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Optimized Kalman filtering in dynamical environments for thumb robot motion estimation

International Journal of Reconfigurable and Embedded Systems (IJRES) · Vol. 13 No. 3 (2024) · pp. 512–519

DOI
10.11591/ijres.v13.i3.pp512-519
ISSN
2722-2608, 2089-4864
Published
2024-11-01
Publisher
Institute of Advanced Engineering and Science
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Stroke, a prevalent nerve disorder in Indonesia, necessitates post-stroke rehabilitation like physical and occupational therapy. Hand and finger muscle training, crucial for restoring movement, often involves innovative solutions like finger prosthetic robotics arms. In particular, the advancement in thumb robotics emphasizes the estimation of thumb motion, where the ensemble Kalman filter square root (EnKF-SR) and H-infinity methods are deemed dependable for both linear and nonlinear models. Simulation results, using 400 ensembles, demonstrated nearly identical accuracy between the methods, exceeding 99%, with a 6-7% increase in accuracy compared to 200 ensembles. These advancements offer promising prospects for effective post-stroke rehabilitation and improved thumb movement restoration.

Keywords

Collaboration network of the authors

40 authors · 113 co-authorship links · 45 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Institut Teknologi Sepuluh Nopember
  • Universitas Nahdlatul Ulama Surabaya
  • Universitas Jambi
  • Universitas Airlangga
  • Universitas Islam Negeri Antasari Banjarmasin
  • University of Malaya
  • Universitas Pattimura
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Dimas Fajar Uman PutraInstitut Teknologi Sepuluh Nopember14
Wilda SyahriAffiliation unknown11
Hendro NurhadiInstitut Teknologi Sepuluh Nopember8
Berny Pebo TomasouwUniversitas Pattimura8
Andy SuryowinotoInstitut Teknologi Adhi Tama Surabaya6
Risty Jayanti YuniarAffiliation unknown6
Kharis SugiartoAffiliation unknown6
Dinita RahmaliaDarul Ulum Islamic University5
Firman YudiantoUniversitas Nahdlatul Ulama Surabaya5
Bambang SuhartoAffiliation unknown5
Yusnaidar YusnaidarUniversitas Jambi4
Dieky AdzkiyaInstitut Teknologi Sepuluh Nopember4
Vaizal Asy’ariUniversity of Pembangunan Nasional Veteran Jawa Timur4
Anis Yohana ChaerunisaaAffiliation unknown3
Machrus AliUniversitas Darul Ulum3
Hadi SuyonoUniversity of Brawijaya3
Katherin IndriawatiInstitut Teknologi Sepuluh Nopember2
Reza Maliki AkbarInstitut Teknologi Sepuluh Nopember2
Damris MuhammadUniversitas Jambi2
Aghnia HazrinaAffiliation unknown2
Rifanza HirzanAffiliation unknown2
Epinur EpinurAffiliation unknown2
Abu BakarAffiliation unknown2
Madyawati LatiefAffiliation unknown2
Andita Fitri Mutiara RizkiAffiliation unknown2
Wihda Aisarul AzmiAffiliation unknown2
Melva LouisaAffiliation unknown2
I Made ArtikaAffiliation unknown2
Josephine Elizabeth SiregarAffiliation unknown2
Edisar YantoAffiliation unknown1
Syaiful SyaifulAffiliation unknown1
Emi AndriyaniAffiliation unknown1
Devi Trianauli SiraitAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) http://ijres.iaescore.com/index.php/IJRES/oai, first harvested 8 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Optimized Kalman filtering in dynamical environments for thumb robot motion estimation</dc:title>
	<dc:creator>Herlambang, Teguh</dc:creator>
	<dc:creator>Susanto, Fajar Annas</dc:creator>
	<dc:creator>Firdaus, Aji Akbar</dc:creator>
	<dc:creator>Kusuma, Vicky Andria</dc:creator>
	<dc:creator>Suprapto, Sena Sukmananda</dc:creator>
	<dc:creator>Muhaimin, Muhaimin</dc:creator>
	<dc:creator>Arof, Hamzah</dc:creator>
	<dc:subject xml:lang="en-US">EnKF-SR; Estimation; H-infinity; Motion; Thumb</dc:subject>
	<dc:description xml:lang="en-US">Stroke, a prevalent nerve disorder in Indonesia, necessitates post-stroke rehabilitation like physical and occupational therapy. Hand and finger muscle training, crucial for restoring movement, often involves innovative solutions like finger prosthetic robotics arms. In particular, the advancement in thumb robotics emphasizes the estimation of thumb motion, where the ensemble Kalman filter square root (EnKF-SR) and H-infinity methods are deemed dependable for both linear and nonlinear models. Simulation results, using 400 ensembles, demonstrated nearly identical accuracy between the methods, exceeding 99%, with a 6-7% increase in accuracy compared to 200 ensembles. These advancements offer promising prospects for effective post-stroke rehabilitation and improved thumb movement restoration.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2024-11-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>10.11591/ijres.v13.i3.pp512-519</dc:identifier>
	<dc:source xml:lang="en-US">International Journal of Reconfigurable and Embedded Systems (IJRES); Vol 13, No 3: November 2024; 512-519</dc:source>
	<dc:source>2722-2608</dc:source>
	<dc:source>2089-4864</dc:source>
	<dc:source>10.11591/ijres.v13.i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijres.iaescore.com/index.php/IJRES/article/view/21201/pdf</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Institute of Advanced Engineering and Science (IAES)</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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