Cargando…

Multimodal Data for the Detection of Freezing of Gait in Parkinson’s Disease

Freezing of gaits (FOG) is a very disabling symptom of Parkinson’s Disease (PD), affecting about 50% of PD patients and 80% of advanced PD patients. Studies have shown that FOG is related to a complex interplay between motor, cognitive and affective factors. A full characterization of FOG is crucial...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Wei, Yang, Zhuokun, Li, Hantao, Huang, Debin, Wang, Lipeng, Wei, Yanzhao, Zhang, Lei, Ma, Lin, Feng, Huanhuan, Pan, Jing, Guo, Yuzhu, Chan, Piu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9546845/
https://www.ncbi.nlm.nih.gov/pubmed/36207427
http://dx.doi.org/10.1038/s41597-022-01713-8
_version_ 1784805135175647232
author Zhang, Wei
Yang, Zhuokun
Li, Hantao
Huang, Debin
Wang, Lipeng
Wei, Yanzhao
Zhang, Lei
Ma, Lin
Feng, Huanhuan
Pan, Jing
Guo, Yuzhu
Chan, Piu
author_facet Zhang, Wei
Yang, Zhuokun
Li, Hantao
Huang, Debin
Wang, Lipeng
Wei, Yanzhao
Zhang, Lei
Ma, Lin
Feng, Huanhuan
Pan, Jing
Guo, Yuzhu
Chan, Piu
author_sort Zhang, Wei
collection PubMed
description Freezing of gaits (FOG) is a very disabling symptom of Parkinson’s Disease (PD), affecting about 50% of PD patients and 80% of advanced PD patients. Studies have shown that FOG is related to a complex interplay between motor, cognitive and affective factors. A full characterization of FOG is crucial for FOG detection/prediction and prompt intervention. A protocol has been designed to acquire multimodal physical and physiological information during FOG, including gait acceleration (ACC), electroencephalogram (EEG), electromyogram (EMG), and skin conductance (SC). Two tasks were designed to trigger FOG, including gait initiation failure and FOG during walking. A total number of 12 PD patients completed the experiments and produced a length of 3 hours and 42 minutes of valid data including 2 hours and 14 minutes of normal gait and 1 hour and 28 minutes of freezing of gait. The FOG episodes were labeled by two qualified physicians. The multimodal data have been validated by a FOG detection task.
format Online
Article
Text
id pubmed-9546845
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-95468452022-10-09 Multimodal Data for the Detection of Freezing of Gait in Parkinson’s Disease Zhang, Wei Yang, Zhuokun Li, Hantao Huang, Debin Wang, Lipeng Wei, Yanzhao Zhang, Lei Ma, Lin Feng, Huanhuan Pan, Jing Guo, Yuzhu Chan, Piu Sci Data Data Descriptor Freezing of gaits (FOG) is a very disabling symptom of Parkinson’s Disease (PD), affecting about 50% of PD patients and 80% of advanced PD patients. Studies have shown that FOG is related to a complex interplay between motor, cognitive and affective factors. A full characterization of FOG is crucial for FOG detection/prediction and prompt intervention. A protocol has been designed to acquire multimodal physical and physiological information during FOG, including gait acceleration (ACC), electroencephalogram (EEG), electromyogram (EMG), and skin conductance (SC). Two tasks were designed to trigger FOG, including gait initiation failure and FOG during walking. A total number of 12 PD patients completed the experiments and produced a length of 3 hours and 42 minutes of valid data including 2 hours and 14 minutes of normal gait and 1 hour and 28 minutes of freezing of gait. The FOG episodes were labeled by two qualified physicians. The multimodal data have been validated by a FOG detection task. Nature Publishing Group UK 2022-10-07 /pmc/articles/PMC9546845/ /pubmed/36207427 http://dx.doi.org/10.1038/s41597-022-01713-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Zhang, Wei
Yang, Zhuokun
Li, Hantao
Huang, Debin
Wang, Lipeng
Wei, Yanzhao
Zhang, Lei
Ma, Lin
Feng, Huanhuan
Pan, Jing
Guo, Yuzhu
Chan, Piu
Multimodal Data for the Detection of Freezing of Gait in Parkinson’s Disease
title Multimodal Data for the Detection of Freezing of Gait in Parkinson’s Disease
title_full Multimodal Data for the Detection of Freezing of Gait in Parkinson’s Disease
title_fullStr Multimodal Data for the Detection of Freezing of Gait in Parkinson’s Disease
title_full_unstemmed Multimodal Data for the Detection of Freezing of Gait in Parkinson’s Disease
title_short Multimodal Data for the Detection of Freezing of Gait in Parkinson’s Disease
title_sort multimodal data for the detection of freezing of gait in parkinson’s disease
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9546845/
https://www.ncbi.nlm.nih.gov/pubmed/36207427
http://dx.doi.org/10.1038/s41597-022-01713-8
work_keys_str_mv AT zhangwei multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT yangzhuokun multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT lihantao multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT huangdebin multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT wanglipeng multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT weiyanzhao multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT zhanglei multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT malin multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT fenghuanhuan multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT panjing multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT guoyuzhu multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease
AT chanpiu multimodaldataforthedetectionoffreezingofgaitinparkinsonsdisease