Estimating rehabilitation exercise recognition performance in sensing garments

Publication Type Journal Article
Authors Holger Harms, Oliver Amft, Gerhard Tröster
Title Estimating rehabilitation exercise recognition performance in sensing garments
Abstract A fundamental challenge limiting information quality obtained from smart sensing garments is the influence of textile movement relative to limbs. We present and validate a comprehensive modeling and simulation framework to predict recognition performance in casual loose-fitting garments. A statistical posture and wrinkle-modeling approach is introduced to simulate sensor orientation errors pertained to local garment wrinkles. A metric was derived to assess fitting, the body-garment mobility. We validated our approach by analyzing simulations of shoulder and elbow rehabilitation postures with respect to experimental data using actual casual garments. Results confirmed congruent performance trends with estimation errors below 4% for all study participants. Our approach allows to estimate the impact of fitting before implementing a garment and performing evaluation studies with it. These simulations revealed critical design parameters for garment prototyping, related to performed body posture, utilized sensing modalities, and garment fitting. We concluded that our modeling approach can substantially expedite design and development of smart garments through early-stage performance analysis.
Publication IEEE Transactions on Information Technology in Biomedicine
Volume 14
Issue 6
Pages 1436–1445
Date 2010
DOI 10.1109/TITB.2010.2076822
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Friedrich-Alexander-Universität Erlangen-Nürnberg