Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Microplastic pollution in marine sediments of the Antarctic coastal environment of Potter Cove and nearby areas (25 de Mayo/King George Island, South Shetlands).

Marine pollution bulletin·2024

Same author

Neoadjuvant letrozole and palbociclib in patients with HR-positive/HER2-negative early breast cancer and Oncotype DX Recurrence Score ≥18: DxCARTES study.

ESMO open·2024

Same author

First-line therapy with palbociclib in patients with advanced HR<sup>+</sup>/HER2<sup>-</sup> breast cancer: The real-life study PALBOSPAIN.

Breast cancer research and treatment·2024

Same author

Microplastic pollution in waters of the Antarctic coastal environment of Potter Cove (25 de Mayo Island/King George Island, South Shetlands).

The Science of the total environment·2024

Same author

Effect of bimatoprost sustained-release intracameral implant on intraocular pressure and medication burden in patients with prior glaucoma surgery.

Journal francais d'ophtalmologie·2023

Same author

Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities.

NeuroImage·2023

Same journal

Segmentation of the parasagittal dura mater on multi-center 3D-FLAIR MRI.

NeuroImage·2026

Same journal

Spatial frequency channels implement a mental ruler in spatial vision.

NeuroImage·2026

Same journal

Exploring the Link Between Intravoxel Incoherent Motion Measured Brain Diffusivity During Wakefulness and Sleep Macrostructure in the Elderly.

NeuroImage·2026

Same journal

Closed-loop adaptation of transcranial magnetic stimulation intensity with electroencephalography feedback.

NeuroImage·2026

Same journal

Volumetric postmortem MRI of the medial temporal lobe in Alzheimer's disease and related disorders: methodological advances and implications for in vivo biomarker development.

NeuroImage·2026

Same journal

Neural responses to equity and inequity when receiving vicarious rewards for self and charity during adolescence.

NeuroImage·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 5, 2025

High Density Event-related Potential Data Acquisition in Cognitive Neuroscience

High Density Event-related Potential Data Acquisition in Cognitive Neuroscience

Published on: April 16, 2010

HAPPILEE: HAPPE In Low Electrode Electroencephalography, a standardized pre-processing software for lower density

K L Lopez¹, A D Monachino¹, S Morales²

¹Northeastern University, 360 Huntington Ave, Boston, MA, United States.

|July 11, 2022

Summary

This summary is machine-generated.

A new automated pipeline, HAPPILEE, standardizes Electroencephalography (EEG) data processing for low-density recordings. This tool enhances analysis of brain function across diverse research and clinical settings.

Keywords:

Automated pre-processing Electroencephalography HAPPILEE Low-density EEG Processing pipeline

More Related Videos

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources

Published on: November 26, 2016

Cortical Source Analysis of High-Density EEG Recordings in Children

Cortical Source Analysis of High-Density EEG Recordings in Children

Published on: June 30, 2014

Related Experiment Videos

Last Updated: Sep 5, 2025

High Density Event-related Potential Data Acquisition in Cognitive Neuroscience

High Density Event-related Potential Data Acquisition in Cognitive Neuroscience

Published on: April 16, 2010

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources

Published on: November 26, 2016

Cortical Source Analysis of High-Density EEG Recordings in Children

Cortical Source Analysis of High-Density EEG Recordings in Children

Published on: June 30, 2014

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Lower-density Electroencephalography (EEG) is widely used in research and clinical settings.
Existing automated EEG pre-processing pipelines primarily cater to high-density systems, leaving a gap for lower-density data.
Lower-density EEG often involves long recordings and large sample sizes, necessitating efficient and standardized processing methods.

Purpose of the Study:

To introduce the HAPPE In Low Electrode Electroencephalography (HAPPILEE) pipeline, a novel automated solution for processing low-density EEG data.
To provide a standardized and optimized pipeline for various EEG recording types, including task-free and task-related data.
To facilitate reproducible research and clinical practice by ensuring consistent data quality and processing.

Main Methods:

HAPPILEE is a standardized, automated pipeline designed for EEG recordings with channel layouts from 1 to approximately 32 electrodes.
The pipeline integrates multiple processing steps: filtering, line noise reduction, bad channel detection, artifact correction, segmentation, and bad segment rejection, all optimized for low-density data.
It interfaces with the HAPPE+ER pipeline for event-related potential data and includes post-processing reports on data and pipeline quality metrics.

Main Results:

The HAPPILEE pipeline has been optimized using both recorded and simulated low-density EEG data.
Performance comparisons demonstrate HAPPILEE's effectiveness against other artifact correction and rejection strategies.
The pipeline ensures standardized processing, facilitating evaluation and reporting of data quality.

Conclusions:

HAPPILEE addresses the need for standardized, automated pre-processing of low-density EEG data.
The pipeline offers a robust solution for analyzing diverse EEG datasets, improving efficiency and reproducibility.
HAPPILEE is freely available as part of HAPPE 2.0 software, promoting wider adoption in the scientific community.