Hybridization between multi-objective genetic algorithm and support vector machine for feature selection in walker-assisted gait

Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, compar...

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Published in:	Computer methods and programs in biomedicine Vol. 113; no. 3; pp. 736 - 748
Main Authors:	Martins, Maria, Costa, Lino, Frizera, Anselmo, Ceres, Ramón, Santos, Cristina
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ireland Ltd 01.03.2014 Elsevier
Subjects:	Adult Algorithms Applied sciences Biological and medical sciences Biomechanical Phenomena Computational Biology Computer science; control theory; systems Data processing. List processing. Character string processing Dependent Ambulation - physiology Dependent Ambulation - statistics & numerical data Diseases of the osteoarticular system. Orthopedic treatment Evolutionary algorithms Exact sciences and technology Gait - physiology Gait analysis Humans Internal Medicine Medical sciences Memory organisation. Data processing Models, Biological Other Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects) Rehabilitation - instrumentation Rehabilitation - statistics & numerical data Software Support Vector Machine Walker assistance Walkers Young Adult Walker assistance Gait analysis Evolutionary algorithms Space time correlation Gait Redundancy Evolutionary algorithm Handicapped aid Pedestrian Hybridization Posture Walking Pain Genetic algorithm Annoyance Kinematics Vector support machine Selection criterion Medical application
ISSN:	0169-2607, 1872-7565, 1872-7565
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Abstract	Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach.
AbstractList	Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach.Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Abstract Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach.
Author	Santos, Cristina Martins, Maria Ceres, Ramón Frizera, Anselmo Costa, Lino
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Keywords	Walker assistance Gait analysis Evolutionary algorithms Space time correlation Gait Redundancy Evolutionary algorithm Handicapped aid Pedestrian Hybridization Posture Walking Pain Genetic algorithm Annoyance Kinematics Vector support machine Selection criterion Medical application
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References	Martins, Frizera, Santos, Ceres (bib0005) 2011 Olney, Griffin, McBride (bib0015) 1998; 78 Jurman, Furlanello (bib0110) Baofeng (bib0025) 2009; 39 Deb, Pratap, Agarwal, Meyarivan (bib0055) 2002; 6 Altman, Bland (bib0120) 1994; 309 Vaughan, Davis, O’Connor (bib0010) 1992 Handl, Knowles (bib0075) 2006; 2 Lai, Begg, Palaniswami (bib0020) 2009; 13 Fawcett (bib0090) 2006; 27 Ishikura (bib0125) 2001; 55 Igel (bib0065) 2005 K. Deb, An introduction to genetic algorithms, in: Sadhana 24 Parts 4 And 5, Vol. 24, (4–5), August–Ocotober 1999, pp. 293–315. Youdas, Kotajarvi, Padgett, Kaufman (bib0130) 2005; 86 Hamdani, Won, Alimi, Karray (bib0070) 2007; 4431 Winter (bib0085) 1991 Bi (bib0060) 2003 Sun, Yin (bib0050) 2007; 35 Saeys, Inza, Larrañaga (bib0030) 2007; 23 Morita, Sabourin, Bortolozzi, Suen (bib0045) 2003; 2 Bäck (bib0105) 1996 Cunha (bib0040) 2010; 74 Lee, Landgrebe (bib0035) 1997; 8 Alkjaer, Larsen, Pedersen, Nielsen, Simonsen (bib0080) 2006; 5 Altman, Bland (bib0115) 1994; 308 Spall (bib0100) 2003 Lee (10.1016/j.cmpb.2013.12.005_bib0035) 1997; 8 Cunha (10.1016/j.cmpb.2013.12.005_bib0040) 2010; 74 Baofeng (10.1016/j.cmpb.2013.12.005_bib0025) 2009; 39 Sun (10.1016/j.cmpb.2013.12.005_bib0050) 2007; 35 Bi (10.1016/j.cmpb.2013.12.005_bib0060) 2003 Altman (10.1016/j.cmpb.2013.12.005_bib0120) 1994; 309 Spall (10.1016/j.cmpb.2013.12.005_bib0100) 2003 Saeys (10.1016/j.cmpb.2013.12.005_bib0030) 