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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; in revised form: 10 October 2013 / Accepted: 25 October 2013 / Published: 1 November 2013
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.
Keywords: mobility profiling; activity recognition; foot force sensor; GPS; accelerometer
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MDPI and ACS Style
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.
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(11):14918-14953.
Zhang, Zelun; Poslad, Stefan. 2013. "Design and Test of a Hybrid Foot Force Sensing and GPS System for Richer User Mobility Activity Recognition." Sensors 13, no. 11: 14918-14953.