Automatic determination of a measurement of digital lifestyle via aggregation of a set of heterogeneous measurements originating from heterogeneous sources

Abstract

The invention relates to a system (1) for determining a degree of screen dependency of a user (2), comprising - at least one software module (23, 24) embedded in a set of pieces of information-processing equipment (13, 14) and configured to collect first measurements (42) on the behaviour of applications installed on said pieces of information-processing equipment and second measurements (43) on the behaviour of said pieces of information-processing equipment; - a database (30) for storing said measurements; - a server (50) for periodically determining an aggregation of said measurements and a degree of screen dependency depending on said aggregation.

Description

automatic determination of a measure of digital lifestyle by aggregating a set of heterogeneous measurements from heterogeneous sources FIELD OF THE INVENTION

[0001] The present invention relates to the determination of a degree of screen dependence, representative of a user's digital lifestyle. It aims in particular to aggregate objective and holistic measurements for this purpose.

[0002] CONTEXT OF THE INVENTION

[0003] Excessive screen use is now recognized as a major problem in our society. Furthermore, the global pandemic that began in 2020 led individuals to self-isolate for several months and intensified both screen-dependent behaviors and the number of scientific and political discussions surrounding this issue.

[0004] In France, the MILDECA (Interministerial Mission for the Fight against Drugs and Addictive Behavior) published a report in 2021 stating that 24% of young French people aged 15-24 report watching videos for more than 4 hours a day and 33% of young people play online games for the same number of hours a day.

[0005] However, excessive use of screens (e.g., smartphones, the internet, online games) has multiple consequences that can be dramatic for the health and cognitive development of adolescents and young adults. Indeed, the difficulty in regulating screen use can lead to serious pathological disorders such as video game addiction.

[0006] Recent findings have shown that regular exposure to television or video games is associated with fewer positive attitudes toward school and lower academic performance. These include Adelantado-Renau et al., “Association Between Screen Media Use and Academic Performance Among Children and Adolescents: A Systematic Review and Meta-analysis,” 2019, DOI: 10.1001 / jamapediatrics.2019.3176.

[0007] This can be explained in particular by the fact that excessive screen use is also linked to weaker cognitive skills such as a weak perception of self-regulation, as for example explained in Gökçearslan et al., “Modeling smartphone addiction: The role of smartphone usage, self-regulation, general self-efficacy and cyberloafing in university students” in Computers in Human Behavior, 2016, DOI:10.1016 / j.chb.2016.05.091, or LaRose et al., “Unregulated Internet Usage: Addiction, Habit, or Deficient Self-Regulation?” in Media Psychology, 5(3), 225-25, 2003.

[0008] Wartberg et al., “The relevance of emotion regulation, procrastination, and perceived stress for problematic social media use in a representative sample of children and adolescents” in Computers in Human Behavior, vol. 121, 2021, also links this excessive use to more inattention.

[0009] Furthermore, excessive screen use is associated with poorer sleep quality, according to Chen & Gau, “Sleep problems and internet addiction among children and adolescents: a longitudinal study,” in Journal of Sleep Research, 2016, or Ratan et al., “Smartphone Addiction and Associated Health Outcomes in Adult Populations: A Systematic Review,” in International Journal of Environmental Research and Public Health, 2021, and also with lower self-esteem, greater anxiety, and more depression, as discussed in Prizant-Passal et al., “Social anxiety and internet use–A meta-analysis: What do we know? What are we missing?”, in Computers in Human Behaviors, vol. 62, 2016, or in the aforementioned article by Ratan et al.

[0010] To prevent or even remedy this difficulty, one of the challenges is to identify individuals likely to use screens excessively.

[0011] However, reporting problematic screen use practices is generally done using self-reported questionnaire measures. Examples include the Smartphone Addiction Scale by Kwon et al., “The smartphone addiction scale: development and validation of a short version for adolescents,” 2013, https: / / doi.org / 10.1371 / journal.pone.0083558, and the Game Addiction Scale, described in Lemmens et al., “Development and Validation of a Game Addiction Scale for Adolescents,” in Media Psychology 12(1):77-95, 2009, DOI: DOI:10.1080 / 15213260802669458.

[0012] US2010 / 076274A1 describes a state-of-the-art human / digital media interaction tracking system.

