DATA ENTRY DEVICE

Abstract

A data input device (10) comprises a functional surface (12) adapted to receive pressure from a user, such as the pressure of a user's finger (14); a piezoelectric film (16) having at least one axis of sensitivity (30, 34) and disposed below the functional surface and adapted to emit an electrical signal as a function of the pressure received by the functional surface; and a computing unit (18) configured to receive the signal generated by the piezoelectric film in response to pressure on the functional surface; and to determine from this signal an area and / or shape of the functional surface pressed by the user using a classification algorithm. Abstract figure: Figure 1

Description

Title of the invention: DATA INPUT DEVICE Technical field

[0001] The present disclosure relates to the field of data input devices, and in particular touch surfaces and keyboards. Prior art

[0002] Keyboards are generally composed of a surface which is sensitive to the pressure of the finger associated with each key. The keyboard can integrate elements of the mechanical type (for example an inductive switch), of the capacitive type (for example electrodes) or even of the ultrasonic type.

[0003] Whatever the solution, the finger pressure sensitive areas must be organized in a matrix or in a specific organization specific to a keyboard. Depending on the technology used, there are various mechanical limitations in their integration. For example, mechanical switches can be aesthetically unpleasing in addition to requiring a movement path, inductive switches suffer from their magnetic sensitivity. As for the capacitive matrix, it works poorly when positioned behind metal.

[0004] It would therefore be beneficial to have a keyboard or more generally a data entry device which frees itself from these constraints. Summary

[0005] The present disclosure improves the situation.

[0006] A data input device is provided comprising a functional surface adapted to receive pressure from a user, such as pressure from a user's finger; a piezoelectric film having at least one sensitivity axis and being arranged below the functional surface and adapted to emit an electrical signal as a function of the pressure received by the functional surface; and a computing unit configured to: receive the signal generated by the piezoelectric film in response to the pressure on the functional surface; and determine from this signal an area and / or a shape of the functional surface pressed by the user using a classification algorithm.

[0007] By "below" we refer to an axis orthogonal to the plane of the two largest dimensions of the functional surface. The underside of the functional surface extends, in use, on the side opposite the contact face with the user, in particular the user's finger.

[0008] The functional surface can thus form a human-machine interface of the touch surface type. Preferably, the functional surface forms, in use, a surface external surface of a motor vehicle. The invention thus makes it possible to very easily transform any portion of the bodywork or other external surface of a motor vehicle into a touch-sensitive surface.

[0009] According to another aspect, there is provided a motor vehicle such as a car including the above device.

[0010] The features set out in the following paragraphs may, optionally, be implemented, independently of one another or in combination with one another:

[0011] - the shape is a point, a line or a two-dimensional figure.

[0012] - the calculation unit configured to determine from the signal generated by the film piezoelectric the time sequence of pressing the functional surface using a classification algorithm.

[0013] - the input device is a keyboard, the functional surface includes a plurality of zones, each zone corresponding to a key, and the computing unit is configured to determine from this signal the key corresponding to the zone of the functional surface pressed by the user.

[0014] - the keys are arranged in a line and the piezoelectric film is a single piezoelectric film having a sensitivity axis arranged parallel to the key line.

[0015] - the keys are arranged in a matrix according to rows and columns, and the film pie zoelectric is a single piezoelectric film having at least two non-parallel axes of sensitivity.

[0016] - the keys are arranged in a matrix according to rows and columns, and the film pie zoelectric consists of a first piezoelectric film having a first axis of sensitivity and a second piezoelectric film having a second axis of sensitivity, the first piezoelectric film being arranged relative to the second piezoelectric film so as to have the first axis of sensitivity at a non-zero angle, preferably at 90 degrees, from the second axis of sensitivity.

[0017] - the first piezoelectric film is arranged opposite the functional surface of so as to have the first sensitivity axis parallel to the rows of the key matrix, and the second piezoelectric film is arranged opposite the functional surface so as to have the second sensitivity axis parallel to the columns of the key matrix.

[0018] - the classification algorithm is of the set type.

[0019] - the classification algorithm is of the boosting type, for example AdaBoost (Adaptive Boosting), Gradient Boosting, or XGBoost (Extreme Gradient Boosting).

