Normal and pathological gait classification LSTM model
Computer vision-based clinical gait analysis is the subject of permanent research. However, there are very few datasets publicly available; hence the comparison of existing methods between each other is not straightforward. Even if the test data are in an open access, existing databases contain very...
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| Vydáno v: | Artificial intelligence in medicine Ročník 94; s. 54 - 66 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Netherlands
Elsevier B.V
01.03.2019
Elsevier |
| Témata: | |
| ISSN: | 0933-3657, 1873-2860, 1873-2860 |
| On-line přístup: | Získat plný text |
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| Abstract | Computer vision-based clinical gait analysis is the subject of permanent research. However, there are very few datasets publicly available; hence the comparison of existing methods between each other is not straightforward. Even if the test data are in an open access, existing databases contain very few test subjects and single modality measurements, which limit their usage. The contributions of this paper are three-fold. First, we propose a new open-access multi-modal database acquired with the Kinect v.2 camera for the task of gait analysis. Second, we adapt to use the skeleton joint orientation data to calculate kinematic gait parameters to match golden-standard MOCAP systems. We propose a new set of features based on 3D low-limbs flexion dynamics to analyze the symmetry of a gait. Third, we design a Long-Short Term Memory (LSTM) ensemble model to create an unsupervised gait classification tool. The results show that joint orientation data provided by Kinect can be successfully used in an inexpensive clinical gait monitoring system, with the results moderately better than reported state-of-the-art for three normal/pathological gait classes. |
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| AbstractList | Computer vision-based clinical gait analysis is the subject of permanent research. However, there are very few datasets publicly available; hence the comparison of existing methods between each other is not straightforward. Even if the test data are in an open access, existing databases contain very few test subjects and single modality measurements, which limit their usage. The contributions of this paper are three-fold. First, we propose a new open-access multi-modal database acquired with the Kinect v.2 camera for the task of gait analysis. Second, we adapt to use the skeleton joint orientation data to calculate kinematic gait parameters to match golden-standard MOCAP systems. We propose a new set of features based on 3D low-limbs flexion dynamics to analyze the symmetry of a gait. Third, we design a Long-Short Term Memory (LSTM) ensemble model to create an unsupervised gait classification tool. The results show that joint orientation data provided by Kinect can be successfully used in an inexpensive clinical gait monitoring system, with the results moderately better than reported state-of-the-art for three normal/pathological gait classes.Copyright © 2019 Elsevier B.V. All rights reserved. Computer vision-based clinical gait analysis is the subject of permanent research. However, there are very few datasets publicly available; hence the comparison of existing methods between each other is not straightforward. Even if the test data are in an open access, existing databases contain very few test subjects and single modality measurements, which limit their usage. The contributions of this paper are three-fold. First, we propose a new open-access multi-modal database acquired with the Kinect v.2 camera for the task of gait analysis. Second, we adapt to use the skeleton joint