Principal component analysis for ataxic gait using a triaxial accelerometer

Background It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait. Methods Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial. Results PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = −0.363, p = 0.004; ρ = −0.574, p < 0.001, respectively). Conclusions PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Matsushima, Akira [verfasserIn] Yoshida, Kunihiro Genno, Hirokazu Ikeda, Shu-ichi

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Cerebellar ataxia Triaxial accelerometer Ataxic gait Gait analysis Principal component analysis SARA

Anmerkung:	© The Author(s). 2017

Übergeordnetes Werk:	Enthalten in: Journal of neuroEngineering and rehabilitation - London : BioMed Central, 2004, 14(2017), 1 vom: 02. Mai
Übergeordnetes Werk:	volume:14 ; year:2017 ; number:1 ; day:02 ; month:05

Links:	Volltext

DOI / URN:	10.1186/s12984-017-0249-7

Katalog-ID:	SPR029226538

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allfields	10.1186/s12984-017-0249-7 doi (DE-627)SPR029226538 (SPR)s12984-017-0249-7-e DE-627 ger DE-627 rakwb eng Matsushima, Akira verfasserin aut Principal component analysis for ataxic gait using a triaxial accelerometer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait. Methods Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial. Results PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = −0.363, p = 0.004; ρ = −0.574, p < 0.001, respectively). Conclusions PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer. Cerebellar ataxia (dpeaa)DE-He213 Triaxial accelerometer (dpeaa)DE-He213 Ataxic gait (dpeaa)DE-He213 Gait analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 SARA (dpeaa)DE-He213 Yoshida, Kunihiro aut Genno, Hirokazu aut Ikeda, Shu-ichi aut Enthalten in Journal of neuroEngineering and rehabilitation London : BioMed Central, 2004 14(2017), 1 vom: 02. Mai (DE-627)461907933 (DE-600)2164377-5 1743-0003 nnns volume:14 year:2017 number:1 day:02 month:05 https://dx.doi.org/10.1186/s12984-017-0249-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2017 1 02 05
spelling	10.1186/s12984-017-0249-7 doi (DE-627)SPR029226538 (SPR)s12984-017-0249-7-e DE-627 ger DE-627 rakwb eng Matsushima, Akira verfasserin aut Principal component analysis for ataxic gait using a triaxial accelerometer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait. Methods Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial. Results PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = −0.363, p = 0.004; ρ = −0.574, p < 0.001, respectively). Conclusions PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer. Cerebellar ataxia (dpeaa)DE-He213 Triaxial accelerometer (dpeaa)DE-He213 Ataxic gait (dpeaa)DE-He213 Gait analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 SARA (dpeaa)DE-He213 Yoshida, Kunihiro aut Genno, Hirokazu aut Ikeda, Shu-ichi aut Enthalten in Journal of neuroEngineering and rehabilitation London : BioMed Central, 2004 14(2017), 1 vom: 02. Mai (DE-627)461907933 (DE-600)2164377-5 1743-0003 nnns volume:14 year:2017 number:1 day:02 month:05 https://dx.doi.org/10.1186/s12984-017-0249-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2017 1 02 05
allfields_unstemmed	10.1186/s12984-017-0249-7 doi (DE-627)SPR029226538 (SPR)s12984-017-0249-7-e DE-627 ger DE-627 rakwb eng Matsushima, Akira verfasserin aut Principal component analysis for ataxic gait using a triaxial accelerometer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait. Methods Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial. Results PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = −0.363, p = 0.004; ρ = −0.574, p < 0.001, respectively). Conclusions PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer. Cerebellar ataxia (dpeaa)DE-He213 Triaxial accelerometer (dpeaa)DE-He213 Ataxic gait (dpeaa)DE-He213 Gait analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 SARA (dpeaa)DE-He213 Yoshida, Kunihiro aut Genno, Hirokazu aut Ikeda, Shu-ichi aut Enthalten in Journal of neuroEngineering and rehabilitation London : BioMed Central, 2004 14(2017), 1 vom: 02. Mai (DE-627)461907933 (DE-600)2164377-5 1743-0003 nnns volume:14 year:2017 number:1 day:02 month:05 https://dx.doi.org/10.1186/s12984-017-0249-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2017 1 02 05
allfieldsGer	10.1186/s12984-017-0249-7 doi (DE-627)SPR029226538 (SPR)s12984-017-0249-7-e DE-627 ger DE-627 rakwb eng Matsushima, Akira verfasserin aut Principal component analysis for ataxic gait using a triaxial accelerometer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait. Methods Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial. Results PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = −0.363, p = 0.004; ρ = −0.574, p < 0.001, respectively). Conclusions PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer. Cerebellar ataxia (dpeaa)DE-He213 Triaxial accelerometer (dpeaa)DE-He213 Ataxic gait (dpeaa)DE-He213 Gait analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 SARA (dpeaa)DE-He213 Yoshida, Kunihiro aut Genno, Hirokazu aut Ikeda, Shu-ichi aut Enthalten in Journal of neuroEngineering and rehabilitation London : BioMed Central, 2004 14(2017), 1 vom: 02. Mai (DE-627)461907933 (DE-600)2164377-5 1743-0003 nnns volume:14 year:2017 number:1 day:02 month:05 https://dx.doi.org/10.1186/s12984-017-0249-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2017 1 02 05
