Turn detection and characterization with inertial sensors
Gespeichert in:
Deutscher übersetzter Titel: | Erkennung von Umkehrbewegungen und deren Charakterisierung mit Trägheitssensoren |
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Autor: | Pearson, Sean; Mancini, Martina; El-Gohary, Mahmoud; McNames, James; Horak, Fay |
Erschienen in: | icSPORTS 2013 : proceedings of the International Congress on Sports Science Research and Technology Support ; September 20-22, 2013, in Vilamoura, Algarve, Portugal |
Veröffentlicht: | Cham: Science and Technology Publications (Verlag), 2013, S. 19-22, Lit. |
Herausgeber: | International Congress on Sports Science Research and Technology Support |
Format: | Literatur (SPOLIT) |
Publikationstyp: | Sammelwerksbeitrag |
Medienart: | Elektronische Ressource (online) Gedruckte Ressource |
Dokumententyp: | Tagungsband |
Sprache: | Englisch |
DOI: | 10.5220/0004647000190022 |
Schlagworte: | |
Online Zugang: | |
Erfassungsnummer: | PU201609006439 |
Quelle: | BISp |
TY - COLL AU - Pearson, Sean A2 - Pearson, Sean A2 - Mancini, Martina A2 - El-Gohary, Mahmoud A2 - McNames, James A2 - Horak, Fay DB - BISp DP - BISp KW - Algorithmus KW - Analyse, biomechanische KW - Biomechanik KW - Feldversuch KW - Ganganalyse KW - Gleichgewichtsvermögen KW - Information, sensorische KW - Neurophysiologie KW - Richtungsänderung KW - Risikofaktor KW - Sporttechnologie KW - Sturz KW - Trägheitsmoment KW - Wearables LA - eng PB - Science and Technology Publications CY - Cham TI - Turn detection and characterization with inertial sensors TT - Erkennung von Umkehrbewegungen und deren Charakterisierung mit Trägheitssensoren PY - 2013 N2 - Turn detection and characterization in the home is important for continuous assessment of gait and balance in people with movement disability. Turning often results in falling in individuals with movement disorders. Researchers and clinicians would benefit from a system that identifies and characterizes their daily mobility behavior to predict their risk of falling, benefits or side effects of treatment, and progression of disease. The goal of this study is to develop an algorithm that is capable of reliably detecting turns during gait with the goal of applying it over long periods outside a lab environment. Performance of the algorithm is validated against an optical marker system and video analysis of a subset of the participants. L2 - http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=hPwF9E0rKD8=&t=1 L2 - https://dx.doi.org/10.5220/0004647000190022 DO - 10.5220/0004647000190022 SP - S. 19-22 BT - icSPORTS 2013 : proceedings of the International Congress on Sports Science Research and Technology Support ; September 20-22, 2013, in Vilamoura, Algarve, Portugal M3 - Elektronische Ressource (online) M3 - Gedruckte Ressource ID - PU201609006439 ER -