A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric Vision

Abstract In this manuscript, we describe a unique dataset of human locomotion captured in a variety of out-of-the-laboratory environments captured using Inertial Measurement Unit (IMU) based wearable motion capture. The data contain full-body kinematics for walking, with and without stops, stair amb...

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Main Authors: Abhishek Sharma, Vijeth Rai, Melissa Calvert, Zhongyi Dai, Zhenghao Guo, David Boe, Eric Rombokas
Format: Article
Language:English
Published: Nature Portfolio 2023-01-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-023-01932-7
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author Abhishek Sharma
Vijeth Rai
Melissa Calvert
Zhongyi Dai
Zhenghao Guo
David Boe
Eric Rombokas
author_facet Abhishek Sharma
Vijeth Rai
Melissa Calvert
Zhongyi Dai
Zhenghao Guo
David Boe
Eric Rombokas
author_sort Abhishek Sharma
collection DOAJ
description Abstract In this manuscript, we describe a unique dataset of human locomotion captured in a variety of out-of-the-laboratory environments captured using Inertial Measurement Unit (IMU) based wearable motion capture. The data contain full-body kinematics for walking, with and without stops, stair ambulation, obstacle course navigation, dynamic movements intended to test agility, and negotiating common obstacles in public spaces such as chairs. The dataset contains 24.2 total hours of movement data from a college student population with an approximately equal split of males to females. In addition, for one of the activities, we captured the egocentric field of view and gaze of the subjects using an eye tracker. Finally, we provide some examples of applications using the dataset and discuss how it might open possibilities for new studies in human gait analysis.
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spelling doaj.art-76b503fce1f942dd808235fa4ae163fc2023-01-15T12:04:07ZengNature PortfolioScientific Data2052-44632023-01-0110111110.1038/s41597-023-01932-7A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric VisionAbhishek Sharma0Vijeth Rai1Melissa Calvert2Zhongyi Dai3Zhenghao Guo4David Boe5Eric Rombokas6Mechanical Engineering, University of WashingtonElectrical and Computer Engineering, University of WashingtonElectrical Engineering and Computer Science, Massachusetts Institute of TechnologyElectrical and Computer Engineering, University of WashingtonElectrical and Computer Engineering, University of WashingtonMechanical Engineering, University of WashingtonMechanical Engineering, University of WashingtonAbstract In this manuscript, we describe a unique dataset of human locomotion captured in a variety of out-of-the-laboratory environments captured using Inertial Measurement Unit (IMU) based wearable motion capture. The data contain full-body kinematics for walking, with and without stops, stair ambulation, obstacle course navigation, dynamic movements intended to test agility, and negotiating common obstacles in public spaces such as chairs. The dataset contains 24.2 total hours of movement data from a college student population with an approximately equal split of males to females. In addition, for one of the activities, we captured the egocentric field of view and gaze of the subjects using an eye tracker. Finally, we provide some examples of applications using the dataset and discuss how it might open possibilities for new studies in human gait analysis.https://doi.org/10.1038/s41597-023-01932-7
spellingShingle Abhishek Sharma
Vijeth Rai
Melissa Calvert
Zhongyi Dai
Zhenghao Guo
David Boe
Eric Rombokas
A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric Vision
Scientific Data
title A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric Vision
title_full A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric Vision
title_fullStr A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric Vision
title_full_unstemmed A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric Vision
title_short A Non-Laboratory Gait Dataset of Full Body Kinematics and Egocentric Vision
title_sort non laboratory gait dataset of full body kinematics and egocentric vision
url https://doi.org/10.1038/s41597-023-01932-7
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