Accessibility assessment for cosmetic applicators configured for users with limited mobility

Abstract

ACCESSIBILITY DIAGNOSIS FOR COSMETIC APPLICATOR CONFIGURED FOR USERS WITH LIMITED MOBILITY An accessibility diagnostic system is proposed for a motion stabilization device for stabilizing a cosmetic applicator.The system includes a mobile user device that has a touchscreen and a motion sensor, the mobile user device including processing circuitry configured to: display a request to a user for an input of a specific tracing motion or a specific displacement of the mobile user device, and collect information indicating a pattern of hand movement of the user from the results of the user input in response to the request; and a server device that is connected to the mobile user device via a network, the server device including processing circuitry configured to receive the information collected from the mobile user device, determine an amount of motion stabilization to be established for the motion stabilization device from the information collected, and generate the determined amount of motion stabilization.Figure for the abridged version: none.

Description

Title of the invention: ACCESSIBILITY DIAGNOSIS FOR COSMETIC APPLICATOR CONFIGURED FOR USERS WITH LIMITED MOBILITY DOMAIN

[0001] The present disclosure describes a system and features relating to a device for modifying, mitigating, changing, reducing, compensating for or the like the movement of a cosmetic applicator caused by involuntary movements, tremors, limited mobility or the like of a user. Context

[0002] Involuntary body movements, or tremors, can occur in people with motor disorders or even in healthy people. Because of these involuntary movements, a person may have difficulty performing a task that requires care and precision, such as applying a cosmetic composition to a part of the body, including the face, hands, or feet.

[0003] Therefore, there is a need for a solution that allows the application of a cosmetic composition that is compatible with the diverse and disposable nature of cosmetic applicators. SUMMARY

[0004] In one embodiment, an accessibility diagnostic system is provided for a motion stabilization device for stabilizing a cosmetic applicator, comprising: a mobile user device that includes a touchscreen and a motion sensor, the mobile user device including processing circuitry configured to: display a request to a user for input of a specific tracing motion or a specific movement of the mobile user device, and collect information indicative of a movement pattern of the user's hands based on the user's input results in response to the request;and a server device that is connected to the mobile user device via a network, the server device including processing circuitry configured to receive the collected information from the mobile user device, determine an amount of motion stabilization to be established for the motion stabilization device based on the collected information, and generate the determined amount of motion stabilization. ;

[0005] In one embodiment, inputting a specific tracing motion comprises at least one of tracing a straight line and tracing a pattern. circular.

[0006] In one embodiment, inputting a specific movement of the mobile user device comprises at least one of moving the mobile user device near the user's face and rotating the mobile user device in a predetermined direction.

[0007] In one embodiment, the mobile user device is configured to provide a questionnaire to the user and the amount of motion stabilization to be established for the motion stabilization device is further based on the user's responses to the questionnaire.

[0008] In one embodiment, the processing circuitry of the server device is configured to combine the information collected from the mobile user device and determine whether motion stabilization is active or static based on comparing a value associated with the collected information to a threshold.

[0009] In one embodiment, the processing circuitry of the server device is configured to determine whether motion stabilization is active or static for at least one particular cosmetic application based on comparing a value associated with the collected information to a threshold.

[0010] In one embodiment, the processing circuitry server device determines the amount of motion stabilization by inputting the collected information into a neural network that is trained to generate a motion stabilization profile based on pre-existing combinations of collected information about the motion stabilization profiles. Brief description of the drawings

[0011] A more complete appreciation of the embodiments and numerous advantages associated therewith will be readily obtained, as the same will be better understood by reference to the following detailed description when considered in conjunction with the accompanying drawings:

[0012] [Fig-1] [Fig.l] shows a motion stabilizing device.

[0013] [Fig.2] [Fig.2] shows how the motion stabilization device pair with an adapter and a makeup applicator.

[0014] [Fig.3A] [Fig.3A] shows a diagram of the internal components of a motion stabilizing device.

[0015] [Fig.3B] [Fig.3B] shows a diagram of an alternative embodiment of the motion stabilizing device in which the receiving portion comprises an electromagnetic positioner instead of the driving elements shown in [Fig.3A].

[0016] [Fig.4] [Fig.4] shows an overview of a handle connection system universal adapter.

[0017] [Fig.5] [Fig.5] shows a system according to one embodiment which comprises a mobile user device, a motion stabilizer and a server device.

[0018] [Fig.6A][Fig.6B] Figures 6A and 6B show two challenges involving the user attempting to trace objects on the smartphone itself.