[0020] - the piezoelectric film is directly bonded to the functional surface. Brief description of the drawings

[0021] Other characteristics, details and advantages will appear on reading the detailed description below, and on analyzing the attached drawings, in which: Fig. 1

[0022] [Fig-1] schematically shows a data input device according to a embodiment, in the form of a keyboard. Fig. 2

[0023] [Fig.2] shows a partial and transparent top view of the input device of data from [Fig.l]. Fig. 3

[0024] [Fig.3] shows an example of electrical signals observed when a user presses a part of the data input device of [Fig.l]. Fig. 4

[0025] [Fig.4] shows an example of an electrical signal (left) and its conversion (right) into time graph of slope of said signal. Fig. 5

[0026] [Fig.5] shows examples of time window divisions of graphs temporal slope of electrical signals observed when a user presses a part of the data input device. Description of the embodiments

[0027] Reference is now made to [Fig.l]. A data input device 10 comprises a functional surface 12 adapted to receive finger presses 14 from a user, a piezoelectric film 16 disposed below the functional surface 12 and adapted to emit an electrical signal as a function of the finger presses 14 of the user on the functional surface 12, and a computing unit 18 configured to receive the signal generated by the piezoelectric film 16 in response to the finger press 14 on the functional surface 12, and determine from this signal an area of ​​the functional surface 12 pressed by the user.

[0028] The data input device 10 makes it possible to identify the shape and position of a pressure made on the functional surface 12 by the user using one or more fingers. The shape of the pressure may be a point (for example if the data input device 10 is a keyboard), a line or a two-dimensional figure (for example a circle, a zigzag or a triangle).

[0029] The functional surface 12 includes an external face 20 which receives the pressures of the user's fingers 14, and an internal face 22 connected to the piezoelectric film 16. The external surface 20 can directly receive the pressure of the user's fingers 14, for example as a touch-sensitive surface, or via the interaction of a mechanical device, such as for example a keyboard key. The functional surface 12 may be a monolithic surface or consist of a plurality of adjacent surfaces.

[0030] The functional surface 12 can be any surface suitable for transmitting pressure from the user's fingers to the piezoelectric film 16. Therefore, the functional surface 12 can be relatively rigid as long as the piezoelectric film 16 can detect atomic displacement in the functional surface 12. The functional surface 12 can be of any material and shape.

[0031] The piezoelectric film 16 can be directly bonded to the functional surface 12. In another embodiment, an element is arranged between the piezoelectric film 16 and the functional surface 12. This element makes it possible to transmit the pressure of the user's fingers.

[0032] The piezoelectric film 16 includes at least one piezoelectric film having at least one sensitivity axis. Thus, depending on the implementation of the data input device 10, there may be a single film having a single sensitivity axis for detecting pressures arranged in a line (for example, keys arranged in a line or a line-type movement, in which case detection is only required along one dimension / axis), or there may be a single film having two or more sensitivity axes for detecting pressures along two dimensions / axes (for example, keys arranged in rows and columns (matrix) or a two-dimensional figure). It is also possible that the piezoelectric film 16 includes two or more piezoelectric films, each having a sensitivity axis for detecting pressures along two dimensions.

[0033] The calculation unit 18 makes it possible to analyze the finger pressures 14 on the functional surface 12 to deduce their location and shape. For this, the calculation unit uses a classification algorithm. The number of classes of the classification algorithm will depend on the number of shapes / locations of finger pressures to be identified. For example, for a 9-digit numeric keypad, the number of classes will be 9.

[0034] The computing unit 18 may be located close to or distant from the functional surface 12.

[0035] Referring now to [Fig. 2], an example of implementation of the data entry device 10 is shown in the form of a 9-key numeric keypad 24, each key corresponding to a number from 1 to 9. The functional surface 12 is therefore divided into 9 zones 26. This division can be virtual or physical.

[0036] Since the data input device 10 is a numeric keypad 24 having rows and columns (i.e. two-dimensional), the piezoelectric film 16 has at least two axes of sensitivity. In the case of [Fig. 2], it was chosen that the piezoelectric film 16 consists of two piezoelectric films, each having one axis of sensitivity. It would also have been possible to have only one piezoelectric film but that this one has two or more axes of sensitivity. It would also have been possible to have more than two piezoelectric films.

[0037] In the case of [Fig. 2], therefore, the piezoelectric film 16 is made up of a first piezoelectric film 28 having a first sensitivity axis 30, and a second piezoelectric film 32 having a second sensitivity axis 34. The sensitivity axes 30, 34 are shown in dotted lines in [Fig. 2]. The first piezoelectric film 28 is arranged relative to the second piezoelectric film 32 so as to have the first sensitivity axis 30 at a non-zero axis of the second sensitivity axis 34. In the example of [Fig. 2], the angle between the first sensitivity axis 30 and the second sensitivity axis 34 is 90 degrees. It could be, however, that the first sensitivity axis 30 is at a non-zero angle other than perpendicular to the second sensitivity axis 34.Having the sensitivity axes 30, 34 of the piezoelectric film(s) makes it possible to detect a shape which would be either at a two-dimensional position on the functional surface 12, such as for example a point on the numeric keypad 24, or a two-dimensional shape, such as a circle, triangle or zigzag.