[0013] An objective of the present invention is to provide an objective approach for determining a user's degree of screen addiction. This degree makes it possible to assess digital lifestyle hygiene.

[0014] The degree of digital lifestyle hygiene is a characterization of the impact of screens on a user's health. This characterization is a continuum that extends from moderate use to problematic use. Problematic screen use can be observed in several cases: - when recreational use of screens has become the only activity of a user during their waking hours, - when the user sacrifices aspects of their social life in favor of recreational use of screens (schooling, professional situation, friendly or family situations), - when the user's health is endangered because of screen use (sedentary lifestyle, sleep, social isolation, depression).

[0015] Digital hygiene includes the use of equipment, particularly equipment with screens. Excessive use of these screens constitutes poor digital hygiene.

[0016] The invention therefore aims to determine a quantification, or a quantitative (and qualitative) measure, of this digital lifestyle. In particular, the invention aims to determine a degree of screen dependence, and thus makes it possible to assign the user to a class among, for example, normal behavior, abnormal but not problematic behavior, and problematic behavior that may be related to dependence, or addiction.

[0017] In particular, the invention aims to enable an assessment of this digital lifestyle that is not solely dependent on the declaration of screen users, which can be distorted and lead to a bad diagnosis.

[0018] It also aims to avoid being too intrusive but on the contrary to be as transparent as possible in order on the one hand not to impact the quality of life of users by imposing additional actions, and on the other hand to prevent them from changing their behavior as a result of surveillance.

[0019] It also aims to enable monitoring over time of users' digital lifestyle and any addictions they may have. Indeed, methods based on questionnaires to be completed only provide a one-off "snapshot" of the user's state, and it would be necessary to multiply these completions to be able to detect changes in addiction (or more generally in digital lifestyle), which might not be acceptable to users and / or would hinder the provision of precise and correct answers.

[0020] Finally, the invention aims to offer a holistic evaluation, that is to say to cover the use of the different screens and equipment available to the same user.

[0021] To this end, according to a first aspect, the present invention can be implemented by a system for determining a degree of dependency on a user's screens, comprising at least one software module embedded on a set of information processing equipment, adapted to collect first measurements on the behavior of the applications installed on said information processing equipment and second measurements on the behavior of said information processing equipment; a database for storing said measurements; a server for periodically determining an aggregation of said measurements and a degree of dependency on the screens as a function of said aggregation, the system further comprises at least one physical sensor capable of collecting third measurements relating to said at least one piece of equipment; said server being adapted to determine said aggregation as a function of said third measurements.

[0022] According to preferred embodiments, the invention comprises one or more of the following features which can be used separately or in partial combination with each other or in total combination with each other: said at least one physical sensor is one of a probe embedded in an electrical outlet supplying power to at least one piece of equipment from among a television and a video game console, capable of collecting third measurements on the electrical behavior of said at least one piece of equipment, a motion detection device for detecting a disconnection of the power supply of the at least one piece of equipment, capable of collecting third measurements relating to the position of the at least one piece of equipment, and a base capable of collecting third measurements relating to the position of the at least one piece of equipment; said electrical outlet is adapted to collect a particular measurement in the event of physical disconnection of said at least one piece of equipment;said electrical outlet is arranged so that upon said physical disconnection, said electrical outlet is no longer powered; said server is adapted to assign a class to said user based on said degree of dependence on screens; said server is adapted to determine an aggregation of measurements of the same nature coming from separate equipment;

[0023] According to a second aspect, the invention can also be implemented by a method for determining a degree of dependency on a user's screens, comprising the collection of first measurements on the behavior of applications installed on a set of information processing equipment, and second measurements on the behavior of said information processing equipment, by at least one software module embedded on said set of information processing equipment; the storage of said measurements in a database; the periodic determination of an aggregation of said measurements and of a degree of dependency on screens as a function of said aggregation, by a server.

[0024] According to preferred embodiments, the invention comprises one or more of the following features which can be used separately or in partial combination with each other or in total combination with each other:the method further comprises the collection of third measurements on the electrical behavior of at least one piece of equipment, by a probe embedded in an electrical outlet supplying said at least one piece of equipment among a television and a video game console, said aggregation taking into account said third measurements.the method comprises the assignment of a class to said user, according to said degree of dependence on screens.The method is implemented for a predefined duration

[0025] Other characteristics and advantages of the invention will appear on reading the following description of a preferred embodiment of the invention, given by way of example and with reference to the appended drawings. BRIEF DESCRIPTION OF THE FIGURES

[0026] The accompanying drawings illustrate the invention:

[0027] schematically represents an example of architecture according to an embodiment of the invention;

[0028] is a schematic view of a device for ensuring the connection status;

[0029] is a schematic view of a game console and a device for ensuring the state of use of a game console in a first position;

[0030] is a schematic view of the game console and the device in a second position.

