matlab version 2022a Search Results


machine learning toolbox 12 3  (MathWorks Inc)
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eeg data in matlab  (MathWorks Inc)
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MathWorks Inc eeg data in matlab
Fig. 1. Schematic overview of the alignment between electroencephalography <t>(EEG)</t> responses and <t>the</t> <t>phonetic</t> transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.
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MathWorks Inc matlab matlab
Fig. 1. Schematic overview of the alignment between electroencephalography <t>(EEG)</t> responses and <t>the</t> <t>phonetic</t> transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.
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matlab simbiology app  (MathWorks Inc)
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MathWorks Inc matlab simbiology app
Fig. 1. Schematic overview of the alignment between electroencephalography <t>(EEG)</t> responses and <t>the</t> <t>phonetic</t> transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.
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co optimization  (MathWorks Inc)
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MathWorks Inc co optimization
Fig. 1. Schematic overview of the alignment between electroencephalography <t>(EEG)</t> responses and <t>the</t> <t>phonetic</t> transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.
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r/rstudio (version 2022.07.2  (RStudio)
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Fig. 1. Schematic overview of the alignment between electroencephalography <t>(EEG)</t> responses and <t>the</t> <t>phonetic</t> transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.
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musculoskeletal model  (OpenSim Ltd)
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OpenSim Ltd musculoskeletal model
Fig. 1. Schematic overview of the alignment between electroencephalography <t>(EEG)</t> responses and <t>the</t> <t>phonetic</t> transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.
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psychophysics toolbox version 3  (MathWorks Inc)
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Fig. 1. Schematic overview of the alignment between electroencephalography <t>(EEG)</t> responses and <t>the</t> <t>phonetic</t> transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.
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originpro  (OriginLab corp)
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OriginLab corp originpro
Fig. 1. Schematic overview of the alignment between electroencephalography <t>(EEG)</t> responses and <t>the</t> <t>phonetic</t> transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.
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statistical parametric mapping  (MathWorks Inc)
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MathWorks Inc statistical parametric mapping
Fig. 1. Schematic overview of the alignment between electroencephalography <t>(EEG)</t> responses and <t>the</t> <t>phonetic</t> transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.
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Image Search Results


Fig. 1. Schematic overview of the alignment between electroencephalography (EEG) responses and the phonetic transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.

Journal: Hearing research

Article Title: Phoneme-related potentials recorded from normal hearing listeners and cochlear implant users in a selective attention paradigm to continuous speech.

doi: 10.1016/j.heares.2024.109136

Figure Lengend Snippet: Fig. 1. Schematic overview of the alignment between electroencephalography (EEG) responses and the phonetic transcriptions, followed by the extraction of phoneme-related potentials (PRPs). Two audio files were presented simulta- neously: One to-be attended (blue) and one to-be unattended (red). The text of the audio files was phonetically transcribed. The EEG responses and the pho- netic transcriptions were temporally aligned so that the onset of each phoneme was marked in the EEG. The EEG was segmented into trials containing indi- vidual phonemes, with each phoneme onset occurring at a trial latency of 0 ms. The time average of trials containing the same phoneme was calculated and represents the PRP.

Article Snippet: The phonetic transcriptions were temporally aligned with the EEG data in Matlab (The MathWorks, Inc., Natick, Massachusetts, version 2022a) using the EEGLAB toolbox (Delorme and Makeig, 2004, version 2020_0).

Techniques: Extraction