2007; 23 Bäck (10.1016/j.cmpb.2013.12.005_bib0105) 1996 Youdas (10.1016/j.cmpb.2013.12.005_bib0130) 2005; 86 Fawcett (10.1016/j.cmpb.2013.12.005_bib0090) 2006; 27 Winter (10.1016/j.cmpb.2013.12.005_bib0085) 1991 Vaughan (10.1016/j.cmpb.2013.12.005_bib0010) 1992 Hamdani (10.1016/j.cmpb.2013.12.005_bib0070) 2007; 4431 Lai (10.1016/j.cmpb.2013.12.005_bib0020) 2009; 13 Martins (10.1016/j.cmpb.2013.12.005_bib0005) 2011 Handl (10.1016/j.cmpb.2013.12.005_bib0075) 2006; 2 Deb (10.1016/j.cmpb.2013.12.005_bib0055) 2002; 6 Alkjaer (10.1016/j.cmpb.2013.12.005_bib0080) 2006; 5 Igel (10.1016/j.cmpb.2013.12.005_bib0065) 2005 Altman (10.1016/j.cmpb.2013.12.005_bib0115) 1994; 308 10.1016/j.cmpb.2013.12.005_bib0095 Ishikura (10.1016/j.cmpb.2013.12.005_bib0125) 2001; 55 Olney (10.1016/j.cmpb.2013.12.005_bib0015) 1998; 78 Morita (10.1016/j.cmpb.2013.12.005_bib0045) 2003; 2 Jurman (10.1016/j.cmpb.2013.12.005_sbref0110)
References_xml	– year: 2003 ident: bib0060 article-title: Multi-objective programming in SVMs publication-title: Proceedings of the Twentieth International Conference on Machine Learning, ICML – year: 2011 ident: bib0005 article-title: Assistive mobility devices focusing on smart walkers: classification and review publication-title: Robotics and Autonomous Systems – volume: 55 start-page: 73 year: 2001 end-page: 82 ident: bib0125 article-title: Biomechanical analysis of weight bearing force and muscle activation levels in the lower extremities during gait with a walker publication-title: Acta Medica Okayama – volume: 308 start-page: 1552 year: 1994 ident: bib0115 article-title: Diagnostic tests. 1: Sensitivity and specificity publication-title: BMJ – volume: 8 start-page: 75 year: 1997 end-page: 83 ident: bib0035 article-title: Decision boundary feature extraction for neural networks publication-title: IEEE Transactions on Neural Networks – volume: 27 start-page: 861 year: 2006 end-page: 874 ident: bib0090 article-title: An introduction to ROC analysis publication-title: Pattern Recognition Letters – year: 1992 ident: bib0010 article-title: Dynamics of Human Gait – volume: 5 year: 2006 ident: bib0080 article-title: Biomechanical analysis of rollator walking publication-title: Biomedical Engineering Online – volume: 74 start-page: 85 year: 2010 end-page: 92 ident: bib0040 article-title: Feature selection using multi-objective evolutionary algorithms: application to cardiac SPECT diagnosis publication-title: Advances in Intelligent and Soft Computing – volume: 309 start-page: 102 year: 1994 ident: bib0120 article-title: Diagnostic tests. 2: Predictive values publication-title: BMJ – volume: 39 start-page: 36 year: 2009 end-page: 46 ident: bib0025 article-title: Gait feature subset selection by mutual information publication-title: IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans – start-page: 534 year: 2005 end-page: 546 ident: bib0065 article-title: Multi-objective model selection for support vector machines publication-title: EMO – volume: 13 start-page: 687 year: 2009 end-page: 702 ident: bib0020 article-title: Computational intelligence in gait research: a perspective on current applications and future challenges publication-title: IEEE Transactions on Information Technology in Biomedicine – volume: 4431 start-page: 240 year: 2007 end-page: 247 ident: bib0070 article-title: Multi-objective feature selection with NSGA II publication-title: Adaptive and Natural Computing Algorithms – volume: 35 start-page: 95 year: 2007 end-page: 118 ident: bib0050 article-title: A genetic algorithm based approach for 3D face recognition publication-title: Computer Imaging Vision – volume: 23 start-page: 2507 year: 2007 end-page: 2517 ident: bib0030 article-title: A review of feature selection techniques in bioinformatics