Locogram software: tool for analysing gait exercises

Patent metadata

Field	Value
Publication number	US-11253172-B2
Application number	US-201816476484-A
Country	US
Kind code	B2
Filing date	Jan 9, 2018
Priority date	Jan 10, 2017
Publication date	Feb 22, 2022
Grant date	Feb 22, 2022

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.

First claim

The invention claimed is:

1. A method for providing, by a visual representation:
a temporal analysis of a regularity and symmetry of a sequence of N gait or running cycles of the same a person, by comparing each cycle taken individually with each of the other cycles taken individually,
and a determination of a presence and number of erratic cycles as well as a number of cycles necessary to establish gait or running rhythms, and at what point these erratic gait cycles and rhythms are reached, the method comprising the following steps:
a measurement step (i) for measuring raw time signals using sensors that relate to a physical movement variable measured of at least one body segment of the person, where the physical variable measured is chosen from the following list: magnitude of acceleration, magnitude of non-gravitational acceleration, speed, angular velocity, movement, position, or a force exerted by the person when moving on a device,
a processing and calculation step, subdivided into:
a processing and separation step (ii) for processing and separating the raw time signals into distinct time signals Ci in order to break down the gait or run into gait or running cycles, each time signal Ci being a temporal series of points of the measured physical variable and having a given shape, amplitude and duration, the series Ci being associated with a given cycle i of the person's gait or run;
a calculation step (iii) for calculating at least one similarity coefficient between the signal Ci associated with the gait or running cycle i and another signal Cj associated with a gait or running cycle j of the person, the similarity coefficient being at least one of:
a similarity coefficient of a shape fij of the two signals Ci and Cj, which is independent of the amplitude and of the duration, where fij=fji, or
a similarity coefficient of an amplitude aij of the two signals Ci and Cj, which is independent of the shape and of the duration, where aij=aji, or
a similarity coefficient of a duration dij of the two signals Ci and Cj, which is independent of the shape and of the duration, where dij=dji,
an ordering step (iv) for ordering the similarity coefficient in a square matrix M(i,j) in row i and in column j, where i and j are natural integers ranging from 1 to N, the N gait or running cycles being in chronological order, according to their order in the gait or running sequence;
a display step (v) for displaying the square matrix M(i,j) with similarity coefficient values fij, aij or dij shown in cells (ij) of the square matrix M(i,j) using a visual representation of the similarity coefficient value within an interval between two extreme values, continuously without thresholds, to enable determining:
the similarity between all the gait and running cycles i and j of the person, by comparing each cycle taken individually with each of the other cycles taken individually, and
the number of erratic cycles and the number of cycles necessary to establish gait or running rhythms, and at what point in the sequence these erratic cycles and rhythms are reached.

2. The method according to claim 1 , wherein the processing and calculation step, the similarity coefficient between the signal Ci relating to the gait or running of one foot of the person and the signal Cj relating to the gait or running of the other foot is determined and in that the number of cycles−N=Nf, which is the number of cycles of the foot.

3. The method according to claim 2 , wherein in the processing and calculation step, the similarity coefficient between the signal Ci relating to the gait or running of the person's right foot and the signal Cj relating to the gait or running of the same person's left foot is determined, and the number of cycles N is equal to the sum of the number of cycles of the right foot and the number of cycles of the left foot: N=Nr+Nl, Nr and Nl which are the number of cycles of the right foot and the number of cycles of the left foot.

4. The method according to claim 1 , wherein the gait or running rhythms determined are: one or more established rhythms, the start of the gait or running sequence, or about-turn.

5. The method according to claim 1 , wherein, in the display step (v), each value of the similarity coefficient is represented by a color on a continuous graduated scale corresponding to a scale of similarity coefficients.

6. The method according to claim 5 , wherein:
in the processing and calculation step, the three similarity coefficients fij, aij and dij are calculated, each similarity coefficient being associated with the same color scale as the other similarity coefficients, each color having the same meaning in terms of similarity;
in the display step (v), the values of the similarity coefficients are presented in different square matrices [F(i,j), A(i,j), D(i,j)];
the similarity coefficients being chosen:
such that once calculated, all the values of the similarity coefficients fij, aij, dij are in the same interval [a; b] and
such that the higher the values of the similarity coefficients fij, aij, dij, the more similar the signals Ci, Cj are.

7. The method according to claim 1 , wherein the similarity coefficient is a shape coefficient, and in the processing and calculation stage:
each time signal Ci is normalized in terms of duration with each time signal Cj so that the two signals Ci and Cj have the same duration;
each time signal Ci is normalized in terms of amplitude;
a shape similarity coefficient fij is-calculated between each normalized signal C′i and another normalized signal C′j, for all gait or running cycles.

8. The method according to claim 7 , wherein the shape similarity coefficient is Pearson's coefficient, the values of the similarity coefficient being set to 0 if the value of Pearson's coefficient is below zero.

9. The method according to claim 1 , wherein:
the similarity coefficient is a duration similarity coefficient,
a processing and calculation unit ( 3 ) is set up to:
calculate a duration Di of the signal Ci and a duration Dj of signal Cj,
calculate the duration similarity coefficient dij, which is the ratio of the shortest of the two durations Di and Dj to the longest of the two durations Di and Dj.

10. The method according to claim 1 , wherein the similarity coefficient is an amplitude similarity coefficient,
and a processing and calculation unit ( 3 ) is set up to:
calculate an amplitude Ai of the signal Ci and an amplitude Aj of the signal Cj,
calculate the amplitude similarity coefficient aij, which is the ratio of the smallest of the two amplitudes Ai and Aj to the largest of the two amplitudes Ai and Aj.

11. The method according to claim 10 , wherein the amplitude Ai, Aj is a standard deviation or a root mean square.

12. The method according to claim 1 , further comprising:
calculating parameters for evaluating the regularity of the gait or run;
calculating parameters for evaluating the symmetry of the gait or run;
calculating the number of cycles necessary for a gait or running sequence or sub-sequence.

13. The method according to claim 12 , wherein the following are calculated to determine the regularity of the gait or run:
a mean of all cells (i,j) of the square matrix M(i,j), excluding cells i=j,
a standard deviation of all cells (i,j) of the square matrix M(i,j), excluding cells i=j,
a mean of cells i ranging from 1 to Nf, and the cells j ranging from Nf+1 to Nr+Nl.

14. The method according to claim 1 , wherein the raw time signals are processed and separated automatically or manually prior to the calculation step (iii) prior to the calculation of the similarity coefficient.

Assignees

• Univ Paris Descartes
• Centre Nat Rech Scient
• Univ Paris Nord
• Etat Francais—Ministere De La Defense—Direction Centrale Du Service De Sante Des Armee
• Univ Paris

Inventors

• Vidal Pierre
• Barrois-Muller Rémi
• Ricard Damien
• Oudre Laurent

Classifications

• A61B5/7246

  using correlation, e.g. template matching or determination of similarity · CPC title

• A61B5/112 Primary

  Gait analysis · CPC title

• A61B2562/0219

  Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches · CPC title

• A61B5/4082

  Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette · CPC title

• G01C22/006 Primary

  Pedometers · CPC title