Sensitivity analysis and optimization for a head movement model

Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide t...
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Autor*in:	Zangemeister, W. H. [verfasserIn] Lehman, S. Stark, L.

Format:	Artikel
Sprache:	Englisch

Erschienen:	1981

Schlagwörter:	Sensitivity Analysis Head Movement Movement Trajectory Head Rotation Sixth Order

Anmerkung:	© Springer-Verlag 1981

Übergeordnetes Werk:	Enthalten in: Biological cybernetics - Springer-Verlag, 1975, 41(1981), 1 vom: Juni, Seite 33-45
Übergeordnetes Werk:	volume:41 ; year:1981 ; number:1 ; month:06 ; pages:33-45

Links:	Volltext

DOI / URN:	10.1007/BF01836125

Katalog-ID:	OLC2052682317

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520			\|a Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model.
650		4	\|a Sensitivity Analysis
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allfields	10.1007/BF01836125 doi (DE-627)OLC2052682317 (DE-He213)BF01836125-p DE-627 ger DE-627 rakwb eng 570 VZ 570 000 VZ 12 ssgn BIODIV DE-30 fid Zangemeister, W. H. verfasserin aut Sensitivity analysis and optimization for a head movement model 1981 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1981 Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model. Sensitivity Analysis Head Movement Movement Trajectory Head Rotation Sixth Order Lehman, S. aut Stark, L. aut Enthalten in Biological cybernetics Springer-Verlag, 1975 41(1981), 1 vom: Juni, Seite 33-45 (DE-627)129556351 (DE-600)220699-7 (DE-576)015013545 0340-1200 nnns volume:41 year:1981 number:1 month:06 pages:33-45 https://doi.org/10.1007/BF01836125 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 SSG-OPC-BBI SSG-OPC-MAT GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_55 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_74 GBV_ILN_101 GBV_ILN_105 GBV_ILN_130 GBV_ILN_259 GBV_ILN_267 GBV_ILN_2002 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2045 GBV_ILN_2088 GBV_ILN_2219 GBV_ILN_2237 GBV_ILN_2409 GBV_ILN_2410 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4035 GBV_ILN_4046 GBV_ILN_4082 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4277 GBV_ILN_4302 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4319 GBV_ILN_4320 GBV_ILN_4324 GBV_ILN_4700 AR 41 1981 1 06 33-45
spelling	10.1007/BF01836125 doi (DE-627)OLC2052682317 (DE-He213)BF01836125-p DE-627 ger DE-627 rakwb eng 570 VZ 570 000 VZ 12 ssgn BIODIV DE-30 fid Zangemeister, W. H. verfasserin aut Sensitivity analysis and optimization for a head movement model 1981 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1981 Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model. Sensitivity Analysis Head Movement Movement Trajectory Head Rotation Sixth Order Lehman, S. aut Stark, L. aut Enthalten in Biological cybernetics Springer-Verlag, 1975 41(1981), 1 vom: Juni, Seite 33-45 (DE-627)129556351 (DE-600)220699-7 (DE-576)015013545 0340-1200 nnns volume:41 year:1981 number:1 month:06 pages:33-45 https://doi.org/10.1007/BF01836125 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 SSG-OPC-BBI SSG-OPC-MAT GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_55 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_74 GBV_ILN_101 GBV_ILN_105 GBV_ILN_130 GBV_ILN_259 GBV_ILN_267 GBV_ILN_2002 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2045 GBV_ILN_2088 GBV_ILN_2219 GBV_ILN_2237 GBV_ILN_2409 GBV_ILN_2410 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4035 GBV_ILN_4046 GBV_ILN_4082 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4277 GBV_ILN_4302 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4319 GBV_ILN_4320 GBV_ILN_4324 GBV_ILN_4700 AR 41 1981 1 06 33-45
allfields_unstemmed	10.1007/BF01836125 doi (DE-627)OLC2052682317 (DE-He213)BF01836125-p DE-627 ger DE-627 rakwb eng 570 VZ 570 000 VZ 12 ssgn BIODIV DE-30 fid Zangemeister, W. H. verfasserin aut Sensitivity analysis and optimization for a head movement model 1981 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1981 Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model. Sensitivity Analysis Head Movement Movement Trajectory Head Rotation Sixth Order Lehman, S. aut Stark, L. aut Enthalten in Biological cybernetics Springer-Verlag, 1975 41(1981), 1 vom: Juni, Seite 33-45 (DE-627)129556351 (DE-600)220699-7 (DE-576)015013545 0340-1200 nnns volume:41 year:1981 number:1 month:06 pages:33-45 https://doi.org/10.1007/BF01836125 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 SSG-OPC-BBI SSG-OPC-MAT GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_55 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_74 GBV_ILN_101 GBV_ILN_105 GBV_ILN_130 GBV_ILN_259 GBV_ILN_267 GBV_ILN_2002 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2045 GBV_ILN_2088 GBV_ILN_2219 GBV_ILN_2237 GBV_ILN_2409 GBV_ILN_2410 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4035 GBV_ILN_4046 GBV_ILN_4082 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4277 GBV_ILN_4302 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4319 GBV_ILN_4320 GBV_ILN_4324 GBV_ILN_4700 AR 41 1981 1 06 33-45