publication-title: Bioinformatics Advance Access – ident: bib0110 – year: 1996 ident: bib0105 article-title: Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms – volume: 2 start-page: 666 year: 2003 end-page: 670 ident: bib0045 article-title: Unsupervised feature selection using multi-objective genetic algorithms for handwritten word recognition publication-title: ICDAR – volume: 78 start-page: 814 year: 1998 end-page: 828 ident: bib0015 article-title: Multivariate examination of data from gait analysis of persons with stroke publication-title: Journal of the American Physical Therapy Association – year: 2003 ident: bib0100 article-title: Introduction to Stochastic Search and Optimization – volume: 86 start-page: 394 year: 2005 end-page: 398 ident: bib0130 article-title: Partial weight-bearing gait using conventional assistive devices publication-title: Archives of Physical Medicine and Rehabilitation – volume: 2 start-page: 217 year: 2006 end-page: 238 ident: bib0075 article-title: Feature subset selection in unsupervised learning via multiobjective optimization publication-title: International Journal of Computational Intelligence Research – volume: 6 start-page: 182 year: 2002 end-page: 197 ident: bib0055 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Transactions on Evolutionary Computation – year: 1991 ident: bib0085 article-title: The Biomechanics and Motor Control of Human Gait: Normal, Elderly and Pathological – reference: K. Deb, An introduction to genetic algorithms, in: Sadhana 24 Parts 4 And 5, Vol. 24, (4–5), August–Ocotober 1999, pp. 293–315. – start-page: 534 year: 2005 ident: 10.1016/j.cmpb.2013.12.005_bib0065 article-title: Multi-objective model selection for support vector machines – volume: 5 issue: 2 year: 2006 ident: 10.1016/j.cmpb.2013.12.005_bib0080 article-title: Biomechanical analysis of rollator walking publication-title: Biomedical Engineering Online – volume: 8 start-page: 75 year: 1997 ident: 10.1016/j.cmpb.2013.12.005_bib0035 article-title: Decision boundary feature extraction for neural networks publication-title: IEEE Transactions on Neural Networks doi: 10.1109/72.554193 – volume: 35 start-page: 95 year: 2007 ident: 10.1016/j.cmpb.2013.12.005_bib0050 article-title: A genetic algorithm based approach for 3D face recognition publication-title: Computer Imaging Vision doi: 10.1007/978-1-4020-6182-0_4 – year: 1996 ident: 10.1016/j.cmpb.2013.12.005_bib0105 – year: 1991 ident: 10.1016/j.cmpb.2013.12.005_bib0085 – year: 2003 ident: 10.1016/j.cmpb.2013.12.005_bib0100 – year: 2003 ident: 10.1016/j.cmpb.2013.12.005_bib0060 article-title: Multi-objective programming in SVMs – ident: 10.1016/j.cmpb.2013.12.005_bib0095 doi: 10.1007/BF02823145 – volume: 308 start-page: 1552 year: 1994 ident: 10.1016/j.cmpb.2013.12.005_bib0115 article-title: Diagnostic tests. 1: Sensitivity and specificity publication-title: BMJ doi: 10.1136/bmj.308.6943.1552 – volume: 27 start-page: 861 year: 2006 ident: 10.1016/j.cmpb.2013.12.005_bib0090 article-title: An introduction to ROC analysis publication-title: Pattern Recognition Letters doi: 10.1016/j.patrec.2005.10.010 – ident: 10.1016/j.cmpb.2013.12.005_sbref0110 – volume: 309 start-page: 102 year: 1994 ident: 10.1016/j.cmpb.2013.12.005_bib0120 article-title: Diagnostic tests. 