Abstract
Step length (SL) is a fundamental parameter for the characterization of normal and pathologic gait. In particular, Freezing of Gait (FOG) in Parkinson’s Disease is a motor disorder associated with a markedly reduction of SL, hence this parameter has the potential to be used for FOG detection and monitoring. In this paper, we present a non-obtrusive and non-invasive architecture for the estimation of SL from trunk acceleration. We compared the reliability of our methodology with a stereophotogrammetric system, which is the gold standard for gait analysis. Preliminary experimental results on three healthy subjects are reported. Results show that the architecture could be employed to detect SL reduction prior to a FOG event.
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Pepa, L., Rossini, M., Spalazzi, L., Verdini, F. (2016). Step Length Estimation for Freezing of Gait Monitoring in Parkinsonian Patients. In: Conti, M., Martínez Madrid, N., Seepold, R., Orcioni, S. (eds) Mobile Networks for Biometric Data Analysis. Lecture Notes in Electrical Engineering, vol 392. Springer, Cham. https://doi.org/10.1007/978-3-319-39700-9_25
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DOI: https://doi.org/10.1007/978-3-319-39700-9_25
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