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Sekine, M., Tamura, Akay, M.T., Fujimoto, T., Togawa, and Fukui, Y. (2002) Discrimination of gait patterns using wavelet-based fractal analysis. IEEE transactions on Neural Systems and Rehabilitation Engineering, 10-3, 188-196. v Waarsing, J.H., Mayagoitia, R.E. and Veltink, P.H (1996) Quantifying the stability of gait using accelerometers. In 18th Annual International Conference of the IEEE Engi-neering in Medicine and Biology Society, Amsterdam. utilisation d'accéléros pour quantifier la marche.

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• TITLE: Gait spectral index (GSI): a new quantification method for assessing human gait

  AUTHORS: Rodolphe Héliot, Christine Azevedo-Coste, Laszlo Schwirtlich, Bernard Espiau

  KEYWORDS: Gait Evaluation; Walk Training; Accelerometer; Spectral Analysis

  JOURNAL NAME: Health, Vol.2 No.1, January 15, 2010

  ABSTRACT: This paper introduces a simple, quantitative as-sessment tool to follow up the recovery of gait. Today, micro-electro-mechanical systems (MEMS) technology provides with small, simple, low-pow- er consuming and easy to don and doff sensors. In our approach we have selected an accelerome- ter and introduced a new quantity that charac-terizes the gait pattern in the frequency domain, we term it Gait Spectral Index (GSI). GSI allows assessing gait quality and closely relates to the speed and cadence of gait (dynamics). We have tested the GSI approach to quantify the quality of the gait of healthy young and elderly, and post- stroke hemiplegic individuals. We investigated the repeatability and coherence of GSI in healthy individuals (young and elderly) and contrasted this to the post-stroke hemiplegic individuals. We found that high correlation of the GSI with conventional gait parameters. This suggests that GSI, which needs only data from one acceler-ometer, could be an objective quantitative mea- sure of the quality of the walking thereby a sim- ple yet reliable measure of the recovery of func-tion during neuronrehabilitation.