[0031] DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

[0032] The invention aims to capture user behavior across all of these digital devices, in order to have a holistic view of their use of devices equipped with screens and their possible addiction to screens and to be able to quantify it.

[0033] In particular, the invention includes the collection of measurements of the behavior of the software applications used, equipment such as computers, smartphones, digital tablets, virtual reality headsets, smart watches, etc., but also equipment such as televisions, video game consoles, etc.

[0034] One of the difficulties is to take into account equipment of heterogeneous nature, each requiring a specific implementation of technical means for collecting measurements. Another difficulty is to take into account heterogeneous typologies of measurements, and to aggregate, or combine them, in order to determine a degree of dependence (or degree of digital hygiene).

[0035] According to the inventors, this characteristic of taking into account all equipment (regardless of its technical nature) and all types of measurement makes it possible to better monitor the usage behaviors of the different screens that an individual has, and, therefore, to better understand problematic uses and situations of dependence. This approach therefore makes it possible to determine problematic use of screens from several objective and automatically reported indicators.

[0036] Illustrates an architecture according to one embodiment of the invention.

[0037] A user 2 has a fleet of 10 devices with screens and which can therefore, as such, contribute to the potential dependence, or addiction, of user 2.

[0038] Generally speaking, this equipment can be subdivided into two categories: information processing equipment, 13, 14 which allows a software module to be embedded, respectively 23, 24, to collect information, or measurements, on their behavior and the behavior of the installed software applications; other equipment (not shown) which does not allow such software modules to be embedded.

[0039] Among the first type of equipment, we can notably cite mobile telecommunications terminals (of the "smartphone" type), or other terminals equipped with a screen with an interface allowing the installation of an ad-hoc software module such as, for example, digital tablets, computers, connected watches, virtual reality headsets, etc.

[0040] The second type of equipment includes televisions, game consoles, etc. These devices generally do not have interfaces that allow the installation of an ad-hoc software module.

[0041] For this second type of equipment, one embodiment of the invention provides for embedding a probe, 21, 22 within the electrical outlets 11, 12, supplying this equipment. These probes are adapted to collect measurements on the electrical behavior of the equipment they supply.

[0042] Such a socket may have a software infrastructure and interfaces allowing the installation of software modules, implementing the functions of these probes 21, 22. Also, certain sockets may natively have such software modules.

[0043] Indeed, the development of connected objects, enabling support for the Internet of Things (or "IoT"), has enabled the provision of numerous socket solutions enabling advanced functionalities and / or offering means of incorporating additional functionalities via additional software modules.

[0044] An example of such plugs is those developed by the company SHELLY. The "Shelly Plug" natively offers power consumption measurement functions and interfaces, or APIs (Application Programming Interface) allowing access to the measurements made and exporting them to devices external to the plug.

[0045] The interface of the sockets of the Shelly company is described for example on the link:

[0046] https: / / shelly-api-docs.shelly.cloud / gen1 /

[0047] These sockets allow you to query electrical energy measurement means via the MQTT protocol (“Message Queuing Telemetry Transport” in English):

[0048] TOPIC MQTT shellies / <model> - <deviceid> / relay / 0 / power

[0049] According to one embodiment, a socket, a set of sockets, a power strip, or PDU (Power Distribution Unit), can be used. In such an embodiment, the probe 21, 22 makes it possible to collect individualized measurements for each of the sockets of the power strip. In this way, the electrical behavior of each powered equipment can be collected.

[0050] According to one embodiment of the invention, the electrical outlet is adapted to collect a particular measurement in the event of physical disconnection of powered equipment.

[0051] In particular, the electrical outlet 11, 12 may be adapted to prevent the disconnection of equipment without this being detected by the respective probe 21, 22. According to embodiments, the probe may detect the disconnection state by different types of sensors, such as: electric current sensor, temperature sensor, accelerometric and spatial sensor, distance sensor, microswitch, pressure sensor, proximity sensor, voltage sensor, infrared sensor, shock sensor or motion sensor, etc.

