late ALS stages may contribute to the lack of success using BCI technology (Iversen et al, 2008), as the technology was introduced after the participants had become "locked-in" (Gerven et al, 2009;Münte et al, 1998): really, the most successful application for communication has occurred in people at the beginning stages of ALS (Birbaumer et al, 1999;Birbaumer, 2006;Kubler et al, 2001). Nowadays, AAC acceptance and use represent two areas of interest for physicians and scientists.…”

Section: Treatment Of Impaired Communicationmentioning

confidence: 99%

Communication Impairment in ALS Patients Assessment and Treatment

Bongioanni¹

2012

Amyotrophic Lateral Sclerosis

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Section: Treatment Of Impaired Communicationmentioning

confidence: 99%

Communication Impairment in ALS Patients Assessment and Treatment

Bongioanni¹

2012

Amyotrophic Lateral Sclerosis

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“…The corresponding distinguishable features in the EEG signals can be used to design MI-based BCI systems [24][25][26][27][28][29][30]. Many BCI studies have reported good offline results with high accuracies.…”

Section: Introductionmentioning

confidence: 99%

“…Commonly used EEG signals include the event-related P300 potentials [14][15][16][17][18], steady-state visual evoked potentials (SSVEPs) [19][20][21][22][23], and the motor imagery (MI)-related rhythms [24][25][26][27][28][29][30]. In these, the P300 potentials and SSVEPs are evoked by external stimuli and the MI rhythms are voluntarily modulated by the subjects.…”

Section: Introductionmentioning

confidence: 99%

Real-time brain computer interface using imaginary movements

El-Madani

Sørensen

Kjær

et al. 2015

EPJ Nonlinear Biomed Phys

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Background: Brain Computer Interface (BCI) is the method of transforming mental thoughts and imagination into actions. A real-time BCI system can improve the quality of life of patients with severe neuromuscular disorders by enabling them to communicate with the outside world. In this paper, the implementation of a 2-class real-time BCI system based on the event related desynchronization (ERD) of the sensorimotor rhythms (SMR) is described. Methods: Off-line measurements were conducted on 12 healthy test subjects with 3 different feedback systems (cross, basket and bars). From the collected electroencephalogram (EEG) data, the optimum frequency bands for each of the subjects were determined first through an exhaustive search on 325 bandpass filters. The features were then extracted for the left and right hand imaginary movements using the Common Spatial Pattern (CSP) method. Subsequently, a Bayes linear classifier (BLC) was developed and used for signal classification. These three subject-specific settings were preserved for the on-line experiments with the same feedback systems. Results: Six of the 12 subjects were qualified for the on-line experiments based on their high off-line classification accuracies (CAs > 75 %). The overall mean on-line accuracy was found to be 80%. Conclusions:The subject-specific settings applied on the feedback systems have resulted in the development of a successful real-time BCI system with high accuracies.

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“…Conversely, other wireless EEG designs combine both stimulus player and EEG headset with synchronization [25,26]. In [22], the latter attempt, specific clinical hardware for stimulation with a specific SYN port was used (PS33-PLUS, by Grass Technologies); although in terms of usability, we would expect wireless EEG headsets to permit users to use their own stimulus players without addition of extra synchronization hardware.…”

Section: Introductionmentioning

confidence: 99%

“…They are standalone solutions that do not integrate a stimulus player. Then, they are not meant to execute ERP paradigms but are suitable for others in which stimulation is not needed (e.g., self-regulation of low frequency cerebral rhythms [22], alpha band modulation [23] or steady-state EEG responses [24]). Conversely, other wireless EEG designs combine both stimulus player and EEG headset with synchronization [25,26].…”

Section: Introductionmentioning

confidence: 99%

A proposal for bio-synchronized transmission of EEG/ERP data

López-Gordo

Padilla

Valle

2016

J Wireless Com Network

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Acquisition of event-related potentials (ERPs) requires a nearly perfect synchronization between the stimulus player and the EEG acquisition unit that clinical systems implement at hardware level by means of a wired link. Out of clinical context, current brain-computer interface technology offers wireless and wearable EEG headsets that provide ubiquitous EEG acquisition. However, they are not adequate for ERPs acquisition since they lack the physical wire with the stimulus player. In this paper, we propose a novel technique devoted to provide a solution to this problem by means of a bio-synchronization approach. This technique adds to the stimulus data, a tagged audio preamble for synchronization (TAP-S) that embeds a synchronization mechanism in its physiological response based on pseudo random sequences. In this way, the EEG data elicited by the preamble and the stimulus are recorded together and the stimulus onset can be directly extracted from the EEG data by preamble detection. TAP-S is tailored to work with any low-cost multimedia player and wireless EEG headsets. Our preliminary results reveal TAP-S as a first, promising, and low-cost approach that, after further improvement, could enable remote processing of ERPs with wireless acquisition with application in telemedicine, ambient assisted living, or brain-computer interfaces.

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A brain–computer interface tool to assess cognitive functions in completely paralyzed patients with amyotrophic lateral sclerosis

Cited by 67 publications

References 33 publications

Communication Impairment in ALS Patients Assessment and Treatment

Communication Impairment in ALS Patients Assessment and Treatment

Real-time brain computer interface using imaginary movements

A proposal for bio-synchronized transmission of EEG/ERP data

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