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Temporal pyramid attention-based spatiotemporal fusion model for Parkinson's disease diagnosis from gait data
Pei XM(裴晓敏)1,2,3; Fan HJ(范慧杰)2,3; Tang YD(唐延东)2,3
Department机器人学研究室
Source PublicationIET SIGNAL PROCESSING
ISSN1751-9675
2021
Volume15Issue:2Pages:80-87
Indexed BySCI
WOS IDWOS:000631725100002
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [U1613214] ; Natural Science Foundation of Liaoning ProvinceNatural Science Foundation of Liaoning Province [2019ZD0066]
Abstract

Parkinson's disease (PD) is currently an ongoing challenge in daily clinical medicine. To reduce diagnosis time and arduousness and even assess PD levels, a temporal pyramid attention-based spatiotemporal (PAST) fusion model for diagnosis of PD is produced by using gait data from ground reaction forces. This model is innovative in two aspects. First, by using the temporal pyramid attention module, multiscale temporal attention is obtained from raw sequences. Second, 1D convolutional neural network and bidirectional long short-term memory layers are used together to learn spatial fusion features from multiple channels in the spatial domain to obtain multichannel, multiscale fusion features. Experiments are performed on the PhysioBank data set, and the results show that the proposed PAST model outperforms other state-of-the-art methods on classification results. This model can assist in the diagnosis and treatment of PD by using gait data.

Language英语
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/28636
Collection机器人学研究室
Corresponding AuthorFan HJ(范慧杰)
Affiliation1.School of Information and Control Engineering, Liaoning Shihua University, Fushun, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China
Recommended Citation
GB/T 7714
Pei XM,Fan HJ,Tang YD. Temporal pyramid attention-based spatiotemporal fusion model for Parkinson's disease diagnosis from gait data[J]. IET SIGNAL PROCESSING,2021,15(2):80-87.
APA Pei XM,Fan HJ,&Tang YD.(2021).Temporal pyramid attention-based spatiotemporal fusion model for Parkinson's disease diagnosis from gait data.IET SIGNAL PROCESSING,15(2),80-87.
MLA Pei XM,et al."Temporal pyramid attention-based spatiotemporal fusion model for Parkinson's disease diagnosis from gait data".IET SIGNAL PROCESSING 15.2(2021):80-87.
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