2: Predictive values publication-title: BMJ doi: 10.1136/bmj.309.6947.102 – volume: 39 start-page: 36 issue: 1 year: 2009 ident: 10.1016/j.cmpb.2013.12.005_bib0025 article-title: Gait feature subset selection by mutual information publication-title: IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans doi: 10.1109/TSMCA.2008.2007977 – volume: 78 start-page: 814 year: 1998 ident: 10.1016/j.cmpb.2013.12.005_bib0015 article-title: Multivariate examination of data from gait analysis of persons with stroke publication-title: Journal of the American Physical Therapy Association – volume: 55 start-page: 73 issue: 2 year: 2001 ident: 10.1016/j.cmpb.2013.12.005_bib0125 article-title: Biomechanical analysis of weight bearing force and muscle activation levels in the lower extremities during gait with a walker publication-title: Acta Medica Okayama – volume: 74 start-page: 85 year: 2010 ident: 10.1016/j.cmpb.2013.12.005_bib0040 article-title: Feature selection using multi-objective evolutionary algorithms: application to cardiac SPECT diagnosis publication-title: Advances in Intelligent and Soft Computing doi: 10.1007/978-3-642-13214-8_11 – volume: 2 start-page: 666 year: 2003 ident: 10.1016/j.cmpb.2013.12.005_bib0045 article-title: Unsupervised feature selection using multi-objective genetic algorithms for handwritten word recognition publication-title: ICDAR – volume: 2 start-page: 217 year: 2006 ident: 10.1016/j.cmpb.2013.12.005_bib0075 article-title: Feature subset selection in unsupervised learning via multiobjective optimization publication-title: International Journal of Computational Intelligence Research doi: 10.5019/j.ijcir.2006.64 – volume: 4431 start-page: 240 year: 2007 ident: 10.1016/j.cmpb.2013.12.005_bib0070 article-title: Multi-objective feature selection with NSGA II publication-title: Adaptive and Natural Computing Algorithms doi: 10.1007/978-3-540-71618-1_27 – volume: 13 start-page: 687 issue: 5 year: 2009 ident: 10.1016/j.cmpb.2013.12.005_bib0020 article-title: Computational intelligence in gait research: a perspective on current applications and future challenges publication-title: IEEE Transactions on Information Technology in Biomedicine doi: 10.1109/TITB.2009.2022913 – volume: 86 start-page: 394 year: 2005 ident: 10.1016/j.cmpb.2013.12.005_bib0130 article-title: Partial weight-bearing gait using conventional assistive devices publication-title: Archives of Physical Medicine and Rehabilitation doi: 10.1016/j.apmr.2004.03.026 – year: 2011 ident: 10.1016/j.cmpb.2013.12.005_bib0005 article-title: Assistive mobility devices focusing on smart walkers: classification and review publication-title: Robotics and Autonomous Systems – year: 1992 ident: 10.1016/j.cmpb.2013.12.005_bib0010 – volume: 23 start-page: 2507 issue: 19 year: 2007 ident: 10.1016/j.cmpb.2013.12.005_bib0030 article-title: A review of feature selection techniques in bioinformatics publication-title: Bioinformatics Advance Access – volume: 6 start-page: 182 year: 2002 ident: 10.1016/j.cmpb.2013.12.005_bib0055 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.996017
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Snippet	Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort... Abstract Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as,...
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SubjectTerms	Adult Algorithms Applied sciences Biological and medical sciences Biomechanical Phenomena Computational Biology Computer science; control theory; systems Data processing. List processing. Character string processing Dependent Ambulation - physiology Dependent Ambulation - statistics & numerical data Diseases of the osteoarticular system. Orthopedic treatment Evolutionary algorithms Exact sciences and technology Gait - physiology Gait analysis Humans Internal Medicine Medical sciences Memory organisation. Data processing Models, Biological Other Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects) Rehabilitation - instrumentation Rehabilitation - statistics & numerical data Software Support Vector Machine Walker assistance Walkers Young Adult
Title	Hybridization between multi-objective genetic algorithm and support vector machine for feature selection in walker-assisted gait
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