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    A Gyroscope Based Accurate Pedometer Algorithm

    Access Status
    Fulltext not available
    Authors
    Jayalath, S.
    Abhayasinghe, Nimsiri
    Murray, Iain
    Date
    2013
    Type
    Conference Paper
    
    Metadata
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    Citation
    Jayalath, Sampath and Abhayasinghe, Nimsiri and Murray, Iain. 2013. A Gyroscope Based Accurate Pedometer Algorithm, in Proceedings of the 4th International Conference on Indoor Positioning and Indoor Navigation, Oct 28-31 2013, pp. 510-513. Montbellard, France: Université de Franche-Comté.
    Source Title
    Proceedings of 2013 International Conference on Indoor Positioning and Indoor Navigation
    Source Conference
    2013 International Conference on Indoor Positioning and Indoor Navigation
    ISBN
    978-1-4799-4043-1
    URI
    http://hdl.handle.net/20.500.11937/14986
    Collection
    • Curtin Research Publications
    Abstract

    Accurate step counting is important in pedometer based indoor localization. Existing step detection techniques are not sufficiently accurate, especially at low walking speeds that are commonly observed when navigating unfamiliar environments. This is more critical when vision impaired indoor navigation is considered due to the fact that they have relatively low walking speeds. Almost all existing pedometer techniques use accelerometer data to identify steps, which is not very accurate at low walking speeds. This paper describes a gyroscope based pedometer algorithm implemented in a smartphone. The smartphone is placed in the pocket of the trouser, which is a usual carrying position of the mobile phone. The gyroscope sensor data is used for the identification of steps. The algorithm was designed to demand minimal computational resources so that it can be easily implemented in an embedded platform. Raw data from the sensor are filtered using a 6th order Butterworth filter for noise reduction. This is then sent though a zero crossing detector which identifies the steps. A minimum delay between two consecutive zero crossings was used to avoid fluctuations being counted and peak detection was used to validate steps. The algorithm has a calibration mode, in which the absolute minimum swing of data is learnt to set the threshold. This approach demonstrated accuracies above 96% even at slow walking speeds on flat land, above 95% when walking up/down hills and above 90% when going up/down stairs. This has supported the concept that the gyroscope can be used efficiently in step identification for indoor positioning and navigation systems.

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