orientation data to calculate kinematic gait parameters to match golden-standard MOCAP systems. We propose a new set of features based on 3D low-limbs flexion dynamics to analyze the symmetry of a gait. Third, we design a Long-Short Term Memory (LSTM) ensemble model to create an unsupervised gait classification tool. The results show that joint orientation data provided by Kinect can be successfully used in an inexpensive clinical gait monitoring system, with the results moderately better than reported state-of-the-art for three normal/pathological gait classes. Computer vision-based clinical gait analysis is the subject of permanent research. However, there are very few datasets publicly available; hence the comparison of existing methods between each other is not straightforward. Even if the test data are in an open access, existing databases contain very few test subjects and single modality measurements, which limit their usage. The contributions of this paper are three-fold. First, we propose a new open-access multi-modal database acquired with the Kinect v.2 camera for the task of gait analysis. Second, we adapt to use the skeleton joint orientation data to calculate kinematic gait parameters to match golden-standard MOCAP systems. We propose a new set of features based on 3D low-limbs flexion dynamics to analyze the symmetry of a gait. Third, we design a Long-Short Term Memory (LSTM) ensemble model to create an unsupervised gait classification tool. The results show that joint orientation data provided by Kinect can be successfully used in an inexpensive clinical gait monitoring system, with the results moderately better than reported state-of-the-art for three normal/pathological gait classes.Computer vision-based clinical gait analysis is the subject of permanent research. However, there are very few datasets publicly available; hence the comparison of existing methods between each other is not straightforward. Even if the test data are in an open access, existing databases contain very few test subjects and single modality measurements, which limit their usage. The contributions of this paper are three-fold. First, we propose a new open-access multi-modal database acquired with the Kinect v.2 camera for the task of gait analysis. Second, we adapt to use the skeleton joint orientation data to calculate kinematic gait parameters to match golden-standard MOCAP systems. We propose a new set of features based on 3D low-limbs flexion dynamics to analyze the symmetry of a gait. Third, we design a Long-Short Term Memory (LSTM) ensemble model to create an unsupervised gait classification tool. The results show that joint orientation data provided by Kinect can be successfully used in an inexpensive clinical gait monitoring system, with the results moderately better than reported state-of-the-art for three normal/pathological gait classes. |
| Author | Migniot, Cyrille Morozov, Alexey Sushkova, Olga Dipanda, Albert Khokhlova, Margarita |
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| Cites_doi | 10.1016/j.jvcir.2013.02.006 10.1016/j.patrec.2016.10.012 10.1117/1.JEI.25.6.063019 10.1007/s00371-016-1330-0 10.1016/j.gaitpost.2016.10.001 10.3390/s16020194 10.1097/BPO.0b013e3181558ade 10.7243/2055-2386-4-6 10.1109/TSMCB.2010.2043526 10.1016/j.jcm.2016.02.012 10.3390/s16010115 10.1162/neco.1997.9.8.1735 10.1371/journal.pone.0139913 10.1186/1743-0003-9-81 10.7717/peerj.918 10.1007/s00371-015-1092-0 10.1037/1082-989X.1.1.30 10.1016/j.jbiomech.2015.05.021 10.3390/s17102301 10.1037/1040-3590.6.4.284 10.1123/jab.2016-0107 10.3390/s16111792 |
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| Keywords | RGB-D Kinect skeletons LSTM Gait assessment Gait modeling Low-limbs motion |