[0052] To do this, one embodiment consists of arranging the electrical outlet so that when the (male) plug of the equipment is physically disconnected from the (female) socket, the latter is no longer powered. For example, the socket box 11, 12 is encapsulated in an over-housing which holds the (male) plug connected by cord to the powered equipment, so that the latter cannot be disconnected without at least partially removing this over-housing. The latter can be arranged so that its removal, even partial, requires also disconnecting the power supply from the socket box 11, 12. Therefore, the absence, even momentary, of power supply can be detected simply by interrogating the probes 21, 22.

[0053] The challenge is that the measurement of the behavior of the socket 11, 12 actually corresponds to the electrical behavior of the powered equipment. This requires ensuring a unique link between a given socket and associated equipment, and therefore preventing a user from connecting a particular piece of equipment to another socket (possibly not monitored) or connecting another piece of equipment to the given monitored socket.

[0054] For example, this embodiment makes it possible to prevent a user from disconnecting their game console from the monitored socket 11, 12 to connect it to another socket in their home. This would obviously result in the measurements collected being distorted and losing relevance.

[0055] Generally speaking, the measurements collected by the probes 21, 22 therefore aim to be representative of the electrical behavior of monitored equipment which is likely to be involved in a dependency on the user's screens.

[0056] This electrical behavior can be based on the "on" or "off" characteristic of the equipment. From monitoring this characteristic, the probes 21, 22 can determine measurements 41 relating to the electrical behavior of the equipment in terms of: duration of use of the powered equipment, times of use of the powered equipment (on and off times), internal temperature of the outlet, electrical consumption of the powered equipment.

[0057] As an alternative to detecting the electrical consumption of the powered equipment, another device 101 is schematically illustrated in the form of a clamp, making it possible to ensure the connection status between the male plug and the female plug of a piece of equipment. The device 101 is clamped onto the cable (not shown) of the power cord of the equipment. Indeed, to unplug the male plug from the female plug, the user must exert a force on the male plug. The device 101 is capable of measuring that a disconnection force has been applied along the cord from the male plug. This force necessary for unplugging the equipment causes a direct alert signal (light) on a Light Emitting Diode (LED) 102 and / or a sending of data to servers (not shown).The device 101 comprises in this illustrative and non-limiting embodiment a microprocessor 103, a motion sensor 104 and a connector 105 for receiving a plug 105a connected to a cable 105b, making it possible to transfer data from the device 101 to servers and to power the device 101. Any other means of data transmission can however be envisaged within the framework of the invention (Bluetooth signal, wifi, LoRa, Sigfox, sound signal, sending SMS, vibrations, etc.). The device 101 can, for example, be implemented with an Arduino Nano ® system. When the device 101 is clamped on a power cable of equipment to be monitored, any disconnection of the equipment creates a sudden movement on its power cable detected by the device 101.

[0058] The motion sensor can be any sensor capable of detecting movement at the cord where the clip is attached (tilt ball sensor, accelerometer, gyroscope, pressure, piezoelectric, light divergence, vibration).

[0059] It is understood that the method of attaching the device 101 to the cable is not necessarily a clamp. The device 101 can be attached by any other means allowing it to follow the movements of the cable in a solid manner.

[0060] In the case where the motion sensor is an accelerometer, the algorithm for detecting an attempt to disconnect a piece of equipment to be monitored is as follows:- initial state of the position sensor (X1, Y1, Z1)- motion / shock detection- time delay (for example 45 seconds)- reading of the position sensor (Xi, Yi, Zi)- if at least one of the coordinates (Xi, Yi, Zi) differs by more than 10% from the coordinates (X1, Y1, Z1), detect an attempt to disconnect, otherwise false alarm (simple movement of the equipment to be monitored).

[0061] Figures 3 and 4 schematically illustrate another device 203 for ensuring the state of use of a games console or a tablet 201.

[0062] The equipment considered here is a flat equipment, of the games console or tablet type 201, which is equipped with an RFID chip 202 stuck on the rear face of the games console or tablet 201.

[0063] The device 203 is in the form of a base having the shape of an elongated narrow arch, defining a space for receiving the games console or tablet 201.