[0019] [Fig.6C][Fig.6D] Figures 6C and 6D show examples of how results are detected based on the challenges presented in Figures 6A and 6C.

[0020] [Fig.7A][Fig.7B][Fig.7C][Fig.7D] Figures 7A-7D show four challenges related to moving the smartphone itself in space.

[0021] [Fig.7E][Fig.7F] Figures 7E and 7F show how results are received for any of the challenges shown in Figures 7A-7D.

[0022] [Fig.8] [Fig.8] shows additional information about collecting information about the user with a questionnaire.

[0023] [Fig.9] [Fig.9] shows that on the server device, the results of the different challenges are provided as input to a diagnostic engine.

[0024] [Fig. 10] [Fig. 10] illustrates that one method of applying data collection to the motion stabilizer is to make a binary decision on whether or not to use the motion stabilizer during certain types of cosmetic applications.

[0025] [Fig. 11] [Fig. 11] shows a process that relies specifically on the results of the challenge shown in [Fig.6A].

[0026] [Fig. 12] [Fig. 12] shows a process that is specifically based on the results of the challenge shown in [Fig.6B], where a user is asked to draw a circle.

[0027] [Fig. 13] [Fig. 13] is a diagram showing how machine learning can help determine motion stabilization settings.

[0028] [Fig. 14] [Fig. 14] shows the use of the deep learning model once the training has reached an adequate level.

[0029] [Fig. 15] [Fig. 15] shows an example of a display for a user based on the results of the diagnosis in the form of an “adjustment graph.”

[0030] [Fig. 16] [Fig. 16] is a more detailed block diagram illustrating a mobile user device according to certain embodiments of the present disclosure.

[0031] [Fig. 17] [Fig. 17] shows a hardware description of the server device. DETAILED DESCRIPTION

[0032] The present disclosure describes a cosmetic applicator system that minimizes, modifies, mitigates, changes, compensates for, or the like, unintentional movements by stabilizing, orienting, operating, controlling, etc., an applicator for a user and is also designed to be flexible to accommodate different types of commercially available cosmetic applications. The present disclosure further describes a system and features to enhance the functionality of such a cosmetic applicator system.

[0033] The basic features and operation of a motion stabilizing device for a cosmetic applicator are described in U.S. Patent No. 11,458,062.

[0034] [Fig.l] shows a conventional motion stabilizing device 1100, which serves as a base unit for receiving a cosmetic applicator according to one embodiment. The device 1100 includes a handle portion 1101, a receiving portion 1102 and a strap 1103. The receiving portion 1102 includes an interface 1104, shown as a male connector that couples with a cosmetic applicator, which will be discussed in detail below. The receiving portion may be used for communication between the base unit and the applicator. Connection to an adapter and / or an applicator may be achieved using a mechanical coupling, such as a screw-on or snap-on connection or using magnets.

[0035] [Fig.2] shows how the device 1100 couples with an adapter 1105 and a makeup applicator 1106. It can be seen that the adapter fits over the exposed end of the receiving portion 1102. The adapter includes electrical mating connectors (a female connector - not shown) in a recessed portion for making contact with the electrical interface of the receiving portion 1101.

[0036] As shown in [Fig. 2], the receiving portion 1102 is configured to contort, articulate, reposition, etc., between an upright posture (as shown in [Fig. 1]) and a reclined posture (as shown in [Fig. 2]). This is accomplished using a hinge mechanism contained within the receiving portion 1102. [Fig. 2] shows that the hinge mechanism is a self-leveling / motion-stabilizing hinge.

[0037] [Fig. 3A] shows a diagram of the interior components of the device 1100 according to one embodiment. In the handle portion, the device includes a power source 1301, which may be a battery or the like. The device includes a printed circuit board assembly (PCBA) 1302, which may include the position sensor circuit 1307, the reader circuit 1308, the control circuit 1309 and the communication interface 1310, as understood in the art.

[0038] For example, like the sensor circuit 1307, the PCBA may include at least one inertial sensor and at least one distributed motion sensor to detect involuntary muscle movements and measure signals related to these involuntary muscle movements that are created when a user adversely affects the movement of the applicator. These sensors also detect movement of the stabilized output relative to the device. The control circuits send tension controls to the motion-generating elements (described below) in response to signals to cancel tremors or involuntary muscle movements of the user. This cancellation maintains and stabilizes a position of the applicator, keeping it stable.