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| References | Papageorgiou, Chalvatzaki, Tzafestas, Maragos (bib0120) 2015 Koo, Li (bib0210) 2016; 15 Roberts, Mongeon, Prince (bib0045) 2017; 4 Geerse, Coolen, Kolijn, Roerdink (bib0010) 2017; 17 Chaaraoui, Padilla-López, Flórez-Revuelta (bib0060) 2015 Wren, Do, Hara, Dorey, Kay, Otsuka (bib0195) 2007; 27 Vapnik, Mukherjee (bib0185) 2000 Gabel, Gilad-Bachrach, Renshaw, Schuster (bib0100) 2012 Mentiplay, Perraton, Bower, Pua, McGaw, Heywood (bib0015) 2015; 48 Gates, Darter, Dingwell, Wilken (bib0095) 2012; 9 Litany, Bronstein, Bronstein, Makadia (bib0200) 2017 Feng, Li, Luo (bib0155) 2016 Li, Wang, Sharf, Cao, Tu, Chen (bib0055) 2018; 34 Hofmann, Geiger, Bachmann, Schuller, Rigoll (bib0085) 2014; 25 Kastaniotis, Economou, Fotopoulos, Kartsakalis, Papathanasopoulos (bib0105) 2014 Drumond, Marques, Vasconcelos, Clua (bib0130) 2018 Bogo, Kanazawa, Lassner, Gehler, Romero, Black (bib0205) 2016 McGraw, Wong (bib0175) 1996; 1 Liu, Du, Wu, Wang, Qiao (bib0150) 2016 Ordóñez, Roggen (bib0145) 2016; 16 Nguyen, Meunier (bib0080) 2018 Kastaniotis, Theodorakopoulos, Fotopoulos (bib0035) 2016; 25 Cicchetti (bib0215) 1994; 6 Devanne, Wannous, Daoudi, Berretti, Del Bimbo, Pala (bib0110) 2016 Ahmed, Paul, Gavrilova (bib0040) 2015; 31 Blanco (bib0165) 2010 Guess, Razu, Jahandar, Skubic, Huo (bib0050) 2017; 33 Eltoukhy, Oh, Kuenze, Signorile (bib0115) 2017; 51 Gu, Ding, Wang, Wu (bib0125) 2010; 40 Graves, Schmidhuber (bib0140) 2009 Zhu, Lan, Xing, Zeng, Li, Shen (bib0180) 2016 Zhao, Qi, Li, Dong, Yu (bib0160) 2018 Springer, Yogev Seligmann (bib0020) 2016; 16 Kingma, Ba (bib0170) 2014 Rocha, Choupina, Fernandes, Rosas, Vaz, Cunha (bib0070) 2014 Paiement, Tao, Hannuna, Camplani, Damen, Mirmehdi (bib0075) 2014 Pedregosa, Varoquaux, Gramfort, Michel, Thirion, Grisel (bib0190) 2011; 12 Moore, Hnat, van den Bogert (bib0090) 2015; 3 Bobillo, Dranca, Bernad (bib0025) 2017 Kastaniotis, Theodorakopoulos, Economou, Fotopoulos (bib0030) 2016; 84 Hochreiter, Schmidhuber (bib0135) 1997; 9 Geerse, Coolen, Roerdink (bib0005) 2015; 10 Nguyen, Huynh, Meunier (bib0065) 2016; 16 Chaaraoui (10.1016/j.artmed.2018.12.007_bib0060) 2015 Guess (10.1016/j.artmed.2018.12.007_bib0050) 2017; 33 Koo (10.1016/j.artmed.2018.12.007_bib0210) 2016; 15 Nguyen (10.1016/j.artmed.2018.12.007_bib0080) 2018 Devanne (10.1016/j.artmed.2018.12.007_bib0110) 2016 Springer (10.1016/j.artmed.2018.12.007_bib0020) 2016; 16 Cicchetti (10.1016/j.artmed.2018.12.007_bib0215) 1994; 6 Rocha (10.1016/j.artmed.2018.12.007_bib0070) 2014 Feng (10.1016/j.artmed.2018.12.007_bib0155) 2016 Graves (10.1016/j.artmed.2018.12.007_bib0140) 2009 Liu (10.1016/j.artmed.2018.12.007_bib0150) 2016 Blanco (10.1016/j.artmed.2018.12.007_bib0165) 2010 Gates (10.1016/j.artmed.2018.12.007_bib0095) 2012; 9 Papageorgiou (10.1016/j.artmed.2018.12.007_bib0120) 2015 Kastaniotis (10.1016/j.artmed.2018.12.007_bib0030) 2016; 84 Gu (10.1016/j.artmed.2018.12.007_bib0125) 2010; 40 Geerse (10.1016/j.artmed.2018.12.007_bib0010) 2017; 17 Bobillo (10.1016/j.artmed.2018.12.007_bib0025) 2017 Ahmed (10.1016/j.artmed.2018.12.007_bib0040) 2015; 31 Vapnik (10.1016/j.artmed.2018.12.007_bib0185) 2000 McGraw (10.1016/j.artmed.2018.12.007_bib0175) 1996; 1 Geerse (10.1016/j.artmed.2018.12.007_bib0005) 2015; 10 Li (10.1016/j.artmed.2018.12.007_bib0055) 2018; 34 Ordóñez (10.1016/j.artmed.2018.12.007_bib0145) 2016; 16 Zhao (10.1016/j.artmed.2018.12.007_bib0160) 2018 Kastaniotis (10.1016/j.artmed.2018.12.007_bib0105) 2014 Litany (10.1016/j.artmed.2018.12.007_bib0200) 2017 Paiement (10.1016/j.artmed.2018.12.007_bib0075) 2014 Drumond (10.1016/j.artmed.2018.12.007_bib0130) 2018 Nguyen (10.1016/j.artmed.2018.12.007_bib0065) 2016; 16 Gabel (10.1016/j.artmed.2018.12.007_bib0100) 2012 Hochreiter (10.1016/j.artmed.2018.12.007_bib0135) 