TY - JOUR
T1 - Data Descriptor
T2 - Full body mobile brain-body imaging data during unconstrained locomotion on stairs, ramps, and level ground
AU - Brantley, Justin A.
AU - Luu, Trieu Phat
AU - Nakagome, Sho
AU - Zhu, Fangshi
AU - Contreras-Vidal, Jose L.
N1 - Funding Information:
This research is partly supported by NSF award IIS-1302339 and an NIH F99 Predoctoral Fellowship (1F99NS105210-01) to JAB. The authors would like to acknowledge Dr. Beom-Chan Lee for generously sharing the Xsens MVN system along with the Center for Neuromotor and Biomechanics Research (CNBR) for permitting use of other equipment and space. We also would like to thank Dr. Recep A Ozdemir for his assistance in data collection.
Publisher Copyright:
© The Author(s) 2018.
PY - 2018/7/10
Y1 - 2018/7/10
N2 - Human locomotion is a complex process that requires the integration of central and peripheral nervous signalling. Understanding the brain's involvement in locomotion is challenging and is traditionally investigated during locomotor imagination or observation. However, stationary imaging methods lack the ability to infer information about the peripheral and central signalling during actual task execution. In this report, we present a dataset containing simultaneously recorded electroencephalography (EEG), lower-limb electromyography (EMG), and full body motion capture recorded from ten able-bodied individuals. The subjects completed an average of twenty trials on an experimental gait course containing level-ground, ramps, and stairs. We recorded 60-channel EEG from the scalp and 4-channel EOG from the face and temples. Surface EMG was recorded from six muscle sites bilaterally on the thigh and shank. The motion capture system consisted of seventeen wireless IMUs, allowing for unconstrained ambulation in the experimental space. In this report, we present the rationale for collecting these data, a detailed explanation of the experimental setup, and a brief validation of the data quality.
AB - Human locomotion is a complex process that requires the integration of central and peripheral nervous signalling. Understanding the brain's involvement in locomotion is challenging and is traditionally investigated during locomotor imagination or observation. However, stationary imaging methods lack the ability to infer information about the peripheral and central signalling during actual task execution. In this report, we present a dataset containing simultaneously recorded electroencephalography (EEG), lower-limb electromyography (EMG), and full body motion capture recorded from ten able-bodied individuals. The subjects completed an average of twenty trials on an experimental gait course containing level-ground, ramps, and stairs. We recorded 60-channel EEG from the scalp and 4-channel EOG from the face and temples. Surface EMG was recorded from six muscle sites bilaterally on the thigh and shank. The motion capture system consisted of seventeen wireless IMUs, allowing for unconstrained ambulation in the experimental space. In this report, we present the rationale for collecting these data, a detailed explanation of the experimental setup, and a brief validation of the data quality.
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U2 - 10.1038/sdata.2018.133
DO - 10.1038/sdata.2018.133
M3 - Article
C2 - 29989591
AN - SCOPUS:85049808286
VL - 5
JO - Scientific Data
JF - Scientific Data
SN - 2052-4463
M1 - 180133
ER -