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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) · hlm. 512–519

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

Abstrak

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.

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  • Institut Teknologi Sepuluh Nopember
  • Universitas Airlangga
  • Institut Teknologi Kalimantan
  • Universitas Jambi
  • Universitas Nahdlatul Ulama Surabaya
  • Padjadjaran University
  • National Research and Innovation Agency
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Rekan penulisOrganisasiArtikel bersama
Dimas Fajar Uman PutraInstitut Teknologi Sepuluh Nopember14
Wilda SyahriUniversitas Jambi10
Hendro NurhadiInstitut Teknologi Sepuluh Nopember8
Berny Pebo TomasouwUniversitas Pattimura8
Andy SuryowinotoInstitut Teknologi Adhi Tama Surabaya6
Bambang SuhartoUniversitas Airlangga6
Rizky Amalia SinulinggaUniversitas Airlangga6
Risty Jayanti YuniarInstitut Teknologi Kalimantan6
Kharis SugiartoInstitut Teknologi Kalimantan6
Dinita RahmaliaDarul Ulum Islamic University5
Firman YudiantoUniversitas Nahdlatul Ulama Surabaya5
Rachman Sinatriya MarjiantoUniversitas Airlangga5
Dieky AdzkiyaInstitut Teknologi Sepuluh Nopember4
Vaizal Asy’ariUniversity of Pembangunan Nasional Veteran Jawa Timur4
Anis Yohana ChaerunisaaPadjadjaran University3
Yusnaidar YusnaidarUniversitas Jambi3
Machrus AliUniversitas Darul Ulum3
Hadi SuyonoUniversity of Brawijaya3
Muhammad Aziz MuslimUniversity of Brawijaya3
Katherin IndriawatiInstitut Teknologi Sepuluh Nopember2
Reza Maliki AkbarInstitut Teknologi Sepuluh Nopember2
Aghnia HazrinaPadjadjaran University2
Rifanza HirzanPadjadjaran University2
Abu BakarUniversitas Airlangga2
Madyawati LatiefUniversitas Jambi2
Andita Fitri Mutiara RizkiNational Research and Innovation Agency2
Wihda Aisarul AzmiNational Research and Innovation Agency2
Melva LouisaUniversity of Indonesia2
I Made ArtikaIPB University2
Josephine Elizabeth SiregarNational Research and Innovation Agency2
Erna AprilianiInstitut Teknologi Sepuluh Nopember1
Mayga KikiInstitut Teknologi Sepuluh Nopember1
Tesa Eranti PutriUniversitas Airlangga1

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Sumber metadata: OAI-PMH (metadata jurnal) http://ijres.iaescore.com/index.php/IJRES/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (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>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijres.iaescore.com/index.php/IJRES/article/view/21201</dc:identifier>
	<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>
</oai_dc:dc>