1997; 9 Zhu (10.1016/j.artmed.2018.12.007_bib0180) 2016 Bogo (10.1016/j.artmed.2018.12.007_bib0205) 2016 Kastaniotis (10.1016/j.artmed.2018.12.007_bib0035) 2016; 25 Roberts (10.1016/j.artmed.2018.12.007_bib0045) 2017; 4 Hofmann (10.1016/j.artmed.2018.12.007_bib0085) 2014; 25 Eltoukhy (10.1016/j.artmed.2018.12.007_bib0115) 2017; 51 Mentiplay (10.1016/j.artmed.2018.12.007_bib0015) 2015; 48 Kingma (10.1016/j.artmed.2018.12.007_bib0170) 2014 Pedregosa (10.1016/j.artmed.2018.12.007_bib0190) 2011; 12 Wren (10.1016/j.artmed.2018.12.007_bib0195) 2007; 27 Moore (10.1016/j.artmed.2018.12.007_bib0090) 2015; 3 |
| References_xml | – start-page: 895 year: 2016 end-page: 900 ident: bib0110 article-title: Learning shape variations of motion trajectories for gait analysis publication-title: 23rd international conference on pattern recognition (ICPR) – volume: 16 start-page: 1792 year: 2016 ident: bib0065 article-title: Skeleton-based abnormal gait detection publication-title: Sensors – volume: 9 start-page: 81 year: 2012 ident: bib0095 article-title: Comparison of walking overground and in a computer assisted rehabilitation environment (caren) in individuals with and without transtibial amputation publication-title: J Neuroeng Rehabil – volume: 34 start-page: 229 year: 2018 end-page: 241 ident: bib0055 article-title: Classification of gait anomalies from kinect publication-title: Vis Comput – volume: 6 start-page: 284 year: 1994 ident: bib0215 article-title: Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology publication-title: Psychol Assess – start-page: 6342 year: 2015 end-page: 6347 ident: bib0120 article-title: Hidden Markov modeling of human pathological gait using laser range finder for an assisted living intelligent robotic walker publication-title: 2015 IEEE/RSJ international conference on intelligent robots and systems (IROS) – volume: 25 start-page: 063019 year: 2016 ident: bib0035 article-title: Pose-based gait recognition with local gradient descriptors and hierarchically aggregated residuals publication-title: J Electron Imaging – start-page: 325 year: 2016 end-page: 330 ident: bib0155 article-title: Learning effective gait features using LSTM publication-title: 23rd international conference on pattern recognition (ICPR) – volume: 17 start-page: 2301 year: 2017 ident: bib0010 article-title: Validation of foot placement locations from ankle data of a kinect v2 sensor publication-title: Sensors – volume: 84 start-page: 245 year: 2016 end-page: 251 ident: bib0030 article-title: Gait based recognition via fusing information from Euclidean and Riemannian manifolds publication-title: Pattern Recognit Lett – start-page: 164 year: 2014 end-page: 167 ident: bib0105 article-title: Using kinect for assesing the state of multiple sclerosis patients publication-title: 2014 EAI 4th international conference on wireless mobile communication and healthcare (Mobihealth) – start-page: 215 year: 2018 end-page: 222 ident: bib0130 article-title: Peek – an LSTM recurrent network for motion classification from sparse data publication-title: Proceedings of the 13th international joint conference on computer vision, imaging and computer graphics theory and applications – volume 1: GRAPP – volume: 33 start-page: 176 year: 2017 end-page: 181 ident: bib0050 article-title: Comparison of 3d joint angles measured with the kinect 2.0 skeletal tracker versus a marker-based motion capture system publication-title: J Appl Biomech – volume: 3 start-page: e918 year: 2015 ident: bib0090 article-title: An elaborate data set on human gait and the effect of mechanical perturbations publication-title: PeerJ – volume: 1 start-page: 30 year: 1996 ident: bib0175 article-title: Forming inferences about some intraclass correlation coefficients publication-title: Psychol Methods – start-page: 1964 year: 2012 end-page: 1967 ident: bib0100 article-title: Full body gait analysis with kinect publication-title: Engineering in medicine and biology society (EMBC), annual international conference of the IEEE – volume: 48 start-page: 2166 year: 2015 end-page: 2170 ident: bib0015 article-title: Gait assessment using the microsoft xbox one kinect: concurrent validity and inter-day reliability of spatiotemporal and kinematic variables publication-title: J Biomech – volume: 9 start-page: 1735 year: 1997 end-page: 1780 ident: bib0135 article-title: Long short-term memory publication-title: Neural Comput – year: 2018 ident: bib0080 article-title: Walking gait dataset: point clouds, skeletons and silhouettes, Tech. Rep. 1379 – volume: 12 start-page: 2825 year: 2011 end-page: 2830 ident: bib0190 article-title: Scikit-learn: machine learning in python publication-title: J Mach Learn Res – volume: 16 start-page: 194 year: 2016 ident: bib0020 article-title: Validity of the kinect for gait assessment: a focused review publication-title: Sensors – start-page: 561 year: 2016 end-page: 578 ident: bib0205 article-title: Keep it SMPL: automatic estimation of 3d human pose and shape from a single image publication-title: European conference on computer vision – volume: 31 start-page: 915 year: 2015 end-page: 924 ident: bib0040 article-title: Dtw-based kernel and rank-level fusion for 3d gait recognition using kinect publication-title: Vis Comput – volume: 27 start-page: 765 year: 2007 end-page: 768 ident: bib0195 article-title: Gillette gait index as a gait analysis summary measure: comparison with qualitative visual assessments of overall gait publication-title: J Pediatr Orthop – volume: 15 start-page: 155 year: 2016 end-page: 163 ident: bib0210 article-title: A guideline of selecting and reporting intraclass correlation coefficients for reliability research publication-title: J Chiropr Med – start-page: 397 year: 2017 end-page: 404 ident: bib0025 article-title: A fuzzy ontology-based system for gait recognition using kinect sensor publication-title: International conference on scalable uncertainty management – start-page: 153 year: 2014 end-page: 166 ident: bib0075 article-title: Online quality assessment of human movement from skeleton data publication-title: British machine vision conference – volume: 51 start-page: 77 year: 2017 end-page: 83 ident: bib0115 article-title: Improved kinect-based spatiotemporal and kinematic treadmill gait assessment publication-title: Gait Posture – start-page: 1 year: 2015 end-page: 6 ident: bib0060 article-title: Abnormal gait detection with rgb-d devices using joint motion history features publication-title: 11th IEEE international conference and workshops on automatic face and gesture recognition (FG), vol. 7 – volume: 40 start-page: 1021 year: 2010 end-page: 1033 ident: bib0125 article-title: Action and gait recognition from recovered 3-d human joints publication-title: IEEE Trans Syst Man Cybern Part B (Cybern) – start-page: 659 year: 2000 end-page: 665 ident: bib0185 article-title: Support vector method for multivariate density estimation publication-title: Advances in neural information processing systems – start-page: 1058 year: 2016 end-page: 1063 ident: bib0150 article-title: Deep rehabilitation gait learning for modeling knee joints of lower-limb exoskeleton publication-title: 2016 IEEE international conference on robotics and biomimetics (ROBIO) – year: 2014 ident: bib0170 article-title: Adam: a method for stochastic optimization – start-page: 6 year: 2016 ident: bib0180 article-title: Co-occurrence feature learning for skeleton based action recognition using regularized deep lstm networks publication-title: AAAI, vol. 2 – year: 2017 ident: bib0200 