[0064] The device 203 includes an LED 204, a processor 205, an RFID sensor 206, and is powered by a plug 207 connected to a cord 208, the plug 207 and the cord 208 allowing both the power supply to the device 203 and the transfer of data from / to the device 203.

[0065] In the position of the, the games console or tablet 201 is outside the reception space of the device 203, therefore the RFID chip 202 of the games console or tablet 201 is not detected by the RFID sensor 206: it is then assumed that the games console or tablet 201 is in use.

[0066] In the position of the, the games console or tablet 201 is in the reception space of the device 203, therefore the RFID chip 202 of the games console or tablet 201 is detected by the RFID sensor 206: the games console or tablet 201 is then not in use.

[0067] When the processor 205 detects the presence of the chip 202 attached to the game console or tablet 201, the processor 205 sends, according to a determined period, for example every minute, to a server (not shown) an incremental quantity of non-use of the game console in a time-stamped manner (for example using a set of three parameters: { "NonUsageTime": 256, "FirstDetectionTime": "8:45", "FirstDetectionTime": "8:30 p.m."}), except in the case where the user has unlocked time on the game console or tablet 201.

[0068] In addition, when it is necessary to apply usage restrictions to the game console or tablet 201, the light signal of the LED differs in the case where the user can use the game console or tablet and the case where he cannot use it, for example, the LED lights up when the user can use the portable game console and the LED 204 turns off when the user cannot use the game console or tablet 201.

[0069] If the user decides to use the game console or tablet 201 when he is not authorized to use the screens, the device 203 sends data to a server in order to implement an alert.

[0070] It is possible to use other transmitters capable of transmitting usage information when the user is not authorized to use the portable game console or tablet (for example: Bluetooth signal, sound signal, Wifi signal, LoRa, Sigfox, sending SMS, vibration).

[0071] Devices 101 and 203 therefore make it possible to know the state of use of equipment powered by a power cord and of games consoles or tablets.

[0072] These measures 41 provide insight into the use of these types of equipment, such as televisions and video game consoles, not only regarding the total duration of use, but also regarding the times of use. Indeed, in the context of assessing a potential addiction, using a game console, for example, in the morning or in the evening is not irrelevant, the first case being a priori more indicative of an addiction.

[0073] The measurements 41 thus collected can be transmitted to a remote database 30 to be stored there.

[0074] Furthermore, the devices 13, 14 are information processing devices. They therefore allow easier installation of software modules 23, 24 and offer richer interfaces to enable monitoring of the behavior of both the applications installed and executed on these devices as well as on the devices themselves.

[0075] As mentioned above, this equipment may be computers (desktop or laptop), smart communication terminals (or mobile phones), digital tablets, or any other existing or future equipment, having an operating system allowing the installation of software modules and offering interfaces allowing measurements to be obtained on the applications and the equipment.

[0076] According to the invention, the software modules 23, 24 are adapted to collect two types of measurements (at least): measurements 42 on the behavior of the applications installed on the information processing equipment and measurements 43 on the behavior of the information processing equipment itself.

[0077] Generally, software modules are installed to be launched when the user logs in to the equipment and to run continuously in the background to collect real-time metrics on the user's activities. When the equipment does not support multiple sessions, logging in for the user is equivalent to turning on the equipment.

[0078] For example, on a computer running the Windows® operating system, the software module is placed in the directory:

[0079] Users / <nom_d’utilisateur> / AppData / Roaming / Microsoft / Windows / StartMenu / Programs / Startup

[0080] in which<nom_d’utilisateur> is the user name as registered in the Windows® operating system (therefore corresponding to their session).

[0081] So each time you open a session under Windows®, the software module will be automatically executed.

[0082] In addition, the software module can be a program in Python® language, and stored in the equipment in the form of a ".pyw" file. This allows the software module to be considered as a service so as not to be detected as software and make it more difficult for the user to detect and close it.

[0083] Similarly, on equipment running a “Mac OS®” operating system from Apple®, the software module can be stored in the directory:

[0084] ~ / Library / LaunchDaemons /

[0085] In this way, the software module is automatically executed when the equipment is started.

[0086] Similarly, the software module can be a program in Python® language, and stored in the equipment in the form of a ".pyw" file. This allows the software module to be considered as a service so as not to be detected as software and make it more difficult for the user to detect and close it.

[0087] On a tablet or telecommunications terminal type device, the software module can be a launcher in order to be automatically executed when the device is started.

