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Pregled bibliografske jedinice broj: 1186022

Dynamics Combined with Hill Model for Functional Electrical Stimulation Ankle Angle Prediction

(Hrvatsko-kineski bilateralni projekt znanstveno-tehnološke suradnje) Zhang, Xianghong; Jiang, Ziqin; Gao, Yueming; Li, Xu; Xu, Pan; Lučev Vasić, Željka; Čuljak, Ivana; Cifrek, Mario; Du, Min
Dynamics Combined with Hill Model for Functional Electrical Stimulation Ankle Angle Prediction // IEEE Journal of Biomedical and Health Informatics, 27 (2023), 5; 2186-2196 doi:10.1109/JBHI.2022.3158426 (međunarodna recenzija, članak, znanstveni)

CROSBI ID: 1186022 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Dynamics Combined with Hill Model for Functional Electrical Stimulation Ankle Angle Prediction

Autori
Zhang, Xianghong ; Jiang, Ziqin ; Gao, Yueming ; Li, Xu ; Xu, Pan ; Lučev Vasić, Željka ; Čuljak, Ivana ; Cifrek, Mario ; Du, Min

Kolaboracija
Hrvatsko-kineski bilateralni projekt znanstveno-tehnološke suradnje

Izvornik
IEEE Journal of Biomedical and Health Informatics (2168-2194) 27 (2023), 5; 2186-2196

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
FES ; Hill model ; dynamics ; ankle joint angle ; EKF algorithm ; musculoskeletal model

Sažetak
Musculoskeletal models play an essential role in ankle rehabilitation research. The majority of the existing models have established the relationship between EMG and joint torque. However, EMG signal acquisition requires higher clinical conditions, such as sensitivity to external circumstances, such as motion artifacts and electrode position. To solve the nonlinear and time-varying nature of joint movement, a Functional Electrical Stimulation (FES) model was proposed in this study to simulate the whole process of ankle dorsiflexion. The model is combined with muscle contraction dynamics based on Hill model and ankle inverse dynamics to connect FES parameters, torques, and ankle angles. In addition, the extended Kalman filter (EKF) algorithm was applied to identify the unknown parameters of the model. Model validation experiment was performed by acquiring the actual data of healthy volunteers. Results showed that the root mean square error (RMSE) and normalized root mean square error (NRMSE) of this model were 11.93%0.53% and 1.390.26, respectivelywhich means it can effectively predict the output variation of ankle joint angle while changing electrical stimulation parameters. Therefore, the proposed mode is essential for developing closed-loop feedback control of electrical stimulation and has the potential to help patients to conduct rehabilitation training.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Mario Cifrek (autor)

Avatar Url Željka Lučev Vasić (autor)

Avatar Url Ivana Čuljak (autor)

Poveznice na cjeloviti tekst rada:

doi ieeexplore.ieee.org

Citiraj ovu publikaciju:

(Hrvatsko-kineski bilateralni projekt znanstveno-tehnološke suradnje) Zhang, Xianghong; Jiang, Ziqin; Gao, Yueming; Li, Xu; Xu, Pan; Lučev Vasić, Željka; Čuljak, Ivana; Cifrek, Mario; Du, Min
Dynamics Combined with Hill Model for Functional Electrical Stimulation Ankle Angle Prediction // IEEE Journal of Biomedical and Health Informatics, 27 (2023), 5; 2186-2196 doi:10.1109/JBHI.2022.3158426 (međunarodna recenzija, članak, znanstveni)
(Hrvatsko-kineski bilateralni projekt znanstveno-tehnološke suradnje) (Hrvatsko-kineski bilateralni projekt znanstveno-tehnološke suradnje) Zhang, X., Jiang, Z., Gao, Y., Li, X., Xu, P., Lučev Vasić, Ž., Čuljak, I., Cifrek, M. & Du, M. (2023) Dynamics Combined with Hill Model for Functional Electrical Stimulation Ankle Angle Prediction. IEEE Journal of Biomedical and Health Informatics, 27 (5), 2186-2196 doi:10.1109/JBHI.2022.3158426.
@article{article, author = {Zhang, Xianghong and Jiang, Ziqin and Gao, Yueming and Li, Xu and Xu, Pan and Lu\v{c}ev Vasi\'{c}, \v{Z}eljka and \v{C}uljak, Ivana and Cifrek, Mario and Du, Min}, year = {2023}, pages = {2186-2196}, DOI = {10.1109/JBHI.2022.3158426}, keywords = {FES, Hill model, dynamics, ankle joint angle, EKF algorithm, musculoskeletal model}, journal = {IEEE Journal of Biomedical and Health Informatics}, doi = {10.1109/JBHI.2022.3158426}, volume = {27}, number = {5}, issn = {2168-2194}, title = {Dynamics Combined with Hill Model for Functional Electrical Stimulation Ankle Angle Prediction}, keyword = {FES, Hill model, dynamics, ankle joint angle, EKF algorithm, musculoskeletal model} }
@article{article, author = {Zhang, Xianghong and Jiang, Ziqin and Gao, Yueming and Li, Xu and Xu, Pan and Lu\v{c}ev Vasi\'{c}, \v{Z}eljka and \v{C}uljak, Ivana and Cifrek, Mario and Du, Min}, year = {2023}, pages = {2186-2196}, DOI = {10.1109/JBHI.2022.3158426}, keywords = {FES, Hill model, dynamics, ankle joint angle, EKF algorithm, musculoskeletal model}, journal = {IEEE Journal of Biomedical and Health Informatics}, doi = {10.1109/JBHI.2022.3158426}, volume = {27}, number = {5}, issn = {2168-2194}, title = {Dynamics Combined with Hill Model for Functional Electrical Stimulation Ankle Angle Prediction}, keyword = {FES, Hill model, dynamics, ankle joint angle, EKF algorithm, musculoskeletal model} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE

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