title: A multivariate time-warping based classifier for gesture recognition with wearable strain sensors.
abstract: Conductive elastomer elements can be industrially embedded into garments to form unobtrusive strain sensing stripes. The present article outlines the structure of a strain-sensor based gesture detection algorithm. Current sensing prototypes include several dozens of sensors; their redundancy with respect to the limb's degrees of freedom, and other artifacts implied by this measurement technique, call for the development of novel robust multivariate pattern-matching techniques. The algorithm's construction is explained, and its performances are evaluated in the context of motor rehabilitation exercises for both two-class and multi-class tasks.
authors.affiliation: Laboratory for Biomedical Informatics, Dipartimento di Informatica e Sistemistica, Università di Pavia, Italy. toni.giorgino@unipv.it
authors.forename: Toni
authors.initials: T
authors.lastname: Giorgino
authors.forename: Paolo
authors.initials: P
authors.lastname: Tormene
authors.forename: Silvana
authors.initials: S
authors.lastname: Quaglini
mesh_terms: D000465:Algorithms; D015374:Biosensing Techniques; D003020:Clothing; D020724:Elastomers; D004594:Electrophysiology; D015444:Exercise; D005868:Gestures; D006801:Humans; D015999:Multivariate Analysis; D010363:Pattern Recognition, Automated; D021641:Recognition, Psychology; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors
chemical_list: D020724:Elastomers