International Journal of Reconfigurable and Embedded Systems (IJRES)
Vol 13, No 3: November 2024

Optimized Kalman filtering in dynamical environments for thumb robot motion estimation

Herlambang, Teguh (Unknown)
Susanto, Fajar Annas (Unknown)
Firdaus, Aji Akbar (Unknown)
Kusuma, Vicky Andria (Unknown)
Suprapto, Sena Sukmananda (Unknown)
Muhaimin, Muhaimin (Unknown)
Arof, Hamzah (Unknown)



Article Info

Publish Date
01 Nov 2024

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.

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Journal Info

Abbrev

IJRES

Publisher

Subject

Economics, Econometrics & Finance

Description

The centre of gravity of the computer industry is now moving from personal computing into embedded computing with the advent of VLSI system level integration and reconfigurable core in system-on-chip (SoC). Reconfigurable and Embedded systems are increasingly becoming a key technological component ...