Evidence map›Paper›PMID 33594631›Full record

ArticleMedical & biological engineering & computing2021

EEG-based hybrid QWERTY mental speller with high information transfer rate.

Er Akshay Katyal, Rajesh Singla

Abstract read
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In one paragraph

Article in Medical & biological engineering & computing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Er Akshay KatyalICE Department, Dr B.R. Ambedkar N.I.T. Jalandhar, GT Road Bye-Pass, Jalandhar, Punjab, 144011, India. akshay.katyal85@gmail.com.
Rajesh SinglaICE Department, Dr B.R. Ambedkar N.I.T. Jalandhar, GT Road Bye-Pass, Jalandhar, Punjab, 144011, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBrain-computer interface (BCI) spellers detect variations in brain waves to help subjects communicate with the world. This study introduces a P300-SSVEP hybrid BCI-based QWERTY speller.

methodsThe proposed hybrid speller, combines SSVEP and P300 features using a hybrid paradigm. P300 was used as time division multiplexing index which results in the use of lesser number of assumed frequencies for SSVEP elicitation. Each flickering frequency was also assigned a unique colour, to enhance system accuracy.

resultsOn the basis of 20 subjects, an average accuracy of classification of 96.42% and a mean information transfer rate (ITR) of 131.0 bits per min. (BPM) was achieved during the free spelling trial (trial-F). COMPARISON: The t test results revealed that the hybrid QWERTY speller performed significantly better (on the basis of mean classification accuracy and ITR) as compared to the traditional P300 speller) and the QWERTY SSVEP speller. Also, the amount of time taken to spell a word was significantly lesser in the case of hybrid QWERTY speller in contrast to traditional P300 speller while it was almost the same as compared to QWERTY SSVEP speller.

conclusionQWERTY speller outperformed the stereotypical P300 speller as well as QWERTY SSVEP speller.

Indexed as

Brain-Computer InterfacesElectroencephalographyEvent-Related Potentials, P300Evoked Potentials, VisualHumansSeizuresBCIITRP300SpellerSSVEP

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Registered trials

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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.