Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

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

Enhancing mobile brain and body imaging: Open-source solutions for real-world research applications.

iScience·2026
Same author

A portable solution for simultaneous human movement and mobile EEG acquisition: readiness potential for basketball free-throw shooting.

Experimental brain research·2026
Same author

Exploring fNIRS-guided neurofeedback for supplementary motor area training in Parkinson's disease and healthy older adults.

NPJ Parkinson's disease·2026
Same author

The effects of dual-tasking while walking naturally and on a treadmill.

Acta psychologica·2026
Same author

Disentangling the functional roles of pre-stimulus oscillations in crossmodal associative memory formation via sensory entrainment.

Scientific reports·2026
Same author

Evaluation of Pre-Applied Conductive Materials in Electrode Grids for Longterm EEG Recording.

Sensors (Basel, Switzerland)·2025

Related Experiment Video

Updated: Aug 13, 2025

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

43.4K

Outdoor walking: Mobile EEG dataset from walking during oddball task and walking synchronization task.

Joanna E M Scanlon1,2, Nadine S J Jacobsen1, Marike C Maack1

  • 1Neuropsychology Lab, Department of Psychology, University of Oldenburg, Germany.

Data in Brief
|January 23, 2023
PubMed
Summary

This study collected data on attention and walking using foot accelerometers and electroencephalography (EEG) during standing and walking tasks. The dataset explores brain activity during various walking conditions, including synchronization with another person.

Keywords:
AttentionGaitInterpersonal synchronizationMobile EEGSocial neuroscienceWalking

More Related Videos

Measuring the Switch Cost of Smartphone Use While Walking
07:00

Measuring the Switch Cost of Smartphone Use While Walking

Published on: April 30, 2020

1.9K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.5K

Related Experiment Videos

Last Updated: Aug 13, 2025

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

43.4K
Measuring the Switch Cost of Smartphone Use While Walking
07:00

Measuring the Switch Cost of Smartphone Use While Walking

Published on: April 30, 2020

1.9K
A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
11:06

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Published on: April 12, 2016

10.5K

Area of Science:

  • Neuroscience
  • Biomechanics
  • Human-Computer Interaction

Background:

  • Understanding brain activity during locomotion is crucial for gait analysis and rehabilitation.
  • Investigating the impact of social interaction and environmental factors on walking behavior is an emerging area of research.
  • The use of electroencephalography (EEG) and accelerometry provides a multi-modal approach to capture neural and kinematic data during movement.

Purpose of the Study:

  • To present a comprehensive dataset of electroencephalography (EEG) and foot accelerometer data collected during standing and various walking tasks.
  • To investigate neural correlates of attention, walking, and social interaction during locomotion.
  • To provide data for research in areas such as attention, gait analysis, and social neuroscience.

Main Methods:

  • 18 participants performed standing and outdoor walking tasks twice on separate days.
  • Data collection involved foot accelerometers and two electroencephalography (EEG) system configurations (active and passive electrodes).
  • Tasks included eyes open/closed, auditory oddball, and walking with/without an experimenter, including a step synchronization task.

Main Results:

  • The dataset captures neural and kinematic data across diverse walking conditions, including solitary walking and synchronized walking with a partner.
  • Different EEG electrode configurations (active vs. passive) were employed, allowing for comparisons in data quality and utility.
  • The data supports investigations into attentional processes, motor control during gait, and neural underpinnings of social walking behaviors.

Conclusions:

  • This dataset offers valuable insights into the neural and biomechanical aspects of human locomotion.
  • It facilitates research on attention, walking mechanisms, and social neuroscience, particularly in the context of interactive walking.
  • The multi-modal data collected can be leveraged for developing advanced human-gait interaction models and assistive technologies.