System and method for controlling functionality of a device based on user gestures

Abstract

Embodiments of the present disclosure relate to systems and methods for controlling functionality of a device based on a user gesture. An embodiment method for controlling at least one functionality of an electronic device based on a user gesture includes detecting, by a sensor, a change in electrostatic charge of a user during a gesture and generating a charge change signal. The gesture includes moving at least one foot upward and then downward. The method also includes: obtaining, by a processing unit, the charge change signal, detecting a characteristic in the charge change signal that identifies a gesture of moving the foot upward, detecting a characteristic in the charge change signal that identifies a gesture of moving the foot downward, and controlling functionality of the electronic device only in the event that the first characteristic and the second characteristic have been detected.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of Italian Patent Application No. 102020000011221 filed on May 15, 2020, which is incorporated herein by reference. Technical Field

[0003] Embodiments of the present invention relate to a system and method for controlling at least one functionality of an electronic device based on a gesture of a user of the electronic device. Background Art

[0004] Devices for continuous monitoring of the user's body in the environment and during free living conditions are known. Various sensors (e.g., for detecting acceleration, electrical resistance of the skin, temperature of the skin, radiant heat flow and heart rate) are used in various combinations to determine or derive parameters (such as calorie consumption rate, type and level of activity and sleep status). These devices use sophisticated algorithms to integrate the various acquired data streams in order to determine output parameters (e.g., calories burned, type of physical activity, etc.) with the best possible accuracy. Additional sensors for detecting additional parameters provide additional data to the algorithms to improve their accuracy.

[0005] In particular, with regard to step counting, it is known to use a three-axis accelerometer (usually integrated in a portable device) to provide acceleration signals along three orthogonal axes, and to process the acceleration signals with the aid of a step recognition algorithm in order to identify specific signal patterns that may be related to steps taken by a user. However, the acceleration signal processing is calibrated on an "average" or "standard" user, and does not take into account specific physical conditions or needs that may arise (even if only temporarily). For example, due to physical problems, a user may take very short steps, or a step that is different from the normal user step used as a reference in the calibration of the recognition algorithm. Or, in the event that a user has problems in moving, the movement of the arm used by the software installed on the wearable device (e.g., a smart watch) may not indicate a corresponding step of the user. Other unpredictable conditions also prevent correct step counting.

[0006] Electric field sensors are used as an alternative or in addition to accelerometer sensors to determine the user's activity, or to help interpret signals generated by other sensor devices.

[0007] Electric charge is a fundamental component of nature. Electrons from one element are easily transferred to another element when the elements are in direct contact or at a distance. Static charge is generated when charge is transferred between two electrically isolated objects, so that the object with an excess of electrons becomes negatively charged and the object lacking electrons becomes positively charged.

[0008] Electrons move within an object in different ways depending on whether the object is conductive or insulating. In conductors, electrons are more or less evenly distributed throughout the material and can move easily based on the influence of an external electric field. In insulators, the charges are primarily present on the surface. However, depending on the properties of the material and other environmental factors, the charges can be mobile.

[0009] Devices are known that detect changes in the electric field generated by a person during his or her movement or that utilize capacitive type detection. Technologies that use capacitive type detection include, for example, touch screens, systems for detecting the position of occupants in a car, and devices for determining the position, orientation and mass of an object (such as, for example, described in patent document US5,844,415 on electric field detection devices, where a plurality of electrodes are arranged in a defined space for determining the position, mass distribution and orientation of an object in a defined space). This technical solution can also be used to recognize the user's gesture, hand position and orientation, for example, for use in interaction with a processing system instead of a mouse or joystick.

[0010] Patent document US2014 / 0232516 proposes using an electrostatic charge sensor to acquire physiological parameters or user activities (such as walking, cycling or energy consumption) from a field or capacitive sensor.

[0011] The scientific document "Development of a contactless measurement system for human steps" by K. Kurita, SICE 2008 Annual Conference, Japan, describes a system and method for counting the number of steps taken by a subject using a contactless technique. The technique provides for detecting electrostatically induced currents generated as a direct result of the subject's movement in an environment by electrodes placed 1.5 m from the subject. However, the experiments described in the document were performed under ideal conditions and are merely a demonstration of the technical feasibility of step counting, the document does not teach a technique applicable to real life conditions, where the subject performs a number of other activities in addition to steps, each of which causes a change in the electrostatic charge detected by the sensor. In these conditions, the detection of the signal component due solely to the subject's steps is complex and a high reliability of the accuracy of the detection and subsequent counting cannot be guaranteed. Summary of the invention

[0012] Therefore, it is considered necessary to remedy the shortcomings of the prior art by providing a system and method for controlling at least one functionality of an electronic device based on a user gesture of the electronic device that is economical but reliable and requires reduced computational load.

