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Sensors 2013, 13(11), 14918-14953; doi:10.3390/s131114918

Design and Test of a Hybrid Foot Force Sensing and GPS System for Richer User Mobility Activity Recognition

School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK
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Received: 1 September 2013 / Revised: 10 October 2013 / Accepted: 25 October 2013 / Published: 1 November 2013
(This article belongs to the Collection Sensors for Globalized Healthy Living and Wellbeing)
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Abstract

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) and transportation mode simultaneously, and a relatively high computational complexity. Here, a new GPS and Foot-Force (GPS + FF) sensor method is proposed to overcome these challenges that leverages a set of wearable FF sensors in combination with GPS, e.g., in a mobile phone. User mobility activities that can be recognised include both daily user postures and common transportation modes: sitting, standing, walking, cycling, bus passenger, car passenger (including private cars and taxis) and car driver. The novelty of this work is that our approach provides a more comprehensive recognition capability in terms of reliably recognising both human posture and transportation mode simultaneously during travel. In addition, by comparing the new GPS + FF method with both an ACC method (62% accuracy) and a GPS + ACC based method (70% accuracy) as baseline methods, it obtains a higher accuracy (95%) with less computational complexity, when tested on a dataset obtained from ten individuals. View Full-Text
Keywords: mobility profiling; activity recognition; foot force sensor; GPS; accelerometer mobility profiling; activity recognition; foot force sensor; GPS; accelerometer
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Zhang, Z.; Poslad, S. Design and Test of a Hybrid Foot Force Sensing and GPS System for Richer User Mobility Activity Recognition. Sensors 2013, 13, 14918-14953.

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