title: Design and test of a hybrid foot force sensing and GPS system for richer user mobility activity recognition.
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.
authors.affiliation: School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK. zelun.zhang@qmul.ac.uk.
authors.forename: Zelun
authors.initials: Z
authors.lastname: Zhang
authors.forename: Stefan
authors.initials: S
authors.lastname: Poslad
mesh_terms: D061725:Accelerometry / Q000295:instrumentation*; D000328:Adult; D004867:Equipment Design; D005260:Female; D005528:Foot / Q000502:physiology*; D040362:Geographic Information Systems / Q000295:instrumentation*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D016138:Walking / Q000145:classification / Q000502:physiology*