CASIA OpenIR  > 多模态人工智能系统全国重点实验室
A Double-Hurdle Quantification Model for Freezing of Gait of Parkinson's Patients
Ningcun Xu1,2; Chen Wang1; Liang Peng1; Xiao-Hu Zhou1; Jingyao Chen1,2; Zhi Cheng1,2; Zeng-Guang Hou1,3,4
Source PublicationIEEE Transactions on Biomedical Engineering
2024
Pages1 - 12
Abstract

Freezing of gait (FOG) leads to an increased risk of falls and limited mobility in individuals with Parkinson's disease (PD). However, existing research ignores the fine-grained quantitative assessment of FOG severity. This paper provides a double-hurdle model that uses typical spatiotemporal gait features to quantify the FOG severity in patients with PD. Moreover, a novel multi-output random forest algorithm is used as one hurdle of the double-hurdle model, further enhancing the model's performance. We conduct six experiments on a public PD gait database. Results demonstrate that the designed random forest algorithm in the double-hurdle model-hyperparameter independence framework achieves outstanding performances with the highest correlation coefficient (CC) of 0.972 and the lowest root mean square error (RMSE) of 2.488. Furthermore, we study the effect of drug state on the gait patterns of PD patients with or without FOG. Results show that “OFF” state amplifies the visibility of FOG symptoms in PD patients. Therefore, this study holds significant implications for the management and treatment of PD.

MOST Discipline Catalogue工学::计算机科学与技术(可授工学、理学学位)
DOI10.1109/TBME.2024.3402677
Indexed BySCI
Language英语
IS Representative Paper
Sub direction classification人工智能+医疗
planning direction of the national heavy laboratory智能计算与学习
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57189
Collection多模态人工智能系统全国重点实验室
Corresponding AuthorLiang Peng; Zeng-Guang Hou
Affiliation1.the State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences
2.the Faculty of Innovation Engineering, Macau University of Science and Technology
3.CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences
4.the School of Artificial Intelligence, University of Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Ningcun Xu,Chen Wang,Liang Peng,et al. A Double-Hurdle Quantification Model for Freezing of Gait of Parkinson's Patients[J]. IEEE Transactions on Biomedical Engineering,2024:1 - 12.
APA Ningcun Xu.,Chen Wang.,Liang Peng.,Xiao-Hu Zhou.,Jingyao Chen.,...&Zeng-Guang Hou.(2024).A Double-Hurdle Quantification Model for Freezing of Gait of Parkinson's Patients.IEEE Transactions on Biomedical Engineering,1 - 12.
MLA Ningcun Xu,et al."A Double-Hurdle Quantification Model for Freezing of Gait of Parkinson's Patients".IEEE Transactions on Biomedical Engineering (2024):1 - 12.
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