[0013] Embodiments of the present invention relate to a system and method for controlling at least one functionality of an electronic device based on a user gesture of the electronic device. Embodiments of the present invention also relate to an electronic device comprising the system. In particular, the gesture comprises moving at least one foot upward and then downward by the user, and as a result of the gesture, a change in the electrostatic charge of the user's body is detected.

[0014] According to embodiments of the present invention, there is provided a system and method for controlling at least one functionality of an electronic device based on a user gesture of the electronic device, and an electronic device comprising the system, as defined in the accompanying claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] For a better understanding of the invention, embodiments thereof will now be described by way of non-limiting example only and with reference to the accompanying drawings, in which:

[0016] Figure 1 schematically illustrates a system for controlling at least one functionality of an electronic device including an electrostatic charge variation sensor according to an embodiment of the present invention;

[0017] Figure 2 A method for controlling at least one functionality of an electronic device according to an embodiment of the invention is illustrated with the aid of a block diagram;

[0018] Figure 3 Pictured Figure 1 Embodiments of charge change sensors;

[0019] Figure 4A The diagram shows Figure 1 After a series of upward and downward movements of the foot of the user of the electronic device, Figure 3 A charge change signal generated at the output of the sensor;

[0020] Figure 4B Pictured Figure 4A The derivative function of the charge change signal;

[0021] Figure 5 The flowchart illustrates Figure 2 sub-steps of the method;

[0022] Fig. 6A exemplarily illustrating the trend of the charge variation signal and its derivative in the case where the foot of the user moves up and down quickly; and

[0023] Figure 6B The trend of the charge variation signal and its derivative in the case where the foot of the user moves slowly upward and downward are illustrated exemplarily. DETAILED DESCRIPTION

[0024] Figure 1 A motion detection system 1 according to aspects of the present invention is schematically illustrated. The motion detection system 1 comprises a processing unit 2 of an electronic device (or system 4) and an electrostatic charge change sensor 6 coupled to the processing unit 2. In one embodiment, the electrostatic charge change sensor 6 is integrated in the device 4. The processing unit 2 receives a charge change signal S from the electrostatic charge change sensor 6. Q , and according to the charge change signal S Q Generate command or control signal S C .

[0025] The processing unit 2 implements, in use, a method for recognizing a gesture performed by a user of the device 4. The recognition of this gesture results in a command or control signal S C The command or control signal S C For controlling or commanding at least one functionality of the device 4 (eg activating or deactivating the functionality).

[0026] This method relies on Figure 2 The block diagram in is used to represent it.

[0027] refer to Figure 2 , Block B1, the functionality to be controlled is considered to be switched off or disabled, waiting for the command signal S C .

[0028] Then, block B2, obtain the charge change signal S generated by the electrostatic charge change sensor 6 Q .

[0029] Then, block B3, executes processing of the charge change signal S Q steps in order to extract important parameters and identify the parameters of the pose to be detected.

[0030] Block B4, in the event of detecting the gesture, the above functionality of the device 4 is started (block B5); otherwise, the method proceeds by continuing to obtain the charge variation signal S Q And return to block B2.

[0031] In one embodiment of the invention, the gesture to be detected is an upward movement of at least one foot or leg of the user from the ground and a continuous downward movement toward the ground.

[0032] Each upward and downward movement generates a change in electrostatic charge through the user's body due to the charge exchange with the ground / floor, which change is detected by the electrostatic charge change sensor 6. The sequence of upward and downward movements of the user's foot or leg within a predetermined time identifies the user's intention to activate the aforementioned functionality of the device 4 and therefore involves a command signal S to activate this functionality. CThese steps are an implementation of block B4, which therefore includes a sub-step of identifying an upward movement of the foot or leg and, only in the affirmative, leads to a sub-step of identifying a downward movement of the foot or leg within a first time interval. If the downward movement of the leg occurs within the time interval, the method proceeds to block B5; otherwise, the method returns to block B2.

