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1. WO2020136135 - BODY MOTION ANALYSIS DATA TREATMENT

Note: Text based on automatic Optical Character Recognition processes. Please use the PDF version for legal matters

[ EN ]

CLAIMS

1. Method for monitoring a human body motion comprising the steps of:

- providing a garment (1 , 101 ) with a surface comprising a plurality of stress sensors (1.1 -1.8, 101.1 -101.18) measuring at least one component of a stress tensor and generating output signals, the plurality of stress sensors (1.1 -1.8, 101.1 -101.18) being distributed over the surface and being adapted to face a portion of a human body;

- providing a means (3) for detecting or recording 3D coordinates of each of the stress sensors (1.1 -1.8, 101.1-101.18); and

- providing an evaluation unit (2), said unit (2) receiving the output signals of the plurality of stress sensors (1.1 -1.8, 101.1 -101.18) and said 3D coordinates;

said unit (2) being configured for:

- recording at least one stress value of the at least one component of the stress sensor (1.1 -1.8, 101.1 -101.18) measured for each stress sensor;

- estimating at least one stress value representative of a human body motion parameter in a point of the surface at least on the basis of at least two of the at least one stress values, corresponding respectively to the measurements of at least two of the stress sensors (1.1 -1.8, 101.1 -101.18) and at least two 3D coordinates, corresponding to the at least two of the stress sensors (1.1 -1.8, 101.1 -101.18).

2. Method according to claim 1 , characterized in that the at least one stress value in the point of the surface is estimated on the basis of all the at least one stress values of all stress sensors (1.1 -1.8, 101.1 -101.18) and all the 3D coordinates of each stress sensor (1.1 -1.8, 101.1 -101.18).

3. Method according to any of claims 1 to 2, characterized in that the estimation is an interpolation, preferably the interpolation is selected from the group consisting of natural neighbor interpolation, inverse distance weighted, trend surface interpolation, linear triangulation interpolation, spline interpolation, ordinary Kriging, simple Kriging, universal Kriging.

4. Method according to any of claims 1 to 3, characterized in that each of the stress sensors (1.1 -1.8, 101.1 -101.18) is a pressure sensor (1.1 -1.8, 101.1 - 101.18).

5. Method according to claim 4, characterized in that the at least one component of the stress tensor is a pressure.

6. Method according to claim 5, characterized in that the pressure sensor (1.1- 1.8, 101.1-101.18) is defined by a normal vector perpendicular to a plane tangent to the pressure sensor measurement surface.

7. Method according to claim 6, characterized in that the means (3) for detecting or recording 3D coordinates of each of the stress sensors (1.1 -1.8, 101.1- 101.18) is further configured for also detecting or recording a group of components of the normal vector of each stress sensor (1.1 -1.8, 101.1 - 101.18).

8. Method according to claim 7, characterized in that the evaluation unit (2) is further configured for estimating at least one stress value representative of a human body motion parameter in a point of the surface also on the basis of at least two groups of components of the normal vector, corresponding to the at least two of the stress sensors (1.1 -1.8, 101.1-101.18).

9. Method according to any of claim 1 to 3, characterized in that each of the stress sensors (1.1 -1.8, 101.1 -101.18) is a multi-directional shear and normal force sensor (1.1 -1.8, 101.1 -101.18).

10. Method according to claim 9, characterized in that the at least one component of the stress tensor comprises at least one normal stress component and at least one shear stress component.

11. Method according to claim 10, characterized in that the at least one normal stress component is defined by a normal vector perpendicular to a plane tangent to the surface at a given point, the at least one shear stress component is defined by a tangent vector within the plane, the at least one stress value comprises at least two stress values being respectively a pressure corresponding to the normal stress component associated with said normal

vector and a shear stress corresponding to the at least one shear stress component associated with said tangent vector and normal vector.

12. Method according to claim 11 , characterized in that the means (3) for detecting or recording 3D coordinates of each of the stress sensors (1.1 -1.8, 101.1- 101.18) is further configured for also detecting or recording a group of components of the normal and tangential vectors of each stress sensor (1.1 - 1.8, 101.1 -101.18).

13. Method according to claim 12, characterized in that the evaluation unit (2) is further configured for estimating at least one stress value representative of a human body motion parameter in a point of the surface also on the basis of at least two groups of components of the normal and tangential vectors, corresponding to the at least two of the stress sensors (1.1 -1.8, 101.1 -101.18).

14. Method according to any of claims 1 to 13, characterized in that the garment (1 , 101 ) is an article of footwear (1 ), a short, underpants or a glove (101 ).

15. Method according to claim 14, characterized in that the article of footwear (1 ) is an insole (1 ), a sole of a shoe or a sock and the portion of a human body is a sole of a foot.

16. Method according to any of claims 1 to 15, characterized in that the step of providing an evaluation unit (2) comprises the embedment of the evaluation unit (2) within the garment (1 , 101 ).

17. Method according to any of claims 1 to 15, characterized in that the step of providing an evaluation unit (2) comprises the embedment of the evaluation unit (2) within a further garment selected from a group consisting of insole, sole of shoe, sock, short, underpants, glove, armband.

18. Method according to any of claims 1 to 17, characterized in that the point in the surface where the at least one stress value is estimated is different from any points corresponding to the 3D coordinates of the plurality of stress sensors (1.1 -1.8, 101.1 -101.18).

19. Method according to any of claims 1 to 18, characterized in that the output signals corresponding to each of the at least one stress value are recorded for a period of time.

