Position sensing and control with FMG sensors for exoskeleton physical assistance

Muhammad R.U. Islam; Kun Xu; Shaoping Bai

doi:10.1007/978-3-030-01887-0_1

Position sensing and control with FMG sensors for exoskeleton physical assistance

Muhammad R.U. Islam^*, Kun Xu, Shaoping Bai

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Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Bidrag til bog/antologi › Forskning › peer review

5 Citationer (Scopus)

Abstract

Human intention decoding is a primary requirement to control an exoskeleton. In this work, a new method of decoding human intention by Forcemyography (FMG) is explored to estimate elbow joint angle during arm motion. The method utilizes an FSR-based sensor band to read muscle contraction and relaxation. The readings of the sensor band are mapped to the desired joint angle by using coarse Gaussian support vector machine (SVM) regression algorithm. The estimated joint angle is further used to control an elbow joint exoskeleton. Results show that the new method is able to estimate reliably the joint angle for controlling the exoskeleton.

Originalsprog	Engelsk
Titel	Wearable Robotics: Challenges and Trends : Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018
Redaktører	Maria Chiara Carrozza, Silvestro Micera, Jóse L. Pons
Antal sider	5
Forlag	Springer Publishing Company
Publikationsdato	2019
Sider	3-7
ISBN (Trykt)	978-3-030-01886-3
ISBN (Elektronisk)	978-3-030-01887-0
DOI	https://doi.org/10.1007/978-3-030-01887-0_1
Status	Udgivet - 2019

Navn	Biosystems and Biorobotics
Vol/bind	22
ISSN	2195-3562

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10.1007/978-3-030-01887-0_1

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5 Citationer
1 Ph.d.-afhandling

FMG based upper limb motion detection methods, performance analysis and control of assistive exoskeletons
Islam, M. R. U., 2021, Aalborg Universitetsforlag.
Publikation: Ph.d.-afhandling

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Islam, M. R. U., Xu, K., & Bai, S. (2019). Position sensing and control with FMG sensors for exoskeleton physical assistance. I M. C. Carrozza, S. Micera, & J. L. Pons (red.), Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018 (s. 3-7). Springer Publishing Company. https://doi.org/10.1007/978-3-030-01887-0_1

Islam, Muhammad R.U. ; Xu, Kun ; Bai, Shaoping. / Position sensing and control with FMG sensors for exoskeleton physical assistance. Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018. red. / Maria Chiara Carrozza ; Silvestro Micera ; Jóse L. Pons. Springer Publishing Company, 2019. s. 3-7 (Biosystems and Biorobotics, Bind 22).

@inbook{f87fed6d290a4c22be18f12aee53a854,

title = "Position sensing and control with FMG sensors for exoskeleton physical assistance",

abstract = "Human intention decoding is a primary requirement to control an exoskeleton. In this work, a new method of decoding human intention by Forcemyography (FMG) is explored to estimate elbow joint angle during arm motion. The method utilizes an FSR-based sensor band to read muscle contraction and relaxation. The readings of the sensor band are mapped to the desired joint angle by using coarse Gaussian support vector machine (SVM) regression algorithm. The estimated joint angle is further used to control an elbow joint exoskeleton. Results show that the new method is able to estimate reliably the joint angle for controlling the exoskeleton.",

author = "Islam, {Muhammad R.U.} and Kun Xu and Shaoping Bai",

note = "Funding Information: Acknowledgment. The reported work is partially supported by EU-AAL Joint Programme through project AXO-SUIT and Innovation Fund Denmark through project EXO-AIDER. Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.",

year = "2019",

doi = "10.1007/978-3-030-01887-0_1",

language = "English",

isbn = "978-3-030-01886-3",

series = "Biosystems and Biorobotics",

publisher = "Springer Publishing Company",

pages = "3--7",

editor = "Carrozza, {Maria Chiara} and Silvestro Micera and Pons, {J{\'o}se L.}",

booktitle = "Wearable Robotics: Challenges and Trends",

address = "United States",

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Islam, MRU, Xu, K & Bai, S 2019, Position sensing and control with FMG sensors for exoskeleton physical assistance. i MC Carrozza, S Micera & JL Pons (red), Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018. Springer Publishing Company, Biosystems and Biorobotics, bind 22, s. 3-7. https://doi.org/10.1007/978-3-030-01887-0_1

Position sensing and control with FMG sensors for exoskeleton physical assistance. / Islam, Muhammad R.U.; Xu, Kun; Bai, Shaoping.
Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018. red. / Maria Chiara Carrozza; Silvestro Micera; Jóse L. Pons. Springer Publishing Company, 2019. s. 3-7 (Biosystems and Biorobotics, Bind 22).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Bidrag til bog/antologi › Forskning › peer review

TY - CHAP

T1 - Position sensing and control with FMG sensors for exoskeleton physical assistance

AU - Islam, Muhammad R.U.

AU - Xu, Kun

AU - Bai, Shaoping

N1 - Funding Information: Acknowledgment. The reported work is partially supported by EU-AAL Joint Programme through project AXO-SUIT and Innovation Fund Denmark through project EXO-AIDER. Publisher Copyright: © Springer Nature Switzerland AG 2019. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.

PY - 2019

Y1 - 2019

N2 - Human intention decoding is a primary requirement to control an exoskeleton. In this work, a new method of decoding human intention by Forcemyography (FMG) is explored to estimate elbow joint angle during arm motion. The method utilizes an FSR-based sensor band to read muscle contraction and relaxation. The readings of the sensor band are mapped to the desired joint angle by using coarse Gaussian support vector machine (SVM) regression algorithm. The estimated joint angle is further used to control an elbow joint exoskeleton. Results show that the new method is able to estimate reliably the joint angle for controlling the exoskeleton.

AB - Human intention decoding is a primary requirement to control an exoskeleton. In this work, a new method of decoding human intention by Forcemyography (FMG) is explored to estimate elbow joint angle during arm motion. The method utilizes an FSR-based sensor band to read muscle contraction and relaxation. The readings of the sensor band are mapped to the desired joint angle by using coarse Gaussian support vector machine (SVM) regression algorithm. The estimated joint angle is further used to control an elbow joint exoskeleton. Results show that the new method is able to estimate reliably the joint angle for controlling the exoskeleton.

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T3 - Biosystems and Biorobotics

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BT - Wearable Robotics: Challenges and Trends

A2 - Carrozza, Maria Chiara

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Islam MRU, Xu K, Bai S. Position sensing and control with FMG sensors for exoskeleton physical assistance. I Carrozza MC, Micera S, Pons JL, red., Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics WeRob2018. Springer Publishing Company. 2019. s. 3-7. (Biosystems and Biorobotics, Bind 22). doi: 10.1007/978-3-030-01887-0_1

Position sensing and control with FMG sensors for exoskeleton physical assistance

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FMG based upper limb motion detection methods, performance analysis and control of assistive exoskeletons

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