[0033] By way of non-limiting example, the device 4 is a portable electronic device such as a smartphone, and the functionality to be controlled is picture taking by means of a camera or video camera of the device 4 (eg in a selfie mode).

[0034] In one embodiment, the processing unit 2 is a microcontroller integrated in the device 4 .

[0035] The movement detection system 1 has at least one sensitive element or electrode (only Figure 3 5 ), wherein a part of the user's body (e.g. a hand or a finger) can be placed in direct electrical contact with the at least one sensitive element or electrode. In the case of device 4, the electrode 5 can be integrated or connected to the device 4 in another way, for example by means of an external cable or a wireless connection (e.g. integrated in a smart watch connected to the device 4). As is obvious to a person skilled in the art, other embodiments are possible, such that the electrode 5 is in electrical contact with an area of ​​the user's body during the steps of controlling and commanding the aforementioned functionality.

[0036] The sensitive element (electrode) 5 that collects external charges can be a metal surface or an electrode coated with a dielectric material, or can also be a metal surface placed in the case of a device with an integrated sensitive element. In any case, in use, the user is required to place a finger (or hand, or another part of the body) in contact with the sensitive element 5.

[0037] The movement detection system 1 is affected by the changes in electrostatic charge caused by the movements of the user. Signals originating from specific movements (particularly due to upward and downward movements of the feet or legs) can be isolated and identified relative to other movements that are not of interest and relative to the background noise present in the case of user inactivity. However, according to the invention, it is assumed that the functionality is activated starting from a substantially stationary state of the user and therefore it is not necessary to implement the signal S Q to identify, for example, a shape originating from an upward / downward movement of a foot or leg relative to a shape originating from a complex movement of an arm.

[0038] Figure 3An exemplary and non-limiting embodiment of an electrostatic charge variation sensor 6 is illustrated. The electrostatic charge variation sensor 6 comprises an input 8a electrically coupled to an electrode 5, which in turn can be contacted by a part of the user's body; the electrostatic charge variation sensor 6 also comprises an input 8b electrically coupled to the input 8a by means of a resistor R0 and a capacitor C0 connected in parallel to each other. The pair R0, C0 connected to the electrode 5 and placed between the two non-inverting inputs of the two operational amplifiers OP1 and OP2 has the function of accumulating the charge collected by the electrode 5 and the function of managing the frequency band of the input signal (to filter the signal and noise at the unwanted frequency).

[0039] The capacitance value of C0 and the resistance value of R0 can be selected according to the type of filter (e.g., a low-pass filter with a cut-off frequency of tens of Hz (e.g., 20 Hz)) that is desired to be formed. For example, the capacitance of C0 is selected in the range of 5pF-5nF. For example, the resistance of R0 is selected in the range of 500MOhm-50 GOhm. The capacitance value of C0 and the resistance value of R0 can also be selected according to the impedance of the stage to which they are connected, the available frequency of the signal Vd, and the frequency of the interference to be filtered (e.g., the frequency of the power grid, the high-frequency electrical noise of the power supply circuit, etc.).

[0040] In use, the voltage (or potential) Vd established between inputs 8a and 8b represents the differential input of the instrumentation amplifier 12 .

[0041] The instrumentation amplifier 12 includes two operational amplifiers OP1 and OP2. A bias stage (buffer) OP3 is used to bias the instrumentation amplifier 12 to a common mode voltage V CM .

[0042] The inverting terminals of the operational amplifiers OP1 and OP2 are connected to each other by means of a resistor R2. When the two inputs of each operational amplifier OP1, OP2 are at the same potential, the input voltage Vd is also applied to the end of R2, and causes a current equal to I2=Vd / R2 to pass through the resistor R2. This current I2 does not come from the input terminals of the operational amplifiers OP1, OP2, and therefore flows through the two resistors R1 connected between the outputs of the operational amplifiers OP1, OP2, and the two resistors R1 are connected in series with the resistor R2; therefore, the current I2 flowing through the series of three resistors R1-R2-R1 produces an output voltage Vd', which is given by Vd'=I2·(2R1+R2)=Vd·(1+2R1 / R2). Therefore, Figure 3 The total gain of the circuit is Ad=(1+2R1 / R2). The differential gain depends on the value of resistor R2 and can therefore be modified by acting on resistor R2.

