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A benchmark dataset to evaluate sensor displacement in activity recognition

Publication Type Conference Paper
Authors Oresti Banos Legran, Miguel Damas, Hector Pomares, Ignacio Rojas, Mate Toth, Oliver Amft
Title A benchmark dataset to evaluate sensor displacement in activity recognition
Abstract This work introduces an open benchmark dataset to investigate inertial sensor displacement effects in activity recognition. While sensor position displacements such as rotations and translations have been recognised as a key limitation for the deployment of wearable systems, a realistic dataset is lacking. We introduce a concept of gradual sensor displacement conditions, including ideal, self-placement of a user, and mutual displacement deployments. These conditions were analysed in the dataset considering 33 fitness activities, recorded using 9 inertial sensor units from 17 participants. Our statistical analysis of acceleration features quantified relative effects of the displacement conditions. We expect that the dataset can be used to benchmark and compare recognition algorithms in the future.
Date 2012
Proceedings Title SAGAware 2012: International Workshop on Situation, Activity and Goal Awareness
Publisher ACM
Pages 1026–1055
DOI 10.1145/2370216.2370437
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