ALS Population Assessment of a Dynamic Stopping Algorithm Implementation for P300 Spellers

Mainsah, Boyla O.; Collins, Leslie M.; Colwell, Kenneth A.; Sellers, Eric W.; Ryan, David B.; Caves, Kevin; Throckmorton, Chandra S.

doi:10.1007/978-3-319-25190-5_8

Cited by 5 publications

(6 citation statements)

References 25 publications

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“…The spelled letter was identified as the intersection between the row and the column exhibiting the maximum of the sum of scored features (Krusienski et al, 2006 ). As mentioned in the Introduction section, the stimulation sequences were not customized for each patient and thus we performed a static data collection (Mainsah et al, 2015 ). Specifically, a single item (e.g., letter) was intensified 20 times (10 sequences) before the next set of stimuli would start.…”

Section: Methodsmentioning

confidence: 99%

On the Relationship Between Attention Processing and P300-Based Brain Computer Interface Control in Amyotrophic Lateral Sclerosis

Riccio

Schettini

Simione

et al. 2018

Front. Hum. Neurosci.

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Our objective was to investigate the capacity to control a P3-based brain-computer interface (BCI) device for communication and its related (temporal) attention processing in a sample of amyotrophic lateral sclerosis (ALS) patients with respect to healthy subjects. The ultimate goal was to corroborate the role of cognitive mechanisms in event-related potential (ERP)-based BCI control in ALS patients. Furthermore, the possible differences in such attentional mechanisms between the two groups were investigated in order to unveil possible alterations associated with the ALS condition. Thirteen ALS patients and 13 healthy volunteers matched for age and years of education underwent a P3-speller BCI task and a rapid serial visual presentation (RSVP) task. The RSVP task was performed by participants in order to screen their temporal pattern of attentional resource allocation, namely: (i) the temporal attentional filtering capacity (scored as T1%); and (ii) the capability to adequately update the attentive filter in the temporal dynamics of the attentional selection (scored as T2%). For the P3-speller BCI task, the online accuracy and information transfer rate (ITR) were obtained. Centroid Latency and Mean Amplitude of N200 and P300 were also obtained. No significant differences emerged between ALS patients and Controls with regards to online accuracy (p = 0.13). Differently, the performance in controlling the P3-speller expressed as ITR values (calculated offline) were compromised in ALS patients (p < 0.05), with a delay in the latency of P3 when processing BCI stimuli as compared with Control group (p < 0.01). Furthermore, the temporal aspect of attentional filtering which was related to BCI control (r = 0.51; p < 0.05) and to the P3 wave amplitude (r = 0.63; p < 0.05) was also altered in ALS patients (p = 0.01). These findings ground the knowledge required to develop sensible classes of BCI specifically designed by taking into account the influence of the cognitive characteristics of the possible candidates in need of a BCI system for communication.

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Section: Methodsmentioning

confidence: 99%

On the Relationship Between Attention Processing and P300-Based Brain Computer Interface Control in Amyotrophic Lateral Sclerosis

Riccio

Schettini

Simione

et al. 2018

Front. Hum. Neurosci.

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“…This algorithm resulted in significant improvements in accuracy and spelling speed for healthy participants. These results were validated in a study with participants with ALS, one of the target populations for P300 spellers [17].…”

Section: Introductionmentioning

confidence: 68%

“…Healthy participants were presented with a 9×8 grid of characters on a computer screen while participants with communication disabilities were presented with a 6×6 grid of characters (see figure 2). These grids match the grids used in Throckmorton et al [16] and Mainsah et al [17] for participants without disability and with ALS, respectively. Both grids were flashed based on the checkerboard paradigm to eliminate character adjacency and double flash errors [20].…”

Section: P300 Speller Paradigmmentioning

confidence: 99%

Applying dynamic data collection to improve dry electrode system performance for a P300-based brain–computer interface

Clements¹,

Sellers²,

Ryan³

et al. 2016

J. Neural Eng.

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Using dry electrodes is desirable for reduced set-up time; however, this study demonstrates that online performance is significantly poorer than for wet electrodes for users with and without disabilities. We test a new application of dynamic stopping algorithms to compensate for poorer SNR. Dynamic stopping improved dry system performance; however, further signal processing efforts are likely necessary for full mitigation.

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“…Locked-in patients typically have little to no voluntary muscle control but retain cognition and awareness [29][30][31][32][33]. Although methods exist to provide basic communicative capabilities to locked-in patients [33][34][35][36] and are associated with increases in patient-reported quality of life [31,32], these approaches often involve tedious and difficult to learn procedures such as selecting characters one at a time at rates less than ten characters per minute (typing rates are typically more than 175 characters per minute in healthy individuals). Development of a device capable of directly interpreting intended speech from neural activity could result in significant improvements to the speed and naturalness of assistive speech technology and, as a result, the quality of life for impaired patients.…”

Section: Discussionmentioning

confidence: 99%

Real-time classification of auditory sentences using evoked cortical activity in humans

Moses¹,

Leonard

Chang

2018

J. Neural Eng.

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ALS Population Assessment of a Dynamic Stopping Algorithm Implementation for P300 Spellers

Cited by 5 publications

References 25 publications

On the Relationship Between Attention Processing and P300-Based Brain Computer Interface Control in Amyotrophic Lateral Sclerosis

On the Relationship Between Attention Processing and P300-Based Brain Computer Interface Control in Amyotrophic Lateral Sclerosis

Applying dynamic data collection to improve dry electrode system performance for a P300-based brain–computer interface

Real-time classification of auditory sentences using evoked cortical activity in humans

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