[0088] This software module (or application) can be declared via the Android® intent mechanism to respond to the “home” and “default” actions:

[0089] <category android :name="‘’android.intent.category.DEFAULT’’ / ">

[0090] <category android :name="‘‘android.intent.category.HOME’’ / ">

[0091] The background services mechanism allows continuous analysis of the equipment

[0092] The foreground service mechanism allows the service to be kept running in the background indefinitely.

[0093] The "Usage_stat_service" system service is used to analyze open applications and bring the software module back to the foreground if necessary.

[0094] On equipment running an Apple® iOS operating system or an Android® operating system, the MDM (“Mobile Device Management”) tool can be used to put the equipment into a supervised mode and enable continuous analysis of the phone.

[0095] According to embodiments of the invention, the measurements 42 on the behavior of the applications installed on the information processing equipment include all or part of the following measurements: name of the application, duration of use of each application (start time, end time), hours of use of each application, frequency of opening of each application.

[0096] According to embodiments of the invention, the measurements 43 on the behavior of the information processing equipment include all or part of the following measurements: Connection and disconnection times of a session; Switching on and off times of the equipment; Movement of the equipment (number of steps, etc.); Orientation of the equipment; Brightness of the equipment; Frequency of interactions with the equipment (number of “clicks” or other interactions).

[0097] These measurements can obviously take several forms. For example, a software module can transmit events indicating the times of launching and closing an application. It is then easy to automatically determine the duration of use, either by the database 30 (or more precisely the application managing this database), or by the server 50. The software module can also itself perform this calculation and transmit it to the database for storage.

[0098] Generally speaking, a person skilled in the art will understand that these measures can be broken down into equivalent variants, i.e. from which the same semantic information can be automatically and directly deduced. In particular, these equivalent variants must allow the server to determine the aggregated measures mentioned above.

[0099] According to one embodiment, these measurements can be supplemented by self-reported declarative data from the user (for example; sleep diary, emotion log, etc.).

[0100] According to one embodiment, all of these measurements are carried out by the software modules and transmitted to the database 30 for storage.

[0101] This set of heterogeneous measurements 41, 42, 43 (or equivalent variants) makes it possible to obtain a complete and holistic vision which makes it possible to determine a state of the user in relation to a possible dependence on screens. According to this embodiment, this set provides a photograph which optimizes the determination of a relevant state of the user.

[0102] The measurements 41, 42, 43 collected by the software modules can be stored in real time or near real time in the database 30.

[0103] The stored measurements can then be consumed periodically by a server 50 asynchronously, in order to determine aggregated measurements. These aggregated measurements take into account all the measurements 41, 42, 43 concerning a user and, therefore, all the screens that the user may be required to use over time.

[0104] According to one embodiment, the server 50 queries the database 50 once a day in order to determine aggregated measurements. The aggregated measurements are then representative of the user's daily behavior with respect to the screens available to him.

[0105] Aggregated measures are based on heterogeneous measurements from different and varied sources. For example, the usage times of all devices can be aggregated to obtain a total amount of time spent by a person in front of a screen. Similarly, the usage times of the same application (for example, a social network like Facebook®) can be aggregated across all devices.

[0106] According to one embodiment, it is planned to determine aggregated measurements based on measurements of the same type from different equipment.

[0107] These aggregated measures may consist of the following calculations (or equivalents): time spent in front of each application: sum of the durations of use of each application during the period considered; overall time spent in front of each computer screen: sum of the durations of use of a device (these durations being the differences between the times of disconnection and connection to a device); overall time spent in front of each telecommunications terminal screen (“smartphone” or digital tablet, etc.): sum of the durations of use of a device (these durations being the sums of the durations of use of a device (these durations being the sums of the durations of use of the applications that appeared in the foreground); digital sunset: maximum (i.e. latest) time of disconnection on all devices 11, 12, 13, 14; digital sunrise: minimum time of connection on all devices 11, 12, 13, 14;calculation of waking time spent away from screens: difference between the sum of the overall times spent in front of each screen and the duration of a waking day (calculated by the difference between 24 hours and the user's average sleep duration); opening time of each application: difference between the time the application is launched and the time it is connected to the corresponding device; regularity in digital sleep times: difference between digital bedtimes over two consecutive days; difference between digital bedtime and the average self-reported bedtime in the sleep diary; Finally, each application is associated with a usage category among, for example, "social", "games", video", "work" and "others".;

[0108] Aggregated measurements, and therefore the degree of screen dependency, may take into account other data as well, including data not derived from objective measurements carried out by software modules.

