Robust Step Detection in Mobile Phones Through a Learning Process Carried Out in the Mobile
In this paper we describe an strategy to obtain a robust pedometer in mobile phones through a learning process that is carried out in the mobile itself. Using the vertical component of the acceleration, dynamic time warping and data collected on the mobile, we achieve a model able to detect steps and which exhibits an important robustness to the way the mobile is being carried out. We believe this robustness is due to the fact that the model, learnt on the mobile, requires less heuristic parameters and is linked to specific characteristics of the user and the hardware. We have tested our strategy in real experiments carried out at our research centre.
This work has received financial support from the Consellería de Cultura, Educación en Ordenación Universitaria (accreditation 2016–2019, ED431G/08 and reference competitive group 2014–2017 GRC2014/030) and the European Regional Development Fund (ERDF).
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