Benchmarking of Averaging Methods Using Realistic Simulation of Evoked Potentials
Título del documento: Benchmarking of Averaging Methods Using Realistic Simulation of Evoked Potentials
Revista: Computación y sistemas
Base de datos:
Número de sistema: 000607865
ISSN: 1405-5546
Autores: 1
2
3
1
1
Instituciones: 1Universidad Central Marta Abreu de las Villas, Informatics Research Center, Santa Clara, Villa Clara. Cuba
2Universidad Católica del Maule, Facultad de Medicina, Talca, Maule. Chile
3Hospital Manuel Piti Fajardo, Departamento de Electromedicina, Santa Clara. Cuba
Año:
Periodo: Ene-Mar
Volumen: 28
Número: 1
Paginación: 211-219
País: México
Idioma: Inglés
Resumen en inglés The objective of this research is to conduct a comparative evaluation of various averaging methods for estimating evoked potentials using realistic simulations. Simulated signals are commonly employed to assess pattern recognition algorithms for event-related potential estimation since obtaining gold standard records is challenging. The simulations used are considered realistic because they allow for variations in potential latency, component width, and amplitudes. Background noise is simulated using an 8th order Burg autoregressive model derived from the analysis of a real dataset of auditory evoked potentials. The simulations incorporate actual instrumentation and acquisition channel effects, as well as power line interference. Three averaging methods for estimating the evoked potential waveform are compared: classical consistent average, weighted average, and reported average. The comparisons are conducted in two scenarios: one without artifacts and the other with 20% contamination by artifacts. The results of the comparative evaluation indicate that the trimmed average offers the best trade-off between the estimated signal-to-noise ratio (SNR) value and bias.
Keyword: Evoked Potentials,
Averaging methods,
Realistic simulation,
Benchmarking,
SNR,
Bias
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