[0043] Therefore, the differential output Vd′ proportional to the potential Vd between the inputs 8a, 8b is input to the analog-to-digital converter 14, which outputs a charge change signal S for the processing unit 2. Q . Charge change signal S Q For example a high resolution digital stream (16 or 24 bits). The analog-to-digital converter 14 is optional, since the processing unit 2 may be configured to work directly on analog signals, or may itself comprise an analog-to-digital converter for converting the signal Vd'.

[0044] Figure 4A The charge change signal S Q The value of the potential difference Vd introduced by the charge change between the inputs 8a, 8b is represented in the charge change signal S Q The value is expressed here in LSB ("least significant bit"), i.e. the smallest digital value output from the analog-to-digital converter, which is proportional to the potential difference Vd present at the inputs 8a, 8b. Typically, 1 LSB corresponds to a value between a few μV and tens of μV. The proportionality constant (or sensitivity) depends on the gain of the amplifier, the resolution of the analog-to-digital converter and any digital processing (e.g. oversampling, decimation, etc.). Representation in LSB is common in the art and disregards quantization of physical units, since the goal is typically to detect relative changes relative to a stable or base state.

[0045] The progressive number of samples obtained is represented in the charge change signal S Q The reported measurements have been made with a sampling frequency equal to 50 Hz, each sample therefore being separated in time by 20 ms from the next and the previous sample.

[0046] As from Figure 4A As can be seen, the charge change signal S Q There are multiple peaks p1 - p10 that follow each other in time and have amplitudes much larger than the background noise.

[0047] Each peak p1-p10 is caused by the upward movement of the corresponding user's foot or the downward movement of the user's foot. The peaks p1-p10 are identified in the signal Vd' (which is then sampled to generate the signal S Q ), but what is described here applies in an equivalent manner to the signal Vd. In practice, the amplifier stage ( Figure 3An instrumentation amplifier (A / D) is useful but not necessary. If the charge change signal to be obtained (caused by the user's movement) is large enough, or if the electrical characteristics of the analog-to-digital converter allow the charge change signal to be large enough (e.g., high input impedance, high resolution, full scale suitable for the signal to be converted), then this amplifier stage can be omitted and inputs 8a and 8b are the inputs to the analog-to-digital converter.

[0048] When the user performs an upward movement of his / her foot, negative peaks p1, p3, p5, p7, p9 are generated, and when the user performs a downward movement of his / her foot that was previously moved upward, positive peaks p2, p4, p6, p8, p10 are generated. By way of example, starting from time 0, when the user first moves his / her foot upward, the signal S Q A negative peak p1 is generated, and when the same foot subsequently moves downward, the signal S Q The positive peak p2 in is generated. The same happens for the generation of other pairs of negative and positive peaks (upward moving foot: generation of p3, downward moving foot: generation of p4, etc.).

[0049] According to an aspect of the present invention, sampling of the voltage Vd' is provided at a sampling rate of 50 Hz, generating a signal S Q The sampling rate is for example equal to 50 Hz, but may be different, for example chosen in the range 25 Hz - 1 kHz.

[0050] Optionally, the signal S Q Filtering is also provided to remove or attenuate any spectral components not related to the movement to be detected. For example, low pass filtering may be performed to attenuate signals S greater than 30 Hz. Q component in order to reduce the noise induced by the electric field of the power grid as much as possible (usually reduced to 50Hz or 60Hz).

[0051] According to the invention, the parameter of interest is also obtained from the signal S Q is extracted (hereinafter, referred to as “signal S Q " to distinguish the signal S with or without filtering Q ), which is used to detect the user's posture (e.g., the foot moving up from the ground / down to the ground). This operation is used to calculate the relative signal S Q (hereinafter referred to as S Q ') time derivative; signal S Q 'exist Figure 4B Medium picture.

[0052] In the previously described embodiment, as mentioned, the voltage Vd' is sampled at 50 Hz. This means that a signal Vd' representing 2 seconds, where N = 100 signals S QSample S Q (1),…,S Q (N). For signal S Q Each sample S Q (1),…,S Q (N) The derivative value is calculated (or estimated) according to known methods, for example according to the "forward difference method" which is used to calculate the difference between two consecutive samples divided by a time unit.