20. Method according to claim 19, characterized in that the evaluation unit (2) determines key indicators (Kl) for at least one cycle of a plurality of human body motion cycles.

21. Method according to claim 20, characterized in that acceptable values or ranges of values are defined for each key indicator (Kl) and when one of the key indicators (Kl) departs from its acceptable values or ranges of values, a warning signal is issued.

22. Method according to claim 21 , characterized in that the evaluation unit (2) is configured to detect a change of body motion based on the detected persistent variations prior to or during the detection of a key indicator (Kl) departing from its acceptable values or ranges of values.

23. Method according to claim 21 or 22, characterized in that the acceptable values or ranges are preset or based on averaged or reference values of previous cycles.

24. Method according to any of claims 20 to 23, characterized in that the key indicators (Kl) are averaged 3D coordinates of a weighted geometric center estimated for the at least one cycle, wherein the distribution of weight is based on at least one distribution of the at least one stress value.

25. Method according to claim 24 in combination with any of claims 5 to 8 and 14, characterized in that the key indicators (Kl) are averaged 3D coordinates (GX, GY, GZ) of a pressure geometric center estimated for the at least one cycle.

26. Method according to any of claims 20 to 23, characterized in that the key indicators (Kl) are further selected from the group consisting of: the maximum (Pmax) of the at least one stress value during the at least one cycle, the average (Pave) of the at least one stress value over the at least one cycle, the duration of the at least one cycle (T), the point in time when the at least one stress value changes to exceed a reference value, the duration during which the at least one stress value exceeds the reference value, the integral (IP) of the at least one stress value over the duration of the at least one cycle, a linear combination thereof..

27. Method according to claim 24 or 25 in combination with claim 15, characterized in that a plurality of human body motion cycles is a plurality of stride cycles.

28. Method according to claim 24 or 25 in combination with claim 14 when the garment (1 , 101 ) is a glove, characterized in that a plurality of human body motion cycles is a plurality of hand motion cycles.

29. Method according to any of claims 1 to 28, characterized in that the values corresponding to the 3D coordinates of the stress sensors (1.1 -1.8, 101.1- 101.18) are calibrated after the garment (1 , 101 ) being put onto the human body portion to take into account the actual positions of the sensors (1.1 -1.8,

101.1 -101.18).

30. Method according to claim 29, characterized in that the values corresponding to the 3D coordinates of the stress sensors (1.1 -1.8, 101.1-101.18) are based on measurements and/or a model.

31. Method according to any claims 14-30 in combination with claim 8, characterized in that values corresponding to the group of components of the normal vector of each stress sensor (1.1 -1.8, 101.1 -101.18) are estimated in an absolute referential.

32. Method according to claim 31 , characterized in that the values corresponding to group of components of the normal vector of each stress sensor (1.1 -1.8,

101.1 -101.18) are based on measurements of an inertial sensor (1.1 -1.8,

101.1 -101.18) fitted into the garment (1 , 101 ), the evaluation unit (2) or another wearable device such as a smart phone or on a combination of a digital elevation model and global positioning system coordinates estimated by the evaluation unit (2) or another wearable device such as a smart phone.

33. System for monitoring a human body motion comprising:

- a garment (1 , 101 ) with a surface comprising a plurality of stress sensors (1.1 -1.8, 101.1-101.18) measuring at least one component of the stress tensor and generating output signals, the plurality of stress sensors (1.1 -

1.8, 101.1 -101.18) being distributed over the surface and being adapted to face a portion of a human body;

- a means (3) for detecting or recording 3D coordinates of each of the stress sensors (1.1 -1.8, 101.1 -101.18);

- an evaluation unit (2) configured for receiving the output signals of the plurality of stress sensors (1.1 -1.8, 101.1 -101.18) and said 3D coordinates; said unit (2) being configured for:

- recording at least one stress value of the at least one component of the stress sensor (1.1 -1.8, 101.1 -101.18) measured for each stress sensor (1.1 -1.8, 101.1 -101.18);

- estimating at least one stress value representative of a human body motion parameter in a point of the surface on the basis of at least two of the at least one stress values, corresponding respectively to the measurements of at least two of the plurality of stress sensors (1.1 -1.8, 101.1-101.18) and said 3D coordinates.

34. System according to claim 33, characterized in that each of the stress sensors (1.1 -1.8, 101.1 -101.18) is a pressure sensor (1.1 -1.8, 101.1-101.18).

35. System according to claim 34, characterized in that each of the pressure sensors (1.1 -1.8, 101.1 -101.18) is adapted to measure a pressure between 0 and 7 bars or between 0 and 3.5 bars.

36. System according to claim 33, characterized in that each stress sensor (1.1 - 1.8, 101.1 -101.18) is a multi-directional shear and normal force sensor (1.1 - 1.8, 101.1 -101.18).

37. System according to any of claims 33 to 36, characterized in that the garment (1 , 101 ) is an article of footwear, short, underpants or glove (101 ).

38. System according to claim 37, characterized in that the article of footwear (1 ) is an insole (1 ), a sole of a shoe or a sock and the portion of the human body is a sole of a foot.

39. System according to any of the claims 33 to 38, characterized in that the evaluation unit (2) is integrated into the garment (1 , 101 ).

40. System according to any of claims 33 to 38, characterized in that the evaluation unit (2) is integrated into a further garment selected from a group consisting of insole, sole of shoe, sock, short, underpants, glove, armband.