Gait Phase Estimation Based on Noncontact Capacitive Sensing and Adaptive Oscillators
Zheng, Enhao1,2; Manca, Silvia3; Yan, Tingfang3,4; Parri, Andrea3; Vitiello, Nicola3,5; Wang, Qining6,7
AbstractThis paper presents a novel strategy aiming to acquire an accurate and walking-speed-adaptive estimation of the gait phase through noncontact capacitive sensing and adaptive oscillators (AOs). The capacitive sensing system is designed with two sensing cuffs that can measure the leg muscle shape changes during walking. The system can be dressed above the clothes and free human skin from contacting to electrodes. In order to track the capacitance signals, the gait phase estimator is designed based on the AO dynamic system due to its ability of synchronizing with quasi-periodic signals. After the implementation of the whole system, we first evaluated the offline estimation performance by experiments with 12 healthy subjects walking on a treadmill with changing speeds. The strategy achieved an accurate and consistent gait phase estimation with only one channel of capacitance signal. The average root-meansquare errors in one stride were 0.19 rad (3.0% of one gait cycle) for constant walking speeds and 0.31 rad (4.9% of one gait cycle) for speed transitions even after the subjects rewore the sensing cuffs. We then validated our strategy in a real-time gait phase estimation task with three subjects walking with changing speeds. Our study indicates that the strategy based on capacitive sensing and AOs is a promising alternative for the control of exoskeleton/orthosis.
KeywordGait Phase Estimation Orthosis Exoskeleton Capacitive Sensing Adaptive Oscillators
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding OrganizationBeijing Disabled Persons' Federation ; National Natural Science Foundation of China(91648207) ; Beijing Municipal Science and Technology Project(Z151100000915073) ; Beijing Nova Program(Z141101001814001) ; EU within the CYBERLEGs(FP7-ICT-2011-2.1 ; Fondazione Pisa within the IUVO(154/11) ; 287894)
WOS Research AreaEngineering
WOS SubjectEngineering, Biomedical
WOS IDWOS:000411585100012
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Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Peking Univ, Coll Engn, Robot Res Grp, Beijing 100871, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
3.Scuola Super Sant Anna, BioRobot Inst, Pisa, Italy
4.Chinese Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
5.Fdn Don Carlo Gnocchi, Florence, Italy
6.Coll Engn, Robot Res Grp, Beijing 100871, Peoples R China
7.Peking Univ, Beijing Innovat Ctr Engn Sci & Adv Technol, Beijing 100871, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zheng, Enhao,Manca, Silvia,Yan, Tingfang,et al. Gait Phase Estimation Based on Noncontact Capacitive Sensing and Adaptive Oscillators[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,2017,64(10):2419-2430.
APA Zheng, Enhao,Manca, Silvia,Yan, Tingfang,Parri, Andrea,Vitiello, Nicola,&Wang, Qining.(2017).Gait Phase Estimation Based on Noncontact Capacitive Sensing and Adaptive Oscillators.IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,64(10),2419-2430.
MLA Zheng, Enhao,et al."Gait Phase Estimation Based on Noncontact Capacitive Sensing and Adaptive Oscillators".IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 64.10(2017):2419-2430.
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