2015
DOI: 10.9781/ijimai.2015.357
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Step Characterization using Sensor Information Fusion and Machine Learning

Abstract: -A pedestrian inertial navigation system is typically used to suppress the Global Navigation Satellite System limitation to track persons in indoor or in dense environments. However, lowcost inertial systems provide huge location estimation errors due to sensors and pedestrian dead reckoning inherent characteristics. To suppress some of these errors we propose a system that uses two inertial measurement units spread in person's body, which measurements are aggregated using learning algorithms that learn the ga… Show more

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Cited by 2 publications
(1 citation statement)
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“…The new API presented allows to develop new real-time collaborative web applications in both JavaScript and Java environments Anacleto, R. Et al. [7] shows a pedestrian inertial navigation system that is typically used to suppress the Global Navigation Satellite System limitation to track persons in indoor or in dense environments. They propose a system that uses two inertial measurement units spread in person's body, which measurements are aggregated using learning algorithms that learn the gait behaviors.…”
mentioning
confidence: 99%
“…The new API presented allows to develop new real-time collaborative web applications in both JavaScript and Java environments Anacleto, R. Et al. [7] shows a pedestrian inertial navigation system that is typically used to suppress the Global Navigation Satellite System limitation to track persons in indoor or in dense environments. They propose a system that uses two inertial measurement units spread in person's body, which measurements are aggregated using learning algorithms that learn the gait behaviors.…”
mentioning
confidence: 99%