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A Hierarchical Architecture for Multisymptom Assessment of Early Parkinson's Disease via Wearable Sensors

文献类型：期刊论文

作者Wang, Chen4; Peng, Liang4; Hou, Zeng-Guang2,3,4; Li, Yanfeng1; Tan, Ying1; Hao, Honglin1
刊名IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
出版日期2022-12-01
卷号14期号:4页码:1553-1563
关键词Diseases Machine learning Hidden Markov models Accelerometers Monitoring Gyroscopes Parkinson's disease Wearable computing Sensor systems multilevel fusion multisymptom assessment Parkinson's disease (PD) wearable sensor system
ISSN号2379-8920
DOI10.1109/TCDS.2021.3123157
通讯作者Hou, Zeng-Guang(zengguang.hou@ia.ac.cn)
英文摘要Parkinson's disease (PD) is the second most common neurodegenerative disorder and the heterogeneity of early PD leads to interrater and intrarater variability in observation based clinical assessment. Thus, objective monitoring of PD induced motor abnormalities has attracted significant attention to manage disease progression. Here, we proposed a hierarchical architecture to reliably detect abnormal characteristics and comprehensively quantify the multisymptom severity in patients with PD. A novel wearable device was designed to measure motor features in 15 PD patients and 15 age-matched healthy subjects, while performing five types of motor tasks. The abnormality classes of multimodal measurements were recognized by hidden Markov models (HMMs) in the first layer of the proposed architecture, aiming at motivating the evaluation of specific motor manifestations. Subsequently, in the second layer, three single symptom models differentiated PD motor characteristics from normal motion patterns and quantified the severity of cardinal PD symptoms in parallel. In order to further analyze the disease status, the multilevel severity quantification was fused in the third layer, where machine learning algorithms were adopted to develop a multisymptom severity score. The experimental results demonstrated that the quantification of three cardinal symptoms was highly accurate to distinguish PD patients from healthy controls. Furthermore, strong correlations were observed between the Unified PD Rating Scale (UPDRS) scores and the predicted subscores for tremor (R = 0.75, P = 1.40e - 3), bradykinesia (R = 0.71, P = 2.80e - 3), and coordination impairments (R = 0.69, P = 4.20e - 3), and the correlation coefficient can be enhanced to 0.88 (P = 1.26e - 5) based on the fusion schemes. In conclusion, the proposed assessment architecture holds great promise to push forward the in-home monitoring of clinical manifestations, thus enabling the self-assessment of disease progression.
资助项目National Natural Science Foundation of China[U1913601] ; National Natural Science Foundation of China[61720106012] ; Beijing Natural Science Foundation[Z170003] ; Chinese Academy of Science[XDB32040000]
WOS研究方向Computer Science ; Robotics ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000916821100021
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Chinese Academy of Science
源URL[http://ir.ia.ac.cn/handle/173211/51365]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者Hou, Zeng-Guang
作者单位1.Chinese Acad Med Sci, Peking Union Med Coll Hosp, Peking Union Med Coll, Beijing 100730, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techno, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Inst Automation, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Chen,Peng, Liang,Hou, Zeng-Guang,et al. A Hierarchical Architecture for Multisymptom Assessment of Early Parkinson's Disease via Wearable Sensors[J]. IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,2022,14(4):1553-1563.
APA Wang, Chen,Peng, Liang,Hou, Zeng-Guang,Li, Yanfeng,Tan, Ying,&Hao, Honglin.(2022).A Hierarchical Architecture for Multisymptom Assessment of Early Parkinson's Disease via Wearable Sensors.IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,14(4),1553-1563.
MLA Wang, Chen,et al."A Hierarchical Architecture for Multisymptom Assessment of Early Parkinson's Disease via Wearable Sensors".IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS 14.4(2022):1553-1563.

入库方式： OAI收割

来源：自动化研究所

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