ArticleBrain computer interfaces (Abingdon, England)2016
Probabilistic Simulation Framework for EEG-Based BCI Design.
Article in Brain computer interfaces (Abingdon, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Feedback Related Potentials for EEG-Based Typing Systems.Frontiers in human neuroscience · 2021Article
- An Event-Driven AR-Process Model for EEG-Based BCIs With Rapid Trial Sequences.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2019Article
- Optimal Query Selection Using Multi-Armed Bandits.IEEE signal processing letters · 2018Article
- On Analysis of Active Querying for Recursive State Estimation.IEEE signal processing letters · 2018Article
- An Active RBSE Framework to Generate Optimal Stimulus Sequences in a BCI for Spelling.IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society · 2017Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
A simulation framework could decrease the burden of attending long and tiring experimental sessions on the potential users of brain computer interface (BCI) systems. Specifically during the initial design of a BCI, a simulation framework that could replicate the operational performance of the system would be a useful tool for designers to make design choices. In this manuscript, we develop a Monte Carlo based probabilistic simulation framework for electroencephalography (EEG) based BCI design. We employ one event related potential (ERP) based typing and one steady state evoked potential (SSVEP) based control interface as testbeds. We compare the results of simulations with real time experiments. Even though over and under estimation of the performance is possible, the statistical results over the Monte Carlo simulations show that the developed framework generally provides a good approximation of the real time system performance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.