Related Experiment Video
Updated: Jun 5, 2026

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
Published on: September 8, 2023
Improving P300 morphology through single-trial latency realignment: a comparative study of template-matching
Ilaria Quattrociocchi1,2, Valentina Caracci1,2, Emanuela Rotondo1,2
1Department of Computer, Control and Management Engineering, Sapienza University of Rome, Rome, Italy.
None:
Objective.Trial-to-trial latency variability-well known as latency jitter-is a major source of distortion in event-related potential (ERP) analysis, particularly for late cognitive components such as the P300. Several template-matching algorithms have been proposed to estimate single-trial latency and improve ERP reconstruction, but direct comparisons across different methodological approaches remain limited. This study provides a structured evaluation of three representative algorithms: the woody filter (WF), operating in the time domain; the adaptive wavelet filter (CWT-AWF), extending template matching to the time-frequency domain; and ReSync, a decomposition-based method that combines signal decomposition with time-restricted realignment.Approach.The algorithms were evaluated using surrogate EEG-like data with controlled amplitude ratios (reported as SNR) and known latency jitter, and real EEG recordings from healthy participants performing an auditory oddball task. Performance was assessed in terms of latency-estimation accuracy, latency variability, ERP morphology, and waveform quality.Main Results.Across simulated conditions, ReSync achieved significantly lower latency-estimation errors and reduced variability compared to WF and CWT-AWF, demonstrating robustness even at low SNR levels. Importantly, this advantage persisted when all methods were constrained within the same temporal window, indicating that performance gains are not solely attributable to time restriction. In real EEG data, all algorithms enhanced P300 morphology relative to non-aligned averages, but ReSync yielded the most consistent improvements, including the lowest latency jitter and stable latency distributions within a range consistent with previous findings. Complementary SNR analysis further indicated improved waveform quality when interpreted jointly with latency-based metrics. ReSync also remained stable across both single-channel and multi-channel realignment strategies.Significance.These findings highlight the advantage of combining decomposition and targeted realignment for mitigating ERP latency jitter. ReSync provides a reliable and morphology-preserving framework for single-trial ERP analysis, with potential applications in cognitive neuroscience, brain-computer interfaces, and clinical contexts.