[0053] Other methods allow the derivative to be estimated using a larger number of points with greater accuracy and less sensitivity to noise. In the method known as "second-order central differences," the derivative is y i =(x i+1 -x i-1 ) / 2dt, that is, to estimate the value yi of the derivative y(n) of the function at the i-th sampling step with a duration of dt, it is necessary to know the value x of the function x(n) at the next sampling step and the previous sampling step respectively. i+1 and x i-1 In a method called fourth-order central difference, the derivative y is i =(-x i+2 +8x i+1 -8x i-1 +x i-2 ) / 12dt: In this case, a better estimate of the derivative is obtained at the expense of greater computational and memory usage complexity, since the value of the function x(n) needs to be known by utilizing 4 sampling steps.

[0054] Then, the charge change signal S Q The derivative S Q ' component is extracted, which identifies the performance of the gesture to be detected by the user.

[0055] To this end, with the help of the dual threshold ±Th Q The comparison is used to identify the signal S Q 'component, the signal S Q 'Identifies the expected posture.

[0056] In particular, the upward movement of the foot Figure 4A The signal S Q The change of generates a negative peak p1, and the time derivative of the negative peak p1 is Figure 4B The peaks are represented by a sequence of two peaks, first a negative peak p1' and then a positive peak p1"; similarly, the peaks due to the continuous downward movement of the foot Figure 4A The signal S Q The change of generates the positive peak p2, and the time derivative of the positive peak p2 is Figure 4BIt is represented by a series of two peaks, first the positive peak p2' and then the negative peak p2".

[0057] exist Figure 4B In, use Figure 4A The LSB of the same representation in the signal S Q The value of the derivative calculated on the basis of is represented on the vertical axis. The derivative provides a signal S Q A measurement that varies with "speed" or rate. Similar to Figure 4B , the progression of samples obtained is represented by Figure 4B on the horizontal axis.

[0058] Signal S Q '(peak p1') exceeds (towards negative value) threshold -Th Q Then the same signal S Q '(peak p1") continuously exceeds (towards positive value) threshold +Th Q The signal S is associated with the user performing an upward movement of the foot. Q '(peak p2') exceeds (towards positive value) threshold +Th Q Then the same signal S Q '(Peak p2") exceeds (towards negative value) threshold -Th Q is associated with the user performing a downward movement of the foot. Therefore, by identifying the signal S Q ', can identify the expected upward movement and continued downward movement of the user's foot.

[0059] Similar considerations apply to the peak pairs (p3', p3") and (p4', p4"), identifying an upward shift of the foot identified by peak p3, and a corresponding downward shift of the foot identified by peak p4, and so on.

[0060] As from Figure 4B It is noted that in the absence of user movement, the signal S Q varies slightly, but is essentially constant (unless due to static noise phenomena). In this context, the signal S Q The derivative S Q ' is essentially equal to zero (or its average value is equal to zero). On the contrary, in the case of an expected posture, the derivative S Q ' shows a clear variation, with positive peaks p1', p2' and negative peaks p1', p2' relative to zero. Therefore, the "negative peak" is intended to represent the signal S Q 'Towards negative value (less than signal S Q 'The average value assumed in the absence of movement) changes, which reaches below the threshold -Th Q The value (towards a negative value exceeding the threshold -Th Q); “positive peak” is intended to indicate that the signal S Q 'Towards positive value (greater than signal S Q 'The average value assumed in the absence of movement) changes that reach above the threshold +Th Q The value (towards a positive value exceeding the threshold +Th Q ).

[0061] The Applicant has also verified that, compared to the upward / downward movement of the foot, other movements, such as the swinging of the user's arm supporting the device 4 during activation of the functionality according to the invention, do not generate the signal S Q and S Q '. In fact, the electrostatic charge change caused by the movement of the arm is much lower than and different from the electrostatic charge change caused by the upward movement of the foot; in fact, the electrostatic charge caused by the movement of the arm is not caused by the charge exchange with the ground / floor, but by the change of the electrostatic field induced by the movement of the body (relative to the charge generation or transfer caused by the arm-air friction, which is dominant).

[0062] In one embodiment, the threshold ±Th Q In particular, the Applicant has verified that the signal generated by the movement of the leg is relatively stable with respect to the signal S Q '(and correspondingly, S Q ) is strong enough that each threshold ± Th Q can be preset to be equal to the signal S Q 'The background noise reaches a value (absolute value) of 20 to 50 times the maximum value, so there is no risk of obtaining false alarms.