[0109] For example, according to one embodiment of the invention, data such as responses to questionnaires or other subjective information provided by the user can be used to supplement the objective measures and be aggregated therewith for the purpose of calculating the degree D. This information can for example correspond to weekly mood or physical activity questionnaires.

[0110] Thus, all kinds of data can be used. One of the main ideas of the invention lies precisely in the aggregation of heterogeneous data from different and varied sources in order to construct a holistic view of the user's behavior when faced with their different screens.

[0111] From these aggregated measurements (and therefore, indirectly, from measurements 41, 42, 43 collected by the software modules), the server can determine a degree of dependence on the screens. This determination can be periodic, in particular according to the same period as the query of the database 30.

[0112] According to one embodiment, this degree of dependence on screens can be seen as a quantification of the user's use of screens.

[0113] According to one embodiment, this degree of dependence D can be a linear combination of the aggregated measures m i previously determined. We can write the equation giving D as follows:

[0114]

[0115] in which has i is a weight associated with the influence of the aggregate measure m i in determining the degree D, and n is the number of aggregated measurements

[0116] According to one embodiment, the equation can be written as follows:

[0117]

[0118] The value of degree D is thus between 0 (no dependence) and 1 (strong dependence).

[0119] The parameters a i can be determined in different ways.

[0120] For example, they can be obtained by linear regression, Bayesian networks, k-nearest neighbors algorithm, decision trees, artificial neural networks, logistic regression, etc.

[0121] For example, degree D can be calculated by:

[0122] D = 1 / [1 + exp (- (-7.757

[0123] + 0.433 * video game duration

[0124] + 0.146 * duration of social networks

[0125] + 0.045 * streaming duration (video stream viewing)

[0126] + 0.156 * digital sunset

[0127] - 0.186 * digital lever

[0128] - 0.005 * video game frequency

[0129] + 0.457 * social media frequency

[0130] - 0.058 * streaming frequency

[0131] + 0.203 * computer time

[0132] + 0.139 * smartphone time

[0133] + 0.051 * tablet time

[0134] + 0.229 * game console time ) ) ]

[0135] This digital lifestyle hygiene level D can then be used in different ways: it can be transmitted to the user's equipment, to enable it to be displayed and thus indicate monitoring, period after period, it can be transmitted to a third party (for example an addiction specialist or psychologist) who can thus monitor the evolution of the user's condition; it can enable the user's access to their equipment to be controlled.

[0136] In particular, in the latter case, depending on the degree of dependence on screens, certain applications may be blocked, for example beyond a certain time spent over a period, or during certain time slots.

[0137] For example, "games" or "video" type applications can be blocked during working hours, or beyond 2 hours per day, for example, if the degree of screen addiction exceeds a predetermined threshold.

[0138] Thus rules can be established which depend not only on elements of duration, time, but also on the degree of dependence on screens D.

[0139] According to one embodiment, it is also possible to analyze in real time the images consulted by a user within the open applications, for example by a previously trained artificial intelligence engine, to increase the fidelity of the digital lifestyle qualification data.

[0140] According to one embodiment, the server is adapted to determine whether a user suffers from a screen dependency, or addiction, based on the degree of screen dependency. In particular, it may be adapted to assign a class to the user based on said degree of screen dependency. This class may be chosen, for example, from normal behavior, abnormal but non-problematic behavior, and problematic behavior that may be related to a screen dependency, or addiction.

[0141] In particular, the system may be provided for controlling the use of the screens by a user. According to one embodiment, the equipment is initially restricted, at the start of a first time period, to a first set of functionalities, by means of the software modules and comprises means for determining behavioral information of the user and for transmitting this behavioral information to the server; this server is adapted to grant an additional functionality from a second set of functionalities of the equipment as a function of this behavioral information, and to transmit to the software module of a selected equipment from the set of equipment, a message to allow the user to access this additional functionality.

[0142] This additional functionality can be determined based on the user's degree of screen dependency.

[0143] The degree of dependence on D screens, as well as aggregated measures m i and the different rules allowing action on the equipment 11, 12, 13, 14 depending on this degree D can be accessible to external equipment 60. This external equipment can belong to a third party, such as a psychologist, an addiction doctor, etc.