[0038] Referring now to [Fig. 3], an example of a signal generated by the first piezoelectric film 28 is shown when the functional surface 12 is touched at different locations by the user. It can therefore be seen that for each point of impact of the finger 14 (for example the user presses an area of ​​the functional surface 12 corresponding to key 1, or to key 3) a different electrical signature E1, E2, ... En is generated by the piezoelectric film. Thus, from the signatures, the calculation unit 18, using the classification algorithm, will be able to determine which area and / or shape of the functional surface 12 was pressed by the user.

[0039] In order for the classification algorithm to be able to use the electrical signatures, these are first converted into an N x 1 vector of dimension 1, with the N characteristics of this signal. With reference to Figures 4 and 5, the signal processing part to obtain the vectors corresponding to the electrical signatures will now be explained.

[0040] [Fig.4] shows on the left an example of an electrical signal En as it could have been recorded for example in [Fig.3]. The electrical signal En in the left figure shows the evolution of the intensity over time of the electrical signal. This signal is first converted into a graph ([Fig.4] right) showing the evolution of the slope of the signal En over time. This conversion makes it possible to eliminate noise and to highlight the variation of the signal. This graph of the evolution of the slope of the signal En over time will then be divided into two or three time windows T1, T2, T3, as illustrated in [Fig.5].

[0041] [Fig.5] shows 4 graphs of the evolution of the slope of the electrical signal emitted by the piezoelectric films according to the area of ​​the functional surface (i.e. touch in the case of the keyboard). More specifically, graphs (A) and (B) are respectively the electrical signals emitted by the first piezoelectric film 28 when the respective keys 1 and 3 are pressed. Graphs (C) and (D) are respectively the electrical signals emitted by the second piezoelectric film 30 when the respective keys 1 and 3 are pressed.

[0042] Thus for each electrical signature received by each piezoelectric film transformed into a graph of the temporal evolution of the slope of the electrical signal over time, the slope graph is divided into two, and possibly three time windows. These windows correspond to phases of pressing the finger 14 on the functional surface 12 (window T1), of releasing the finger 14 from the functional surface 12 (window T2), and optionally, if this occurs, of a rebound once the finger is released (as for example in a keyboard) (window T3).

[0043] [Fig.5] shows an example of dividing the slope of the electrical signal into three windows (the bounce being present). During the first time window T1 corresponding to the pressing of the finger 14 on the functional surface 12, the slope is positive or negative. During the second time window T2 corresponding to the release of the finger 14 from the functional surface 12, the slope is of the opposite sign compared to the sign of the slope in the first time window TL. The delimitation between the first and second phases is therefore at the moment of change of sign. During the third time window T3 corresponding to the optional bounce, the slope is of the opposite sign compared to the sign of the slope in the second time window T2 (resp. positive or negative). The delimitation between the second and third time windows T2, T3 is therefore at the moment of change of sign.

[0044] According to one embodiment, a signal processing algorithm makes it possible to divide each time graph of the slope of the electrical signal into 2 or 3 time windows by looking at the changes in sign of the slope.

[0045] For each time window, features will be extracted. The supervised learning algorithm will use these features to classify the received electrical signature into the corresponding area and / or shape of the functional surface (i.e. for a keyboard to identify the key pressed by the user or for a touch surface to identify the shape traced by the user). There may be a multitude of features, and the algorithm may use one, several or all of the features provided to it to determine the corresponding area / shape of the functional surface.

[0046] According to an example, the characteristics extracted from the time graph of the slope of the electrical signal are: (1) Duration of the time window, for each of the 2 or 3 time windows identified above determined on the time evolution graph of the slope of the electrical signal over time, (2) Maximum amplitude of the time graph of the electrical signal in each time window, (3) Maximum slope amplitude of the time graph of the slope of the electrical signal in each time window, (4) Ratios of the slope amplitudes for each time window and for the different piezoelectric films (if 2 piezos, 3 calculated ratios, if 3 piezos, 9 calculated ratios) calculated on the time evolution graph of the slope of the electrical signal over time.

[0047] The characteristics thus obtained are put into vector form as input data for the classification algorithm.