allfieldsGer	10.1007/BF01836125 doi (DE-627)OLC2052682317 (DE-He213)BF01836125-p DE-627 ger DE-627 rakwb eng 570 VZ 570 000 VZ 12 ssgn BIODIV DE-30 fid Zangemeister, W. H. verfasserin aut Sensitivity analysis and optimization for a head movement model 1981 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1981 Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model. Sensitivity Analysis Head Movement Movement Trajectory Head Rotation Sixth Order Lehman, S. aut Stark, L. aut Enthalten in Biological cybernetics Springer-Verlag, 1975 41(1981), 1 vom: Juni, Seite 33-45 (DE-627)129556351 (DE-600)220699-7 (DE-576)015013545 0340-1200 nnns volume:41 year:1981 number:1 month:06 pages:33-45 https://doi.org/10.1007/BF01836125 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 SSG-OPC-BBI SSG-OPC-MAT GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_55 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_74 GBV_ILN_101 GBV_ILN_105 GBV_ILN_130 GBV_ILN_259 GBV_ILN_267 GBV_ILN_2002 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2045 GBV_ILN_2088 GBV_ILN_2219 GBV_ILN_2237 GBV_ILN_2409 GBV_ILN_2410 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4035 GBV_ILN_4046 GBV_ILN_4082 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4277 GBV_ILN_4302 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4319 GBV_ILN_4320 GBV_ILN_4324 GBV_ILN_4700 AR 41 1981 1 06 33-45
allfieldsSound	10.1007/BF01836125 doi (DE-627)OLC2052682317 (DE-He213)BF01836125-p DE-627 ger DE-627 rakwb eng 570 VZ 570 000 VZ 12 ssgn BIODIV DE-30 fid Zangemeister, W. H. verfasserin aut Sensitivity analysis and optimization for a head movement model 1981 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 1981 Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model. Sensitivity Analysis Head Movement Movement Trajectory Head Rotation Sixth Order Lehman, S. aut Stark, L. aut Enthalten in Biological cybernetics Springer-Verlag, 1975 41(1981), 1 vom: Juni, Seite 33-45 (DE-627)129556351 (DE-600)220699-7 (DE-576)015013545 0340-1200 nnns volume:41 year:1981 number:1 month:06 pages:33-45 https://doi.org/10.1007/BF01836125 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 SSG-OPC-BBI SSG-OPC-MAT GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_55 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_74 GBV_ILN_101 GBV_ILN_105 GBV_ILN_130 GBV_ILN_259 GBV_ILN_267 GBV_ILN_2002 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2045 GBV_ILN_2088 GBV_ILN_2219 GBV_ILN_2237 GBV_ILN_2409 GBV_ILN_2410 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4035 GBV_ILN_4046 GBV_ILN_4082 GBV_ILN_4103 GBV_ILN_4193 GBV_ILN_4219 GBV_ILN_4277 GBV_ILN_4302 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4310 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4319 GBV_ILN_4320 GBV_ILN_4324 GBV_ILN_4700 AR 41 1981 1 06 33-45
language	English
source	Enthalten in Biological cybernetics 41(1981), 1 vom: Juni, Seite 33-45 volume:41 year:1981 number:1 month:06 pages:33-45
sourceStr	Enthalten in Biological cybernetics 41(1981), 1 vom: Juni, Seite 33-45 volume:41 year:1981 number:1 month:06 pages:33-45
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Sensitivity Analysis Head Movement Movement Trajectory Head Rotation Sixth Order
dewey-raw	570
isfreeaccess_bool	false
container_title	Biological cybernetics
authorswithroles_txt_mv	Zangemeister, W. H. @@aut@@ Lehman, S. @@aut@@ Stark, L. @@aut@@
publishDateDaySort_date	1981-06-01T00:00:00Z
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author	Zangemeister, W. H.
spellingShingle	Zangemeister, W. H. ddc 570 ssgn 12 fid BIODIV misc Sensitivity Analysis misc Head Movement misc Movement Trajectory misc Head Rotation misc Sixth Order Sensitivity analysis and optimization for a head movement model
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title	Sensitivity analysis and optimization for a head movement model
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title_sort	sensitivity analysis and optimization for a head movement model
title_auth	Sensitivity analysis and optimization for a head movement model
abstract	Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model. © Springer-Verlag 1981
abstractGer	Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model. © Springer-Verlag 1981
abstract_unstemmed	Abstract A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model. © Springer-Verlag 1981
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title_short	Sensitivity analysis and optimization for a head movement model
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Sensitivity analysis and optimization for a head movement model

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