{"id":613,"date":"2021-02-23T11:13:00","date_gmt":"2021-02-23T14:13:00","guid":{"rendered":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/?p=613"},"modified":"2025-09-16T16:26:18","modified_gmt":"2025-09-16T19:26:18","slug":"gait-event-detection-accuracy-effects-of-amputee-gait-pattern-terrain-and-algorithm-2","status":"publish","type":"post","link":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/2021\/02\/23\/gait-event-detection-accuracy-effects-of-amputee-gait-pattern-terrain-and-algorithm-2\/","title":{"rendered":"Evaluation of the offline classification error of human locomotion modes using virtual force-sensing resistor data"},"content":{"rendered":"\n

C. M. Lara-Barrios; P.\u00a0Catalfamo Formento; E. Mu\u00f1oz Larrosa; A. Blanco-Ortega<\/h3>\n\n\n\n

IEEE Xplore<\/em><\/strong><\/h5>\n\n\n\n

Abstract<\/h4>\n\n\n\n

Active lower limb assistive devices are intended to contribute to human movement activities such as locomotion.While some devices are capableto function among a variety of terrains (i.e. level surfaces, inclines, or stairs), wideinstrumentation sets (combining mechanical and bio-signal data) have been usually applied to minimize classification errors for locomotion mode recognition, even if this potentially bias user comfort. Hence, a selection of parameters for classification with limited sensor data could represent a milestone on the development of comfortable lower-limb assistive devices. <\/p>\n\n\n\n

The objective of this study was to find the best combination of parameters for the offline classification of five locomotion modes based on data from discrete areas on a pressure insole. Three virtual force-sensing resistor sensors were located under heel and forefoot regions of six subjectswithout discernible gait abnormalities to study the potential of kineticsignals for locomotion-mode recognition. Parametric tests were used to compare the effect of two types of data, four time-windows and the combinations within five data features on the classification error of linear discriminant analysis classifiers for steady-state gait. Statistical comparisons were made using classification errors measured through five-fold cross-validation. Results showed that the best overall classifier had an average classification error of 7.85\u00b14.76%.Our results were in close resemblance with
related studies which relied on larger sensor sets as their instrumentation strategies. This method presents an insight about the use of a reduced number of sensors for accurate locomotion mode classification on the development of comfortable lower limb assistive devices.<\/p>\n\n\n\n

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Fig. 2: Average level walking gait cycles from threev-FSRs for activearea (top) and raw (bottom)signals.Normalizedcycle at 0% is defined by initial foot contact.Signal saturation is observed on active area signals during stance phase. H: heel, M1: first metatarsal head, M5: fifth metatarsal head.<\/figcaption><\/figure>\n\n\n\n
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C. M. Lara-Barrios; P.\u00a0Catalfamo Formento; E. Mu\u00f1oz Larrosa; A. Blanco-Ortega IEEE Xplore Abstract Active lower limb assistive devices are intended to contribute to human movement activities such as locomotion.While some devices are capableto function among a variety of terrains (i.e. level surfaces, inclines, or stairs), wideinstrumentation sets (combining mechanical and bio-signal data) have been usually […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"footnotes":""},"categories":[7],"tags":[18],"class_list":["post-613","post","type-post","status-publish","format-standard","hentry","category-publicaciones","tag-18"],"_links":{"self":[{"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/posts\/613","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/comments?post=613"}],"version-history":[{"count":5,"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/posts\/613\/revisions"}],"predecessor-version":[{"id":835,"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/posts\/613\/revisions\/835"}],"wp:attachment":[{"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/media?parent=613"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/categories?post=613"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ingenieria.uner.edu.ar\/nucleos\/movimiento_humano\/index.php\/wp-json\/wp\/v2\/tags?post=613"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}