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Development of a Method to Compensate for Signal Quality Variations in Repeated Auditory Event-Related Potential Recordings
Reliable measurements are mandatory in clinically relevant auditory event-related potential (AERP)-based tools and applications. The comparability of the results gets worse as a result of variations in the remaining measurement error. A potential method is studied that allows optimization of the len...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Frontiers Research Foundation
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2856627/ https://www.ncbi.nlm.nih.gov/pubmed/20407635 http://dx.doi.org/10.3389/fneng.2010.00002 |
Sumario: | Reliable measurements are mandatory in clinically relevant auditory event-related potential (AERP)-based tools and applications. The comparability of the results gets worse as a result of variations in the remaining measurement error. A potential method is studied that allows optimization of the length of the recording session according to the concurrent quality of the recorded data. In this way, the sufficiency of the trials can be better guaranteed, which enables control of the remaining measurement error. The suggested method is based on monitoring the signal-to-noise ratio (SNR) and remaining measurement error which are compared to predefined threshold values. The SNR test is well defined, but the criterion for the measurement error test still requires further empirical testing in practice. According to the results, the reproducibility of average AERPs in repeated experiments is improved in comparison to a case where the number of recorded trials is constant. The test-retest reliability is not significantly changed on average but the between-subject variation in the value is reduced by 33–35%. The optimization of the number of trials also prevents excessive recordings which might be of practical interest especially in the clinical context. The efficiency of the method may be further increased by implementing online tools that improve data consistency. |
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