article-title: Deformable shape completion with graph convolutional autoencoders – start-page: 3126 year: 2014 end-page: 3129 ident: bib0070 article-title: Parkinson's disease assessment based on gait analysis using an innovative rgb-d camera system publication-title: 36th annual international conference of the IEEE engineering in medicine and biology society (EMBC) – volume: 10 year: 2015 ident: bib0005 article-title: Kinematic validation of a multi-kinect v2 instrumented 10-meter walkway for quantitative gait assessments publication-title: PLOS ONE – start-page: 106155B year: 2018 ident: bib0160 article-title: LSTM for diagnosis of neurodegenerative diseases using gait data publication-title: Ninth international conference on graphic and image processing (ICGIP 2017), vol. 10615 – volume: 4 start-page: 6 year: 2017 ident: bib0045 article-title: Biomechanical parameters for gait analysis: a systematic review of healthy human gait publication-title: Phys Therapy Rehabil – volume: 16 start-page: 115 year: 2016 ident: bib0145 article-title: Deep convolutional and LSTM recurrent neural networks for multimodal wearable activity recognition publication-title: Sensors – year: 2010 ident: bib0165 article-title: A tutorial on Se (3) transformation parameterizations and on-manifold optimization – volume: 25 start-page: 195 year: 2014 end-page: 206 ident: bib0085 article-title: The tum gait from audio, image and depth (gaid) database: multimodal recognition of subjects and traits publication-title: J Vis Commun Image Represent – start-page: 545 year: 2009 end-page: 552 ident: bib0140 article-title: Offline handwriting recognition with multidimensional recurrent neural networks publication-title: Advances in neural information processing systems – volume: 25 start-page: 195 issue: 1 year: 2014 ident: 10.1016/j.artmed.2018.12.007_bib0085 article-title: The tum gait from audio, image and depth (gaid) database: multimodal recognition of subjects and traits publication-title: J Vis Commun Image Represent doi: 10.1016/j.jvcir.2013.02.006 – start-page: 1058 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0150 article-title: Deep rehabilitation gait learning for modeling knee joints of lower-limb exoskeleton – start-page: 215 year: 2018 ident: 10.1016/j.artmed.2018.12.007_bib0130 article-title: Peek – an LSTM recurrent network for motion classification from sparse data – start-page: 164 year: 2014 ident: 10.1016/j.artmed.2018.12.007_bib0105 article-title: Using kinect for assesing the state of multiple sclerosis patients – volume: 84 start-page: 245 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0030 article-title: Gait based recognition via fusing information from Euclidean and Riemannian manifolds publication-title: Pattern Recognit Lett doi: 10.1016/j.patrec.2016.10.012 – start-page: 3126 year: 2014 ident: 10.1016/j.artmed.2018.12.007_bib0070 article-title: Parkinson's disease assessment based on gait analysis using an innovative rgb-d camera system publication-title: 36th annual international conference of the IEEE engineering in medicine and biology society (EMBC) – volume: 25 start-page: 063019 issue: 6 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0035 article-title: Pose-based gait recognition with local gradient descriptors and hierarchically aggregated residuals publication-title: J Electron Imaging doi: 10.1117/1.JEI.25.6.063019 – volume: 34 start-page: 229 issue: 2 year: 2018 ident: 10.1016/j.artmed.2018.12.007_bib0055 article-title: Classification of gait anomalies from kinect publication-title: Vis Comput doi: 10.1007/s00371-016-1330-0 – start-page: 6 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0180 article-title: Co-occurrence feature learning for skeleton based action recognition using regularized