[0048] For example, if a single piezoelectric film is used [Feature 1, Feature 2, ...., Feature N]. If two piezoelectric films are used [Feature 1- Piezo 1, Feature 2- Piezo 1, ...., Feature N- Piezo 1, Feature 1- Piezo 2, Feature 2- Piezo 2, ...., Feature N- Piezo 2]. If M piezoelectric films are used [Feature 1- Piezo 1, Feature 2-Piezo 1, ...., Feature N- Piezo 1, Feature 1- Piezo 2, Feature 2-Piezo 2, ...., Feature N- Piezo 2,.......Feature 1- Piezo M, Feature 2- Piezo M, ...., Feature N- Piezo M].

[0049] The classification algorithm will have as many classes as there are areas / shapes to detect. For example, for a 9-digit keyboard, there will be 9 classes.

[0050] According to one embodiment, the classification algorithm is a set-theoretic algorithm. According to one embodiment, the classification algorithm is a boosting-type set-theoretic algorithm.

[0051] A boosting algorithm is a machine learning technique that combines the predictions of multiple weak or base models to create a stronger and more accurate prediction model. Boosting belongs to ensemble learning methods, where multiple models are trained and combined to make better predictions than individual models.

[0052] In boosting, base models are typically simple and weak, such as decision trees with limited depth or shallow neural networks. Each base model is trained on a subset of the training data or with different weights assigned to the data points. Models are trained iteratively, with each subsequent model focusing on examples that were misclassified by previous models.

[0053] During the training process, reinforcement assigns higher weights to misclassified examples, effectively giving them more importance. Subsequent models are then trained to prioritize the misclassified examples, attempting to correct the errors made by previous models. This iterative process continues until a predefined stopping criterion is met, such as a maximum number of models or a desired level of accuracy.

[0054] The final prediction is made by combining the predictions of all the base models, usually through a weighted voting system. The weights are determined based on the performance of each base model during training. The idea behind boosting is that by combining multiple weak models, each focusing on different aspects of the data, the overall model can capture complex relationships and improve predictive accuracy.

[0055] Popular boosting algorithms include AdaBoost (Adaptive Boosting), Gradient Boosting, and XGBoost (Extreme Gradient Boosting).

Claims

Claims

1. A data input device (10) comprising: a. A functional surface (12) adapted to receive pressure from a user, such as pressure from a user's finger (14); b. A piezoelectric film (16) having at least one sensitivity axis (30, 34) and being disposed below the functional surface and adapted to emit an electrical signal as a function of the pressure received by the functional surface; and c. A computing unit (18) configured to: i. Receive the signal generated by the piezoelectric film in response to the pressure on the functional surface; and ii. Determine from this signal an area and / or a shape of the functional surface pressed by the user using a classification algorithm.

2. A device according to claim 1, wherein the shape is a point, a line or a two-dimensional figure.

3. Device according to the preceding claim, in which the calculation unit is configured to determine from the signal generated by the piezoelectric film the time sequence of pressing of the functional surface using a classification algorithm.

4. Device according to one of the preceding claims, in which the input device is a keyboard (24), the functional surface includes a plurality of zones (26), each zone corresponding to a key, and the calculation unit is configured to determine from this signal the key corresponding to the zone of the functional surface pressed by the user.

5. A device according to claim 4, wherein the keys are arranged in a line and the piezoelectric film is a single piezoelectric film having a sensitivity axis arranged parallel to the line of keys.

6. A device according to claim 4, wherein the keys are arranged in a matrix in rows and columns, and the piezoelectric film is a single piezoelectric film having at least two axes of non-parallel sensitivity.

7. A device according to claim 4, wherein the keys are arranged in a matrix in rows and columns, and the piezoelectric film consists of a first piezoelectric film (28) having a first sensitivity axis (30) and a second piezoelectric film (32) having a second sensitivity axis (34), the first piezoelectric film being arranged relative to the second piezoelectric film so as to have the first sensitivity axis at a non-zero angle, preferably at 90 degrees, from the second sensitivity axis.

8. Device according to the preceding claim, in which the first piezoelectric film is arranged opposite the functional surface so as to have the first sensitivity axis parallel to the rows of the key matrix, and the second piezoelectric film is arranged opposite the functional surface so as to have the second sensitivity axis parallel to the columns of the key matrix.

9. Device according to one of the preceding claims, in which the classification algorithm is of the set type.

10. Device according to the preceding claim, in which the classification algorithm is of the boosting type, for example Adaptive Boosting, Gradient Boosting, or Extreme Gradient Boosting.

11. Device according to one of the preceding claims, in which the piezoelectric film is directly bonded to the functional surface.

12. Motor vehicle comprising the data input device according to one of claims 1 to 11.

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