Abstract: A device for analyzing the regularity and symmetry of a sequence of N gait or running cycles of a person, comprising sensors for measuring raw time signals of a physical movement variable of a body segment, a processing unit connected to the sensors for measuring and configured to separate the raw time signals into distinct time signals Ci, the Ci series being associated with a given gait or running cycle i of the person, to calculate at least one similarity coefficient between the signal Ci associated with gait or running cycle i and another signal Cj associated with a gait or running cycle j of the person. A display is configured to display the matrix M(i,j) with each value of the similarity coefficient shown in the matrix M(i,j) in color to form a graduated color scale indicating the similarity between the gait or running cycles i and j.

Abstract: A method is provided for characterising a gait comprising steps of: receiving a signal measuring the movement of a target subject measured beforehand; comparing (204) at least one section of the measuring signal with a plurality of reference signals, the plurality of reference signals comprising at least one movement signal measured beforehand on a reference subject different from the target subject, each comparison of the measuring signal with a reference signal producing a similarity coefficient representative of a probability of similarity between the compared signals; and selecting (208) at least one local maximum of interest among the similarity coefficients produced, wherein the plurality of reference signals comprises at least one movement signal measured beforehand on a reference subject afflicted with a gait disorder, and at least one movement signal measured beforehand on a healthy reference object.

Abstract: The present invention concerns a device 1 for analysing the regularity and symmetry of a sequence of N gait or running cycles of a person, comprising measurement sensors 2 for measuring raw time signals of a physical movement variable of a body segment, a processing unit connected to the measurement sensors 2 and having calculation and processing means set up to separate the raw time signals into distinct time signals Ci, the Ci series being associated with a given gait or running cycle i of the person, to calculate at least one similarity coefficient between the signal Ci associated with gait or running cycle i and another signal Cj associated with a gait or running cycle j of the same person, display means 4 connected to the processing unit and displaying the matrix M(i,j) with each value of the similarity coefficient shown in the matrix M(i,j) by a colour in a graduated colour scale to make it possible for the similarity between the gait or running cycles i and j to be seen with the naked eye.

Abstract: A method is provided for characterising a gait comprising steps of: receiving a signal measuring the movement of a target subject measured beforehand; comparing (204) at least one section of the measuring signal with a plurality of reference signals, the plurality of reference signals comprising at least one movement signal measured beforehand on a reference subject different from the target subject, each comparison of the measuring signal with a reference signal producing a similarity coefficient representative of a probability of similarity between the compared signals; and selecting (208) at least one local maximum of interest among the similarity coefficients produced, wherein the plurality of reference signals comprises at least one movement signal measured beforehand on a reference subject afflicted with a gait disorder, and at least one movement signal measured beforehand on a healthy reference object.