Kinetic Twin. Generative anthropometric digital motion twins for kinetic sensor data synthesis

dc.contributorBrülisauer, Aaron
dc.date.accessioned2026-10-14T09:17:12Z
dc.description.abstractThe Kinetic Twin uses generative AI to create synthetic, clinically-conditioned human motion data. This innovation cuts the development time by ~70% for remote patient monitoring algorithms, e.g. assessing physical activity in obesity, by substituting costly real-life data collection campaigns.
dc.identifier.urihttps://irf.fhnw.ch/handle/11645/58359
dc.subjectICT
dc.subjecteHealth
dc.subjectDeep learning
dc.subjectMedtech
dc.subjectAI
dc.subject.ddc004 - Computer Wissenschaften, Internet
dc.subject.ddc610 - Medizin und Gesundheit
dc.titleKinetic Twin. Generative anthropometric digital motion twins for kinetic sensor data synthesis
dc.type00 - Projekt
dspace.entity.typeProject
fhnw.InventedHereYes
fhnw.Project.ContactKirschmann, Moritz
fhnw.Project.End2028-06-30
fhnw.Project.FinanceInnosuisse
fhnw.Project.ManagerKirschmann, Moritz
fhnw.Project.PartnersF. Hoffmann-La Roche AG
fhnw.Project.Start2026-07-01
fhnw.Project.Statelaufend
fhnw.Project.Typeangewandte Forschung
fhnw.affiliation.hochschuleHochschule für Informatik FHNWde_CH
fhnw.affiliation.institutInstitut für Data Science
fhnw.sap.referenceI336-0079-2
fhnw.strategicActionFieldFuture Health
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relation.isContributorOfProject.latestForDiscovery96bb539c-11ec-49d3-8306-934cd74bcbf6
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