5th International ICST Conference on Pervasive Computing Technologies for Healthcare

Research Article

A novel approach for assessing gait using foot mounted accelerometers

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  • @INPROCEEDINGS{10.4108/icst.pervasivehealth.2011.246061,
        author={Matt Patterson and Brian Caulfield},
        title={A novel approach for assessing gait using foot mounted accelerometers},
        proceedings={5th International ICST Conference on Pervasive Computing Technologies for Healthcare},
        publisher={IEEE},
        proceedings_a={PERVASIVEHEALTH},
        year={2012},
        month={4},
        keywords={gait total acceleration accelerometer foot swing phase feature detection},
        doi={10.4108/icst.pervasivehealth.2011.246061}
    }
    
  • Matt Patterson
    Brian Caulfield
    Year: 2012
    A novel approach for assessing gait using foot mounted accelerometers
    PERVASIVEHEALTH
    ICST
    DOI: 10.4108/icst.pervasivehealth.2011.246061
Matt Patterson1,*, Brian Caulfield1
  • 1: Clarity Centre for Sensor Web Technologiesб University College Dublinб Belfield, Dublin 4, Republic of Ireland
*Contact email: matt.patterson@ucd.ie

Abstract

Accelerometer technology is becoming increasingly smaller and cheaper to develop. As a result such devices can easily be integrated into a shoe to ubiquitously capture gait information which could potentially be used to detect development of injuries or neuro-degenerative diseases. Much research has been done comparing accelerometer data to kinematic and spatio-temporal data; however little has been done investigating what insights into normal and dysfunctional gait patterns accelerometer data from the foot can provide. It is important to first gain an understanding of how foot accelerometer data behaves during healthy gait before developing methods to assess dysfunctional gait with such a tool. In this preliminary study we have analyzed data harnessed from tri-axial accelerometers mounted on the dorsi of the feet in 6 healthy subjects walking at different speeds to hypothesize what insights into movement and motor control accelerometer data output alone can provide. Results indicate that peak acceleration during initial swing, mean acceleration during mid-swing and acceleration at initial contact are features that distinguish between walking velocities. These results suggest that quantifying specific acceleration patterns during gait may one day be useful to cheaply and easily detect gait pattern changes due to disease or injury. Though these preliminary results are promising, further work is required to investigate the utility of accelerometer use in a patient population.