2019 IEEE International Conference on Engineering Veracruz (ICEV) 2019
DOI: 10.1109/icev.2019.8920815
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EOG-based interface and speech recognition for wheelchair control

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Cited by 3 publications
(3 citation statements)
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“…The functioning of the circuit has been verified by its ability to produce clear signals with minimal distortions. The amplitude values in Figures 9,10,11,12,13,14,15,16,17,18,19,20 and 21 are consistent with that of the EOG signals, thus proving that all applied electrode positions are active sites of signal acquisition that can be used as inputs in biomedical applications. Furthermore, it can be confirmed that the signals are indeed EOG signals due to the similarity in waveform shape to that of a general EOG signal [6,14].…”
Section: Discussionsupporting
confidence: 63%
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“…The functioning of the circuit has been verified by its ability to produce clear signals with minimal distortions. The amplitude values in Figures 9,10,11,12,13,14,15,16,17,18,19,20 and 21 are consistent with that of the EOG signals, thus proving that all applied electrode positions are active sites of signal acquisition that can be used as inputs in biomedical applications. Furthermore, it can be confirmed that the signals are indeed EOG signals due to the similarity in waveform shape to that of a general EOG signal [6,14].…”
Section: Discussionsupporting
confidence: 63%
“…Each of these values is represented by a different color. Figures 9,10,11,12,13,14,15,16,17,18,19,20 and 21 show the peak-to-peak voltage data obtained for all seven subjects for all electrode positions. Each of these values is in volts and represents the peak-to-peak amplitude of the EOG signal.…”
Section: Resultsmentioning
confidence: 99%
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