allfieldsSound	10.1186/s12984-017-0249-7 doi (DE-627)SPR029226538 (SPR)s12984-017-0249-7-e DE-627 ger DE-627 rakwb eng Matsushima, Akira verfasserin aut Principal component analysis for ataxic gait using a triaxial accelerometer 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 Background It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait. Methods Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial. Results PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = −0.363, p = 0.004; ρ = −0.574, p < 0.001, respectively). Conclusions PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer. Cerebellar ataxia (dpeaa)DE-He213 Triaxial accelerometer (dpeaa)DE-He213 Ataxic gait (dpeaa)DE-He213 Gait analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 SARA (dpeaa)DE-He213 Yoshida, Kunihiro aut Genno, Hirokazu aut Ikeda, Shu-ichi aut Enthalten in Journal of neuroEngineering and rehabilitation London : BioMed Central, 2004 14(2017), 1 vom: 02. Mai (DE-627)461907933 (DE-600)2164377-5 1743-0003 nnns volume:14 year:2017 number:1 day:02 month:05 https://dx.doi.org/10.1186/s12984-017-0249-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2017 1 02 05
language	English
source	Enthalten in Journal of neuroEngineering and rehabilitation 14(2017), 1 vom: 02. Mai volume:14 year:2017 number:1 day:02 month:05
sourceStr	Enthalten in Journal of neuroEngineering and rehabilitation 14(2017), 1 vom: 02. Mai volume:14 year:2017 number:1 day:02 month:05
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topic_facet	Cerebellar ataxia Triaxial accelerometer Ataxic gait Gait analysis Principal component analysis SARA
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authorswithroles_txt_mv	Matsushima, Akira @@aut@@ Yoshida, Kunihiro @@aut@@ Genno, Hirokazu @@aut@@ Ikeda, Shu-ichi @@aut@@
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author	Matsushima, Akira
spellingShingle	Matsushima, Akira misc Cerebellar ataxia misc Triaxial accelerometer misc Ataxic gait misc Gait analysis misc Principal component analysis misc SARA Principal component analysis for ataxic gait using a triaxial accelerometer
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topic_title	Principal component analysis for ataxic gait using a triaxial accelerometer Cerebellar ataxia (dpeaa)DE-He213 Triaxial accelerometer (dpeaa)DE-He213 Ataxic gait (dpeaa)DE-He213 Gait analysis (dpeaa)DE-He213 Principal component analysis (dpeaa)DE-He213 SARA (dpeaa)DE-He213
topic	misc Cerebellar ataxia misc Triaxial accelerometer misc Ataxic gait misc Gait analysis misc Principal component analysis misc SARA
topic_unstemmed	misc Cerebellar ataxia misc Triaxial accelerometer misc Ataxic gait misc Gait analysis misc Principal component analysis misc SARA
topic_browse	misc Cerebellar ataxia misc Triaxial accelerometer misc Ataxic gait misc Gait analysis misc Principal component analysis misc SARA
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title	Principal component analysis for ataxic gait using a triaxial accelerometer
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title_full	Principal component analysis for ataxic gait using a triaxial accelerometer
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author_browse	Matsushima, Akira Yoshida, Kunihiro Genno, Hirokazu Ikeda, Shu-ichi
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format_se	Elektronische Aufsätze
author-letter	Matsushima, Akira
doi_str_mv	10.1186/s12984-017-0249-7
title_sort	principal component analysis for ataxic gait using a triaxial accelerometer
title_auth	Principal component analysis for ataxic gait using a triaxial accelerometer
abstract	Background It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait. Methods Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial. Results PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = −0.363, p = 0.004; ρ = −0.574, p < 0.001, respectively). Conclusions PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer. © The Author(s). 2017
abstractGer	Background It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait. Methods Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial. Results PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = −0.363, p = 0.004; ρ = −0.574, p < 0.001, respectively). Conclusions PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer. © The Author(s). 2017
abstract_unstemmed	Background It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait. Methods Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial. Results PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = −0.363, p = 0.004; ρ = −0.574, p < 0.001, respectively). Conclusions PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer. © The Author(s). 2017
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title_short	Principal component analysis for ataxic gait using a triaxial accelerometer
url	https://dx.doi.org/10.1186/s12984-017-0249-7
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author2	Yoshida, Kunihiro Genno, Hirokazu Ikeda, Shu-ichi
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