[0063] In one embodiment, the threshold ±Th Q The levels may be defined as fixed levels (1 / 4, 1 / 2, 3 / 4, etc.) based on the full scale of the sensor, or may be programmable by the user (e.g., by creating a calibration routine for "move foot up" and "move foot down" gestures, with a user interface that requires the user to perform a certain number of repetitions to estimate the optimal threshold level and possibly the maximum time level between two events).

[0064] Threshold ±Th Q It can be defined, for example, by calculating the mean and standard deviation of the maximum (in the case of positive peaks) and minimum (in the case of negative peaks), and selecting the threshold when the mean decreases or increases (for the maximum or minimum, respectively) by 3 times the standard deviation.

[0065] By way of example, it is considered that when the user is substantially stationary, the signal S QThe background noise of 'oscillates between ±5LSB and the threshold value of 100LSB +Th Q The selection and value of -100LSB threshold -Th Q The choice of allows differentiation between peaks that are actually due to the user's intended movement and background noise.

[0066] In another embodiment, the threshold ±Th Q is of adaptive type, i.e., it is based on the signal S Q ' changes with the trend. The threshold ±Th of the adaptive type Q The calculation of can be performed using techniques known in the art. For example, a sliding window or overlapping windows can be used. Other techniques for calculating adaptive thresholds in real time can be used.

[0067] As reference Figure 2 As discussed, in order to distinguish between a command actually given by the user and an upward / downward movement of the foot for other reasons, the time t elapsed between the detection of a positive peak p1 ″ and the detection of the next positive peak p2 ′ may optionally be detected. OFF , time t OFF For example, the signal S Q 'At threshold + Th Q The following stay time.

[0068] If the time t that elapses between these two peaks p1″ and p2′ OFF Greater than the reference time interval ΔT OFF , then no command (or trigger) is generated for starting the aforementioned functionality of device 4; on the contrary, a command is generated for starting the aforementioned functionality of device 4.

[0069] The time interval ΔT OFF The value of should be chosen taking into account the speed of the foot's upward / downward movement, because the signal S Q The rising and falling edges of the peaks p1-p10 (and therefore, the rising and falling edges of their derivatives) vary depending on the speed of the upward / downward movement of the foot.

[0070] Figure 5 A method for calculating and estimating the time t that elapses between an upward movement of the foot and a subsequent downward movement of the foot is illustrated with the aid of a flow chart. OFF These steps are Figure 2 of step B4.

[0071] refer to Figure 5 Flow chart of, when at step B4a (according to the described mode) the upward movement of the foot is detected, step B4b is executed, wherein the timer T Q is turned on, the timer T QThe time elapsed from the upward movement of the foot to the subsequent placement of the foot on the ground is calculated.

[0072] At each acquisition iteration, the condition "foot resting on the ground" is evaluated (step B4c): if the foot has moved downwards, the signal S of step B2 Q The acquisition is stopped and executed Figure 2 Step B5 (start functionality).

[0073] If the foot is not detected to be resting on the ground at step B4c, the timer T is verified at step B4d. Q Whether the predefined reference interval ΔT has been exceeded OFF (For example, 1 second, which can be set or modified by the user).

[0074] If No (T Q <ΔT OFF ), then increase the timer T Q (Step B4e), and the method returns to step B4c.

[0075] In the case of exceeding ΔT OFF In the case of a threshold value (exit YES from block B4d), the method returns to step B4a to obtain the signal S based on the obtained signal Q to detect the upward movement of the foot.

[0076] Therefore, based on Figure 5 Steps, t off It is the time that elapses between the time when the upward movement of the foot is detected and the time when the downward movement of the foot is detected.

[0077] Fig. 6A The signal S in the case of fast movement is shown by way of example Q and S Q 'trend, and Figure 6B The signal S in the case of slow movement is shown by way of example Q and S Q ' trend. As noted, in Fig. 6A In the case of OFF Basically less than Figure 6B The corresponding time t OFF However, the Applicant has verified that a reference interval ΔT equal to a value between 1 and 2 seconds OFF The choice of (where threshold + Th Q Equal to or greater than 100) covers most situations that occur in practice and can identify slow commands and fast commands.

