Efficiency of the Memory Polynomial Model in Realizing Digital Twins for Gait Assessment

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dc.contributor.authorConte Alcaraz, Javier
dc.contributor.authorMoghaddamnia, Sanam
dc.contributor.authorFuhrwerk, Martin
dc.contributor.authorPeissig, Juergen
dc.date.accessioned2025-02-20T08:42:14Z
dc.date.available2025-02-20T08:42:14Z
dc.date.issued2019
dc.departmentTürk-Alman Üniversitesien_US
dc.description27th European Signal Processing Conference (EUSIPCO) -- SEP 02-06, 2019 -- A Coruna, SPAINen_US
dc.description.abstractOne of the key issues of multi-sensory digital healthcare and therapy is the reliability and user compliance of the applied sensor system. In the context of digital gait analysis and rehabilitation, different technologies have been proposed allowing objective gait assessment and precise quantification of the rehabilitation progress using Inertial Measurement Unit (IMU) platforms. However, this depends largely on the estimation accuracy of the kinematics (body joint angles). This paper presents the concept of a digital equivalent based on the Memory Polynomial Model (MPM) to reduce the number of IMUs needed for the measurements and to simulate the physical mechanism of lower body joint angles based on acceleration data. The MPM parameter estimation is based on the Least Square (LS) approach and is performed using accelerometer records of non-pathological gait patterns. The Normalized Mean Square Error (NMSE) is used to evaluate the performance of the model. According to the results an NMSE of -20 dB is achieved, which indicates the great potential of applying the MPM to develop a digital twin. That kind of twin can serve as a prototype of the physical counterpart to improve the wearability of the sensor system and to reduce physically induced measurement errors as well.
dc.description.sponsorshipEuropean Assoc Signal Proc,Univ Coruna,IEEE Signal Proc Soc,Xunta Galicia, Conselleria Cultura Educac, Oredenac Univ,Turismo A Coruna, Oficina Informac Tuursimo A Coruna,Off Navl Res Global,Xunta Galicia, Centro Investigac TIC,MathWorks,Natl Sci Fdn,Fundac Circulo Tecnologias Defensa Seguridad,Catedra UDC Everis Transformac Digital,Colexico Oficial Enxeneiros Telecomunicac Galicia,Inst Tecnologico Galicia
dc.identifier.doi10.23919/eusipco.2019.8903143
dc.identifier.isbn978-9-0827-9703-9
dc.identifier.issn2076-1465
dc.identifier.scopus2-s2.0-85075608110
dc.identifier.urihttps://doi.org/10.23919/eusipco.2019.8903143
dc.identifier.urihttps://hdl.handle.net/20.500.12846/1581
dc.identifier.wosWOS:000604567700463
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIeee
dc.relation.ispartof2019 27th European Signal Processing Conference (Eusipco)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250220
dc.subjectGait rehabilitationen_US
dc.subjectNonlinear time-varying modelingen_US
dc.subjectIMUen_US
dc.subjectMulti-sensor integrationen_US
dc.subjectDigital twinen_US
dc.subjectMachine learningen_US
dc.titleEfficiency of the Memory Polynomial Model in Realizing Digital Twins for Gait Assessment
dc.typeConference Object

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