Preprocessing choices for P3 analyses with mobile EEG: A systematic literature review and interactive exploration DOI Creative Commons
Nadine Jacobsen, Daniel Kristanto,

Suong Welp

et al.

Psychophysiology, Journal Year: 2024, Volume and Issue: 62(1)

Published: Dec. 19, 2024

Preprocessing is necessary to extract meaningful results from electroencephalography (EEG) data. With many possible preprocessing choices, their impact on outcomes fundamental. While previous studies have explored the effects of stationary EEG data, this research delves into mobile EEG, where complex processing address motion artifacts. Specifically, we describe choices reported for analyzing P3 event-related potential (ERP) during walking and standing. A systematic review 258 walking, identified 27 meeting inclusion criteria. Two independent coders extracted in each study. Analysis revealed commonalities differences, such as widespread use offline filters but limited application line noise correction (3 studies). Notably, 59% involved manual steps, 56% omitted reporting critical parameters at least one step. All employed unique strategies. These findings align with results, emphasizing necessity standardized research. We implemented an interactive visualization tool (Shiny app) aid exploration landscape. The app allows users structure literature regarding different enter planned methods, compare them literature. could be utilized examine how these understand robustness various options. hope increase awareness influence decisions advocate comprehensive standards foster reproducibility

Language: Английский

Preprocessing choices for P3 analyses with mobile EEG: A systematic literature review and interactive exploration DOI Creative Commons
Nadine Jacobsen, Daniel Kristanto,

Suong Welp

et al.

Psychophysiology, Journal Year: 2024, Volume and Issue: 62(1)

Published: Dec. 19, 2024

Preprocessing is necessary to extract meaningful results from electroencephalography (EEG) data. With many possible preprocessing choices, their impact on outcomes fundamental. While previous studies have explored the effects of stationary EEG data, this research delves into mobile EEG, where complex processing address motion artifacts. Specifically, we describe choices reported for analyzing P3 event-related potential (ERP) during walking and standing. A systematic review 258 walking, identified 27 meeting inclusion criteria. Two independent coders extracted in each study. Analysis revealed commonalities differences, such as widespread use offline filters but limited application line noise correction (3 studies). Notably, 59% involved manual steps, 56% omitted reporting critical parameters at least one step. All employed unique strategies. These findings align with results, emphasizing necessity standardized research. We implemented an interactive visualization tool (Shiny app) aid exploration landscape. The app allows users structure literature regarding different enter planned methods, compare them literature. could be utilized examine how these understand robustness various options. hope increase awareness influence decisions advocate comprehensive standards foster reproducibility

Language: Английский

Citations

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