deep lstm networks publication-title: AAAI, vol. 2 – volume: 51 start-page: 77 year: 2017 ident: 10.1016/j.artmed.2018.12.007_bib0115 article-title: Improved kinect-based spatiotemporal and kinematic treadmill gait assessment publication-title: Gait Posture doi: 10.1016/j.gaitpost.2016.10.001 – start-page: 397 year: 2017 ident: 10.1016/j.artmed.2018.12.007_bib0025 article-title: A fuzzy ontology-based system for gait recognition using kinect sensor – volume: 16 start-page: 194 issue: 2 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0020 article-title: Validity of the kinect for gait assessment: a focused review publication-title: Sensors doi: 10.3390/s16020194 – volume: 27 start-page: 765 issue: 7 year: 2007 ident: 10.1016/j.artmed.2018.12.007_bib0195 article-title: Gillette gait index as a gait analysis summary measure: comparison with qualitative visual assessments of overall gait publication-title: J Pediatr Orthop doi: 10.1097/BPO.0b013e3181558ade – volume: 4 start-page: 6 issue: 1 year: 2017 ident: 10.1016/j.artmed.2018.12.007_bib0045 article-title: Biomechanical parameters for gait analysis: a systematic review of healthy human gait publication-title: Phys Therapy Rehabil doi: 10.7243/2055-2386-4-6 – start-page: 6342 year: 2015 ident: 10.1016/j.artmed.2018.12.007_bib0120 article-title: Hidden Markov modeling of human pathological gait using laser range finder for an assisted living intelligent robotic walker – start-page: 1 year: 2015 ident: 10.1016/j.artmed.2018.12.007_bib0060 article-title: Abnormal gait detection with rgb-d devices using joint motion history features – volume: 40 start-page: 1021 issue: 4 year: 2010 ident: 10.1016/j.artmed.2018.12.007_bib0125 article-title: Action and gait recognition from recovered 3-d human joints publication-title: IEEE Trans Syst Man Cybern Part B (Cybern) doi: 10.1109/TSMCB.2010.2043526 – volume: 15 start-page: 155 issue: 2 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0210 article-title: A guideline of selecting and reporting intraclass correlation coefficients for reliability research publication-title: J Chiropr Med doi: 10.1016/j.jcm.2016.02.012 – volume: 16 start-page: 115 issue: 1 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0145 article-title: Deep convolutional and LSTM recurrent neural networks for multimodal wearable activity recognition publication-title: Sensors doi: 10.3390/s16010115 – start-page: 895 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0110 article-title: Learning shape variations of motion trajectories for gait analysis – volume: 9 start-page: 1735 issue: 8 year: 1997 ident: 10.1016/j.artmed.2018.12.007_bib0135 article-title: Long short-term memory publication-title: Neural Comput doi: 10.1162/neco.1997.9.8.1735 – start-page: 1964 year: 2012 ident: 10.1016/j.artmed.2018.12.007_bib0100 article-title: Full body gait analysis with kinect publication-title: Engineering in medicine and biology society (EMBC), annual international conference of the IEEE – volume: 10 issue: 10 year: 2015 ident: 10.1016/j.artmed.2018.12.007_bib0005 article-title: Kinematic validation of a multi-kinect v2 instrumented 10-meter walkway for quantitative gait assessments publication-title: PLOS ONE doi: 10.1371/journal.pone.0139913 – volume: 9 start-page: 81 issue: 1 year: 2012 ident: 10.1016/j.artmed.2018.12.007_bib0095 article-title: Comparison of walking overground and in a computer assisted rehabilitation environment (caren) in individuals with and without transtibial amputation publication-title: J Neuroeng Rehabil doi: 10.1186/1743-0003-9-81 – year: 2014 ident: 10.1016/j.artmed.2018.12.007_bib0170 – volume: 3 start-page: e918 year: 2015 ident: 10.1016/j.artmed.2018.12.007_bib0090 article-title: An elaborate data set on human gait and