Predicting Transitioning Walking Gaits: Hip and Knee Joint Trajectories From the Motion of Walking Canes
In recent years, wearable exoskeletons and powered prosthetics have been considered key elements to remedy mobility loss. One of the main challenges pertaining to this field is the prediction of the wearer's desired motion. In this paper, we perform a human locomotion analysis, and we investiga...
Saved in:
Published in | IEEE transactions on neural systems and rehabilitation engineering Vol. 27; no. 9; pp. 1791 - 1800 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.09.2019
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | In recent years, wearable exoskeletons and powered prosthetics have been considered key elements to remedy mobility loss. One of the main challenges pertaining to this field is the prediction of the wearer's desired motion. In this paper, we perform a human locomotion analysis, and we investigate the accuracy of predicting the angular position of the lower limb joints from the motion of walking canes. Nine healthy subjects took part of this study and performed a locomotor task that comprised straight walking on flat ground, stair ascent, and upright resting posture. Recurrent Neural Networks and polynomial fitting using Least Squares were used to model dynamic and static non-linear mappings, respectively, between the motion of a cane and its contra-lateral leg joints. A successful prediction of both the hip and knee joints was achieved using information from the cane only, and significant improvement of the prediction error was realized through the addition of data from the arm joints. Overall, Recurrent Neural Networks outperformed Least Squares for both joints' angular position prediction. When using the cane only, the static maps were able to predict steady behaviour but failed in predicting transitioning, as opposed to RNN, which was able to capture both steady behaviour and transitions. |
---|---|
AbstractList | In recent years, wearable exoskeletons and powered prosthetics have been considered key elements to remedy mobility loss. One of the main challenges pertaining to this field is the prediction of the wearer's desired motion. In this paper, we perform a human locomotion analysis, and we investigate the accuracy of predicting the angular position of the lower limb joints from the motion of walking canes. Nine healthy subjects took part of this study and performed a locomotor task that comprised straight walking on flat ground, stair ascent, and upright resting posture. Recurrent Neural Networks and polynomial fitting using Least Squares were used to model dynamic and static non-linear mappings, respectively, between the motion of a cane and its contra-lateral leg joints. A successful prediction of both the hip and knee joints was achieved using information from the cane only, and significant improvement of the prediction error was realized through the addition of data from the arm joints. Overall, Recurrent Neural Networks outperformed Least Squares for both joints' angular position prediction. When using the cane only, the static maps were able to predict steady behaviour but failed in predicting transitioning, as opposed to RNN, which was able to capture both steady behaviour and transitions. |
Author | Sinclair, Peter J. Manchester, Ian R. Mounir Boudali, A. |
