NDLI: Extended Kalman filtering for state estimation of a Hill muscle model

Content Provider	IET Digital Library
Author	Mohammadi, Hanieh Yao, Hong Khademi, Gholamreza Nguyen, Thang T. Simon, Dan Richter, Hanz
Abstract	The objectives of this study are five-fold: (i) design an extended Kalman filter (EKF) for the single-muscle and two-muscle Hill models; (ii) design an EKF for unknown-input estimation of the muscle models; (iii) investigate the detectability of the muscle models; (iv) examine the robustness of the EKF to modeling errors; and (v) improve state estimation by incorporating physical constraints into the estimator. Two noisy measurements are available for state estimation: muscle length, which is measured from joint angles; and muscle activation, which is measured from electromyography sensors. Simulation results verify that the EKF is an effective approach for estimation of the activation signals and the states of the system if the system is detectable; the EKF outperforms the high gain observer; and the EKF is robust to modeling errors. The standard deviations of the estimation errors are in the range 0.01–0.1 mm for the muscle lengths, which is one to two orders of magnitude more accurate than the measurements. The standard deviations of the dimensionless muscle activation estimation errors are in the range 0.01–0.02, which is one order of magnitude more accurate than the measurements. A projection approach accounts for constraints to further improve the estimates.
Starting Page	384
Ending Page	394
Page Count	11
ISSN	17518644
Volume Number	12
e-ISSN	17518652
Issue Number	Issue 3, Feb (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/12/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2017.0645
Journal	IET Control Theory & Applications
Publisher Date	2017-12-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Activation Signal Estimation Bioelectric Signal Biology And Medical Computing Contractile Muscle Element Digital Signal Processing Dimensionless Muscle Activation Estimation Error EKF Electrodiagnostics And Other Electrical Measurement Technique Electromyography Electromyography Sonsor Extended Kalman Filtering Filtering Method in Signal Processing High Gain Observer Joint Angles Kalman Filter Measurement Error Medical Signal Processing Muscle Length Measurement Noise Nonlinear Filter Observers Passive Muscle Element Projection Approach Signal Processing Theory Single-muscle Hill Model Standard Deviation State Estimation System Constraint Two-muscle Hill Model Unknown-input Estimation
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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