the effect of mechanical perturbations publication-title: PeerJ doi: 10.7717/peerj.918 – start-page: 106155B year: 2018 ident: 10.1016/j.artmed.2018.12.007_bib0160 article-title: LSTM for diagnosis of neurodegenerative diseases using gait data – year: 2010 ident: 10.1016/j.artmed.2018.12.007_bib0165 – volume: 31 start-page: 915 issue: 6–8 year: 2015 ident: 10.1016/j.artmed.2018.12.007_bib0040 article-title: Dtw-based kernel and rank-level fusion for 3d gait recognition using kinect publication-title: Vis Comput doi: 10.1007/s00371-015-1092-0 – start-page: 325 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0155 article-title: Learning effective gait features using LSTM – volume: 1 start-page: 30 issue: 1 year: 1996 ident: 10.1016/j.artmed.2018.12.007_bib0175 article-title: Forming inferences about some intraclass correlation coefficients publication-title: Psychol Methods doi: 10.1037/1082-989X.1.1.30 – start-page: 545 year: 2009 ident: 10.1016/j.artmed.2018.12.007_bib0140 article-title: Offline handwriting recognition with multidimensional recurrent neural networks publication-title: Advances in neural information processing systems – volume: 48 start-page: 2166 issue: 10 year: 2015 ident: 10.1016/j.artmed.2018.12.007_bib0015 article-title: Gait assessment using the microsoft xbox one kinect: concurrent validity and inter-day reliability of spatiotemporal and kinematic variables publication-title: J Biomech doi: 10.1016/j.jbiomech.2015.05.021 – volume: 17 start-page: 2301 issue: 10 year: 2017 ident: 10.1016/j.artmed.2018.12.007_bib0010 article-title: Validation of foot placement locations from ankle data of a kinect v2 sensor publication-title: Sensors doi: 10.3390/s17102301 – volume: 6 start-page: 284 issue: 4 year: 1994 ident: 10.1016/j.artmed.2018.12.007_bib0215 article-title: Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology publication-title: Psychol Assess doi: 10.1037/1040-3590.6.4.284 – volume: 33 start-page: 176 issue: 2 year: 2017 ident: 10.1016/j.artmed.2018.12.007_bib0050 article-title: Comparison of 3d joint angles measured with the kinect 2.0 skeletal tracker versus a marker-based motion capture system publication-title: J Appl Biomech doi: 10.1123/jab.2016-0107 – year: 2018 ident: 10.1016/j.artmed.2018.12.007_bib0080 – volume: 16 start-page: 1792 issue: 11 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0065 article-title: Skeleton-based abnormal gait detection publication-title: Sensors doi: 10.3390/s16111792 – year: 2017 ident: 10.1016/j.artmed.2018.12.007_bib0200 – start-page: 561 year: 2016 ident: 10.1016/j.artmed.2018.12.007_bib0205 article-title: Keep it SMPL: automatic estimation of 3d human pose and shape from a single image – start-page: 659 year: 2000 ident: 10.1016/j.artmed.2018.12.007_bib0185 article-title: Support vector method for multivariate density estimation publication-title: Advances in neural information processing systems – volume: 12 start-page: 2825 issue: October year: 2011 ident: 10.1016/j.artmed.2018.12.007_bib0190 article-title: Scikit-learn: machine learning in python publication-title: J Mach Learn Res – start-page: 153 year: 2014 ident: 10.1016/j.artmed.2018.12.007_bib0075 article-title: Online quality assessment of human movement from skeleton data publication-title: British 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| SubjectTerms | Adult Algorithms Computer Science Computer Simulation Computer Vision and Pattern Recognition Female Gait Gait assessment Gait modeling Humans Image Processing Kinect skeletons Low-limbs motion LSTM Male Models, Biological Monitoring, Physiologic RGB-D Technology for Human Learning Young Adult |
| Title | Normal and pathological gait classification LSTM model |
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