Author_xml | – sequence: 1 givenname: A. orcidid: 0000-0002-2737-581X surname: Mounir Boudali fullname: Mounir Boudali, A. email: m.boudali@acfr.usyd.edu.au organization: Australian Center for Field Robotics, School of Aerospace, Mechanical, and Mechatronic Engineering, The University of Sydney, Sydney, NSW, Australia – sequence: 2 givenname: Peter J. orcidid: 0000-0002-3957-9561 surname: Sinclair fullname: Sinclair, Peter J. organization: Faculty of Health Science, The University of Sydney, Sydney, NSW, Australia – sequence: 3 givenname: Ian R. orcidid: 0000-0002-7035-3173 surname: Manchester fullname: Manchester, Ian R. organization: Australian Center for Field Robotics, School of Aerospace, Mechanical, and Mechatronic Engineering, The University of Sydney, Sydney, NSW, Australia |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31398125$$D View this record in MEDLINE/PubMed |
BookMark | eNo9j8tOwzAQRS1URB_wAyAh_0CKx44Tmx2q-gDKQ1DEsnLsKXVpnSgOC_4eokJXd67m6Ei3TzqhDEjIObAhANNXi8fXl_GQM9BDroVQOjsiPZBSJYwD67S3SJNUcNYl_Rg3jEGeyfyEdAUIrYDLHlk_1-i8bXz4oIvahOgbX4a2vZvtZ5tT45t4TWe-oiY4eh8Q6V3pQ9PyG7RNWXuMdFKXO9qskT6UrYGWq4NhZALGU3K8MtuIZ385IG-T8WI0S-ZP09vRzTyxQkKTcHQikzJ1LLWSA3fCILeFUpgaQJ0aKwoLiErp3ClhM72yRtoMC6sydFIMyOXeW30VO3TLqvY7U38v_yf_Ahd7wCPi4a1yzQEy8QNlgGUe |
CODEN | ITNSB3 |
CitedBy_id | crossref_primary_10_1109_ACCESS_2021_3104464 crossref_primary_10_1002_aisy_202200361 crossref_primary_10_3390_s24010211 crossref_primary_10_3389_fbioe_2024_1358022 crossref_primary_10_1007_s11517_021_02335_9 crossref_primary_10_1109_TNSRE_2021_3107780 crossref_primary_10_1016_j_bspc_2020_102279 crossref_primary_10_1109_TASE_2022_3185706 crossref_primary_10_3390_act11030073 |
ContentType | Journal Article |
DBID | 97E RIA RIE CGR CUY CVF ECM EIF NPM |
DOI | 10.1109/TNSRE.2019.2933896 |
DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Xplore Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed |
DatabaseTitle | MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) |
DatabaseTitleList | MEDLINE |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 3 dbid: RIE name: IEEE Electronic Library Online url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Occupational Therapy & Rehabilitation |
EISSN | 1558-0210 |
EndPage | 1800 |
ExternalDocumentID | 31398125 8792116 |
Genre | orig-research Research Support, Non-U.S. Gov't Journal Article |
GrantInformation_xml | – fundername: Australian Research Council funderid: 10.13039/501100000923 |
GroupedDBID | --- -~X 0R~ 29I 4.4 53G 5GY 5VS 6IK 97E AAFWJ AAJGR ABVLG ACGFO ACGFS ACIWK ACPRK AENEX AETIX AFPKN AFRAH AIBXA ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD F5P GROUPED_DOAJ HZ~ H~9 IFIPE IPLJI JAVBF LAI M43 O9- OCL OK1 P2P RIA RIE RIG RNS CGR CUY CVF ECM EIF NPM |
ID | FETCH-LOGICAL-c351t-2ed36554d04c5212d3ae2cb88e4a1e94ac3bc1ee8897d83c69fca5c6ebc86ed53 |
IEDL.DBID | RIE |
ISSN | 1534-4320 |
IngestDate | Sat Sep 28 08:26:44 EDT 2024 Mon Nov 04 12:06:19 EST 2024 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 9 |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c351t-2ed36554d04c5212d3ae2cb88e4a1e94ac3bc1ee8897d83c69fca5c6ebc86ed53 |
ORCID | 0000-0002-2737-581X 0000-0002-3957-9561 0000-0002-7035-3173 |
PMID | 31398125 |
PageCount | 10 |
ParticipantIDs | ieee_primary_8792116 pubmed_primary_31398125 |
PublicationCentury | 2000 |
PublicationDate | 2019-09-01 |
PublicationDateYYYYMMDD | 2019-09-01 |
PublicationDate_xml | – month: 09 year: 2019 text: 2019-09-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | United States |