[0078] Finally, it is obvious that changes and variations may be made to what has been discussed above without departing from the scope of the present invention.

[0079] For example, the step of detecting the peaks p1-p10 by means of a threshold value can be performed by identifying the signal S Q or signal S Q For example, machine learning and / or artificial intelligence techniques can be used to automatically identify the signal S Q or S Q ', which is associated with the posture to be detected (upward / downward movement of the leg) so as to distinguish between different types of postures, including: stepping up, stepping down, stepping on the ground, etc.

[0080] In addition, it should be noted that a charge change sensor of a type that is not wearable by the user but is configured to remotely detect static electricity changes generated after the user performs a step can be used. This type of system is a distributed system and can be used, for example, in games or augmented reality applications, where the user performs his / her movements in a defined environment (e.g., a room).

[0081] From the foregoing description, the advantages achieved by the present invention are obvious.

[0082] For example, the invention offers the opportunity to control a device without using hands that may be occupied with other uses (e.g. supporting the device itself). In addition, the invention is not affected by the ambient brightness (a critical parameter in applications of face recognition or gesture recognition according to the prior art) nor by acoustic noise (interference in the case of voice commands). Even in the case of freeing the hands, control by movement of the foot allows not to exert (some unwanted) pressure or movement (buttons, screen touches, etc.) directly on the device to be controlled, which has the advantage of not changing its position, aim or focus (in the case of a camera).

[0083] Although the present invention has been described with reference to illustrative embodiments, the description is not intended to be interpreted in a limiting sense. Various modifications and combinations of the illustrative embodiments and other embodiments of the present invention will be apparent to those skilled in the art by reference to the specification. Therefore, it is intended that the appended claims cover any such modifications or embodiments.

Claims

1. An electronic system comprising: an electrostatic charge change sensor configured to detect a change in electrostatic charge of a user of the electronic device during a gesture performed by the user, and to generate a charge change signal, wherein the gesture includes the user moving at least one foot upward and then downward; as well as a processing unit coupled to the electrostatic charge change sensor, and the processing unit is configured to: acquiring the charge change signal; Calculating a derivative function of the charge change signal; detecting a first characteristic in the derivative function of the charge change signal, the first characteristic identifying the gesture of moving the at least one foot upward, the first characteristic comprising a first positive peak following in time a first negative peak; detecting a second characteristic in the derivative function of the charge change signal, the second characteristic identifying the gesture of moving the at least one foot downward, the second characteristic comprising a second positive peak following the first positive peak in time and followed by a second negative peak; and At least one functionality of the electronic device is controlled in response to detecting both the first characteristic and the second characteristic.

2. The electronic system of claim 1 , wherein the processing unit is configured to detect the first characteristic comprises the processing unit being configured to: defining a negative comparison threshold and a positive comparison threshold for the derivative function; identifying the first negative peak in the derivative function having a first amplitude, the first amplitude exceeding the negative comparison threshold; and The first positive peak is identified in the derivative function having a second amplitude that exceeds the positive comparison threshold.

3. The electronic system of claim 2, wherein the processing unit is configured to detect the second characteristic comprises the processing unit being configured to: identifying in the derivative function the second positive peak having a third amplitude, the third amplitude exceeding the positive comparison threshold; and The second negative peak having a fourth amplitude is identified in the derivative function, the fourth amplitude exceeding the negative comparison threshold.

4. The electronic system of claim 3, wherein the first negative peak, the first positive peak, the second positive peak, and the second negative peak follow each other in time in the absence of additional positive and negative peaks exceeding the positive comparison threshold and the negative comparison threshold. 5 . The electronic system according to claim 3 , wherein the positive comparison threshold and the negative comparison threshold are fixed thresholds preset by the user or are definable by the user. The electronic system of claim 3 , wherein the positive comparison threshold and the negative comparison threshold are adaptive thresholds.

7. The electronic system according to claim 1, wherein the processing unit is further configured to process the charge change signal using a machine learning and / or artificial intelligence algorithm to detect a specific pattern of the charge change signal, wherein the specific pattern identifies the gesture of moving the at least one foot up and down.

8. The electronic system of claim 1, wherein the electrostatic charge variation sensor is an instrumentation amplifier comprising: a first electrode configured to be placed in direct contact with a portion of a body of the user; as well as A second electrode is coupled to a voltage reference terminal, wherein the charge variation signal is a function of a potential difference existing in use between the first electrode and the second electrode.

