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Session: Poster session 2 (Odd numbers)
Session starts: Friday 27 January, 10:00
Presentation starts: 10:00

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Joël Karel (Maastricht University, Department of Advanced Computing Sciences)
Elena Heinze ()
Ralf Peeters (Maastricht University, Department of Advanced Computing Sciences)
Pietro Bonizzi (Maastricht University, Department of Advanced Computing Sciences)

Abstract:
Recurrence Plots (RP) are a tool for investigating and visualizing recurrent behaviour in dynamical systems. RP were originally designed for dealing with univariate signals. However, when measuring gait, typically three-axial accelerometers are used. In such a case it may be more convenient to create a multivariate RP instead of creating a separate RP for each of the accelerometer signals. A multivariate RP takes into account the redundant information of all given signals simultaneously and combines it in the same plot. In this respect, it is reasonable to think that a multivariate RP should be better equipped to capture the recurrent behaviour of a system than its univariate counterpart, when more signals are available from the system. To test this hypothesis, we analysed 20 seconds of gait of a healthy subject from the Long Term Movement Monitoring Database from Physionet, where there is a portion of gait of 13 seconds. For the univariate RP, the vertical of the accelerometer was used as this is the direction in which the gait is expected to reflect the most. For the multivariate RP, all three axes of the accelerometer were employed. This is illustrated below, where from left to right the univariate and the multivariate (using submatrix comparison) thresholded (epsilon=0.10) RPs are provided. It can be observed that the multivariate RP expresses the recurrent behavior more strongly as shown by the diagonal lines. At the same time, the noise in the plot decreases when using multivariate RPs. Hence, this explorative study gives indications that the use of multivariate RP may be beneficial for the analysis of 3D accelerometer signals, and for the joint analysis of multiple signals from the same system.