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  • 1.
    Sant'Anna, Anita
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Wickström, Nicholas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    A Symbol-Based Approach to Gait Analysis From Acceleration Signals: Identification and Detection of Gait Events and a New Measure of Gait Symmetry2010In: IEEE transactions on information technology in biomedicine, ISSN 1089-7771, E-ISSN 1558-0032, Vol. 14, no 5, p. 1180-1187Article in journal (Refereed)
    Abstract [en]

    Gait analysis can convey important information about one’s physical and cognitive condition. Wearable inertial sensor systems can be used to continuously and unobtrusively assess gait during everyday activities in uncontrolled environments. An important step in the development of such systems is the processing and  analysis of the sensor data. This paper presents a symbol-based method used to detect the phases of gait and convey important dynamic information from accelerometer signals. The addition of expert knowledge substitutes the need for supervised learning techniques, rendering the system easy to interpret and easy to improve incrementally. The proposed method is compared to an approach based on peak-detection. A new symbol-based symmetry index is created and compared to a traditional temporal symmetry index and a symmetry measure based on cross-correlation. The symbol-based symmetry index exemplifies how the proposed method can extract more information from the acceleration signal than previous approaches

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