[0144] The external equipment 60 can communicate with the server 50 in various conventional ways. For example, the server 50 may have a web server allowing its data to be exported via a web interface and via the http protocol.

[0145] According to one embodiment, the server 50 may be implemented by a set of circuits co-located in a centralized server or distributed within a server or among a set of servers. This set of servers may include "server farm" or cloud computing arrangements.

[0146] The user can thus be monitored remotely by a third party, via the transmission of the degree of dependency recalculated by periods (for example daily) from the server 50 to the external equipment 60.

[0147] According to one embodiment, a monitoring period over a few weeks (for example 3 weeks) can be set up in order to obtain a relevant view of the evolution of the user's addiction.

[0148] According to one embodiment, the fidelity of the data can be increased for the probe embedded in an electrical outlet or the device 203 with the detection of the user's smartphone. It is indeed usual for a user to have their smartphone nearby or even on them, and to move around with it. The detection of the user's smartphone can therefore make the data detected by the embedded probe or the base (device 203) more robust. Thus, if the user's smartphone is not detected within a Bluetooth radius of 10 meters, this means that the user is not present and the data from the probe embedded in a socket is not detected.

[0149] According to one embodiment, data fidelity may be increased for the probe embedded in an electrical outlet or device 203 with detection of the user's smartphone by ignoring data sent during the user's digital bedtime.

[0150] According to one embodiment, the fidelity of data from a tablet may be increased by providing a different password to each user to unlock the tablet to determine whether the user to be monitored is currently using the tablet. After a specified period of non-use of the tablet, for example fifteen minutes, the tablet requests a password again to prevent a user from using the account of another user who has abandoned the tablet without logging out of the password.

[0151] Of course, the present invention is not limited to the examples and the embodiment described and shown, but is defined by the claims. It is in particular susceptible of numerous variants accessible to those skilled in the art.< / category> < / category> < / deviceid> < / model>

Claims

System (1) for determining a degree of screen dependency of a user (2), comprising at least one software module (23, 24) embedded on a set of information processing equipment (13, 14), adapted to collect first measurements (42) on the behavior of applications installed on said information processing equipment and second measurements (43) on the behavior of said information processing equipment; a database (30) for storing said measurements; a server (50) for periodically determining an aggregation of said measurements and a degree of screen dependency based on said aggregation, further comprising at least one physical sensor capable of collecting third measurements relating to said at least one piece of equipment; said server being adapted to determine said aggregation based on said third measurements. System according to claim 1, wherein said at least one physical sensor is one of a probe (21, 22) embedded in an electrical socket (11, 12) supplying at least one piece of equipment including a television and a video game console, capable of collecting third measurements (41) on the electrical behavior of said at least one piece of equipment, a motion detection device (101) for detecting a disconnection of the power supply of at least one piece of equipment, capable of collecting third measurements relating to the position of at least one piece of equipment, and a base (203) capable of collecting third measurements relating to the position of at least one piece of equipment. System according to claim 2, wherein said electrical socket is adapted to collect a particular measurement in the event of physical disconnection of said at least one piece of equipment. System according to claim 3, wherein said electrical outlet is arranged so that upon said physical disconnection, said electrical outlet is no longer powered. System according to any one of claims 1 to 4, wherein said server is adapted to assign a class to said user based on said degree of screen dependency. System according to any one of claims 1 to 5, wherein said server is adapted to determine an aggregation of measurements of the same nature from separate equipment. Method for determining a degree of screen dependence of a user (2), comprising collecting first measurements (42) on the behavior of applications installed on a set of information processing equipment, and second measurements (43) on the behavior of said information processing equipment, by at least one software module (23, 24) embedded on said set of information processing equipment (13, 14); storing said measurements in a database (30); periodically determining an aggregation of said measurements and a degree of screen dependence as a function of said aggregation, by a server (50);including further the collection of third measurements (41) on the electrical behavior of at least one piece of equipment, by a probe (21, 22) installed in an electrical outlet (11, 12) supplying said at least one piece of equipment among a television and a video game console, said aggregation taking into account said third measurements. ; A method according to claim 7, comprising assigning a class to said user, according to said degree of dependence on screens. Method according to claim 8, implemented for a predefined duration.

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