PublicationPlace_xml | – name: United States |
PublicationTitle | IEEE transactions on neural systems and rehabilitation engineering |
PublicationTitleAbbrev | TNSRE |
PublicationTitleAlternate | IEEE Trans Neural Syst Rehabil Eng |
PublicationYear | 2019 |
Publisher | IEEE |
Publisher_xml | – name: IEEE |
SSID | ssj0017657 |
Score | 2.404388 |
Snippet | In recent years, wearable exoskeletons and powered prosthetics have been considered key elements to remedy mobility loss. One of the main challenges pertaining... |
SourceID | pubmed ieee |
SourceType | Index Database Publisher |
StartPage | 1791 |
SubjectTerms | Adult Algorithms Biomechanical Phenomena Canes data analysis Exoskeletons Female Gait - physiology gait trajectory prediction Hip Hip - physiology Humans Knee Joint - physiology Least-Squares Analysis Legged locomotion Lower Extremity - physiology lower limb rehabilitation Male Neural Networks, Computer Posture - physiology Robot sensing systems system identification Task analysis Trajectory Walking - physiology Young Adult |
Title | Predicting Transitioning Walking Gaits: Hip and Knee Joint Trajectories From the Motion of Walking Canes |
URI | https://ieeexplore.ieee.org/document/8792116 https://www.ncbi.nlm.nih.gov/pubmed/31398125 |
Volume | 27 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LT9tAEB6RnHopLVBeBe2h5VSHJPvwbm8oIkRUiRANghvaXY9FeNgodS78-s6unYiiHrhZttda7axnvp3HNwDfpHN0NpHdJHfSJiIXgvSg6iWkBi0X2kjuYpbvRI2uxPmNvFmDH6taGESMyWfYCZcxlp-VfhFcZcc6NXReUS1opUbVtVqriEGqIqsn_cAiEbzfXRbIdM3xdPL78jRkcZkOGTey0KFvESfoQ8ZNNl1V3qDKaF2G6zBezqtOKnnoLCrX8S9vKBvfO_FP8LGBmeyk3hefYQ2LDfj-mlKYTWs-AXbELv9h696Eu4t5CN-EhGgWbdms8dqya_sYXOvszM6qPz_ZaPbMbJGxXwUiOy9nRRXev4-BADqBs-G8fGKEMNk49gpiZb76wsCSjt2Cq-HpdDBKmo4MieeyVyV9zLgiAJJ1hQ9Fvxm32PdOaxS2h0ZYz53vIWpt0kxzr0zurfQKndcKM8m_QLsoC9wBxgm5uNykxlktvNXWOJflNNpbupnaXdgM63j7XJNu3DZLuAvbtZxWD5aC3Pv_gH34ECRfp4V9hXY1X-AB4YjKHUJrcjE-jNvoL6ddxs8 |
link.rule.ids | 314,780,784,796,27924,27925,54758 |
linkProvider | IEEE |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LT-MwEB6xcIALyxuWXfABOJHS1nZi7w0hSnm0QlAEt8p2JqL7SFA3veyvZ-ykFYs47C1K4siyJzOfZ76ZATiQ1tLZRDajzEoTiUwI0oNxKyI1aLhQWnIbWL79uPsgrp7k0xwcz3JhEDGQz7DhL0MsPy3cxLvKTlSi6bwSf4IFKQjnVtlas5hBEoe6nvQLi0jwdnOaItPUJ4P-_d2553HpBpk3stG-cxEn8EPmTdZ9Vd7hymBfOp-hN51ZRSv52ZiUtuH-viva-L9TX4HlGmiy00oyVmEO8zU4fFtUmA2qigLsiN39U697HZ5vxz6A4ynRLFizUe23ZY_ml3euswszKv98Z93RCzN5yq5zRHZVjPLSv_8jhALoDM464-I3I4zJeqFbECuy2RfODGnZDXjonA_OulHdkyFyXLbKqI0pjwmCpE3hfNpvyg22nVUKhWmhFsZx61qISukkVdzFOnNGuhitUzGmkm_CfF7kuA2ME3axmU60NUo4o4y2Ns1otDN0MzE7sO7XcfhSld0Y1ku4A1vVPs0eTDfyy8cD9mGxO-jdDG8u-9e7sOSloCKJfYX5cjzBb4QqSrsXhOkVlHDJFg |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Predicting+Transitioning+Walking+Gaits%3A+Hip+and+Knee+Joint+Trajectories+From+the+Motion+of+Walking+Canes&rft.jtitle=IEEE+transactions+on+neural+systems+and+rehabilitation+engineering&rft.au=Mounir+Boudali%2C+A.&rft.au=Sinclair%2C+Peter+J.&rft.au=Manchester%2C+Ian+R.&rft.date=2019-09-01&rft.pub=IEEE&rft.issn=1534-4320&rft.volume=27&rft.issue=9&rft.spage=1791&rft.epage=1800&rft_id=info:doi/10.1109%2FTNSRE.2019.2933896&rft_id=info%3Apmid%2F31398125&rft.externalDocID=8792116 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1534-4320&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1534-4320&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1534-4320&client=summon |