9. A portable electronic device comprising: A functional unit configured to perform at least one functionality; An electrostatic charge change sensor configured to: detecting a change in electrostatic charge of a user of the portable electronic device during a gesture performed by the user; as well as generating a charge change signal, wherein the gesture includes the user moving at least one foot upward and then downward; as well as a processing unit coupled to the electrostatic charge change sensor and the functional unit, wherein the processing unit is configured to: acquiring the charge change signal; Calculating a derivative function of the charge change signal; detecting a first characteristic in the derivative function of the charge change signal, the first characteristic identifying the gesture of moving the at least one foot upward, the first characteristic comprising a first positive peak following in time a first negative peak; detecting a second characteristic in the derivative function of the charge change signal, the second characteristic identifying the gesture of moving the at least one foot downward, the second characteristic comprising a second positive peak following the first positive peak in time and followed by a second negative peak; and The at least one functionality of the portable electronic device is controlled in response to detecting both the first characteristic and the second characteristic.

10. The portable electronic device of claim 9, wherein the portable electronic device is a smartphone, the functional unit is a camera, and the functionality is taking a picture or a video.

11. The portable electronic device of claim 9, wherein the processing unit is configured to detect the first characteristic comprises the processing unit being configured to: defining a negative comparison threshold and a positive comparison threshold for the derivative function; identifying the first negative peak in the derivative function having a first amplitude, the first amplitude exceeding the negative comparison threshold; and The first positive peak is identified in the derivative function having a second amplitude that exceeds the positive comparison threshold.

12. The portable electronic device of claim 11 , wherein the processing unit is configured to detect the second characteristic comprises the processing unit being configured to: identifying in the derivative function the second positive peak having a third amplitude, the third amplitude exceeding the positive comparison threshold; and The second negative peak having a fourth amplitude is identified in the derivative function, the fourth amplitude exceeding the negative comparison threshold.

13. A portable electronic device according to claim 9, wherein the processing unit is further configured to process the charge change signal using machine learning and / or artificial intelligence algorithms to detect a specific pattern of the charge change signal, wherein the specific pattern identifies the gesture of moving the at least one foot up and down.

14. A method for controlling an electronic device, comprising: detecting a change in electrostatic charge of a user of the electronic device during a gesture performed by the user, the gesture comprising the user moving at least one foot upward and then downward; generating a charge change signal according to detecting the electrostatic charge change; Calculating a derivative function of the charge change signal; detecting a first characteristic in the derivative function of the charge change signal, the first characteristic identifying the gesture of moving the foot upward, the first characteristic comprising a first positive peak following in time a first negative peak; detecting a second characteristic in the derivative function of the charge change signal, the second characteristic identifying the gesture of moving the foot downward, the second characteristic comprising a second positive peak following the first positive peak in time and followed by a second negative peak; and At least one functionality of the electronic device is controlled in response to detecting both the first characteristic and the second characteristic.

15. The method of claim 14, wherein detecting the first characteristic comprises: defining a negative comparison threshold and a positive comparison threshold for the derivative function; identifying the first negative peak in the derivative function having a first amplitude, the first amplitude exceeding the negative comparison threshold; as well as The first positive peak is identified in the derivative function having a second amplitude that exceeds the positive comparison threshold.

16. The method of claim 15, wherein detecting the second characteristic comprises: identifying in the derivative function the second positive peak having a third amplitude, the third amplitude exceeding the positive comparison threshold; as well as The second negative peak having a fourth amplitude is identified in the derivative function, the fourth amplitude exceeding the negative comparison threshold.

17. The method of claim 16, wherein the first negative peak, the first positive peak, the second positive peak, and the second negative peak follow each other in time in the absence of additional positive and negative peaks exceeding the positive comparison threshold and the negative comparison threshold.

18. The method according to claim 16, wherein the positive comparison threshold and the negative comparison threshold are fixed thresholds preset by the user or are definable by the user. The method of claim 16 , wherein the positive comparison threshold and the negative comparison threshold are adaptive thresholds.

20. The method of claim 14, further comprising processing the charge change signal using a machine learning and / or artificial intelligence algorithm to detect a specific pattern of the charge change signal, the specific pattern identifying the gesture of moving the at least one foot up and down.

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