Investigating Inter-Subject and Inter-Activity Variations in Activity Recognition Using Wearable Motion Sensors | Zendy

Billur Barshan | Zendy; Aras Yurtman | Zendy

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Investigating Inter-Subject and Inter-Activity Variations in Activity Recognition Using Wearable Motion Sensors

Author(s) -

Billur Barshan,

Aras Yurtman

Publication year - 2015

Publication title -

the computer journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.319

H-Index - 64

eISSN - 1460-2067

pISSN - 0010-4620

DOI - 10.1093/comjnl/bxv093

Subject(s) - computer science , activity recognition , dynamic time warping , wearable computer , artificial intelligence , consistency (knowledge bases) , euclidean distance , set (abstract data type) , pattern recognition (psychology) , feature (linguistics) , similarity (geometry) , motion (physics) , machine learning , data mining , embedded system , linguistics , philosophy , image (mathematics) , programming language

This work investigates inter-subject and inter-activity variability of a given activity dataset and provides some new definitions to quantify such variability. The definitions are sufficiently general and can be applied to a broad class of datasets that involve time sequences or features acquired using wearable sensors. The study is motivated by contradictory statements in the literature on the ne...

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