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Pubmed for Handhelds

PUBMED FOR HANDHELDS

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  • Title: Human Activity Recognition from Smart-Phone Sensor Data using a Multi-Class Ensemble Learning in Home Monitoring.
    Author: Ghose S, Mitra J, Karunanithi M, Dowling J.
    Journal: Stud Health Technol Inform; 2015; 214():62-7. PubMed ID: 26210419.
    Abstract:
    Home monitoring of chronically ill or elderly patient can reduce frequent hospitalisations and hence provide improved quality of care at a reduced cost to the community, therefore reducing the burden on the healthcare system. Activity recognition of such patients is of high importance in such a design. In this work, a system for automatic human physical activity recognition from smart-phone inertial sensors data is proposed. An ensemble of decision trees framework is adopted to train and predict the multi-class human activity system. A comparison of our proposed method with a multi-class traditional support vector machine shows significant improvement in activity recognition accuracies.
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