[0039] Those skilled in the art will readily appreciate that a system and method in accordance with the present invention may utilize various implementations of the control circuitry and sensor circuitry and which would be within the spirit and scope of the present invention. In one embodiment, the control circuit 1309 includes an electrical system capable of producing an electrical response from sensor inputs such as a programmable microcontroller or a field-programmable gate array (FPGA). In one embodiment, the control circuit includes an ATMEGA8A 8-bit programmable microcontroller manufactured by Atmel due to its low overall cost, low power consumption, and ability to be used in high-volume applications.

[0040] In one embodiment, the at least one inertial sensor in the sensor circuit is a sensor comprising, in particular, an accelerometer, a gyroscope or a combination of both. In one embodiment, the at least one motion sensor distributed in the sensor circuit is a contactless position sensor comprising, in particular, a Hall effect magnetic sensor.

[0041] The system created by the combination of the sensor circuit, the control circuit, and the motion generating elements may be a closed-loop control system that senses motion and acceleration at various points in the system and feeds detailed information to a control algorithm that moves the motion generating elements appropriately to cancel out the net effect of a user's involuntary muscle movements and thereby stabilize the position of the applicator. The operation and details of the control system elements and the control algorithm are within the art, as described in US PG Publication 2014 / 0052275A1.

[0042] The communication interface 1310 may include a network controller such as BCM43342 Wi-Fi, frequency modulation and a Bluetooth combo chip from Broadcom, for interfacing with a network.

[0043] In the receiver portion of the device, there may be two motor elements to enable three-dimensional movement of the receiver as anti-shake movement. The two motor elements include a y-axis motor element 1303 and an x-axis motor element 1304, each connected to and controlled by the PCB A 1302. Each of the motor elements may be servomotors as understood in the art. The device further includes an end effector coupling 1305, which is configured to be coupled with the adapter 1105. The end effector coupling Terminal 1305 may include a radio frequency identification (RFID) reader 1306, configured to read an RFID tag, which may be included with the applicator, as shown below.

[0044] [Fig. 3B] shows a diagram of an alternative embodiment of the device 1100 in which the receiving portion comprises an electromagnetic positioner 1311 instead of the driving elements shown in [Fig. 3A]. The electromagnetic positioner 1311 may have U-shaped magnetic cores 1312 arranged around a non-magnetic tube 1313, filled with a magnetic fluid 1314. Each of the magnetic cores has arm portions surrounded by windings 1315. The magnetic cores may be controlled by the PCB A control circuit 1302 to act as a controllable active magnetic field generating structure that is used to generate a varying magnetic field that acts on the magnetic fluid, causing it to move, thereby allowing the armature to be moved into the desired coordinate position and / or orientation.Details of the implementation of the electromagnetic positioner 1311 are found in U.S. Patent No. 6,553,161.

[0045] In the conventional motion stabilization device described above, there is a problem, namely that the interface 1104 which receives the adapter 1105 requires a specific attachment point to properly align with the interface.

[0046] Therefore, the embodiments below provide a universal adapter connection between the handle of the motion stabilization device to improve the user experience and reduce the difficulty and time required to configure the system for use.

[0047] In one embodiment, the present disclosure relates to a cosmetic applicator. The cosmetic applicator may be used for a variety of cosmetic applications, including, but not limited to, mascara, eyeliner, eyebrow products, lip products (lipstick, lip gloss, lip liner, etc.), skin and / or hair products. In one embodiment, the cosmetic applicator may include an adapter, wherein the adapter may connect the cosmetic applicator to a motion stabilizer. The motion stabilizer may be, for example, a handle that may prevent involuntary movements such as tremors or spasms. These movements may interfere with the application of cosmetic products and may also make general interaction with cosmetic applicators or tools difficult.For example, many cosmetic products require a twisting motion or force to open or extrude the product. It may be difficult for users to achieve the range of motion or precision necessary to apply these forces to the cosmetic product. In one embodiment, the applicator. cosmetic may carry a cosmetic product and may allow the appropriate force to be applied to the cosmetic product to open, close, mix, stir, agitate, extrude, or achieve other similar functions necessary for application.

[0048] [Fig. 4] shows an overview of a universal adapter handle connection system 400. The system includes a motion stabilizing device 150 that has a handle portion 151 and a hinge portion 152 (receiving portion) that is functionally similar to the device 1100 shown in [Fig. 1]. It further includes a universal adapter 100 that attaches to the device 150 and also contains various types of cosmetic product applicators. The basic features and operation of the universal adapter handle connection system 400 are described in co-pending U.S. applications 18 / 091,882; 18 / 091,920; 18 / 091,843; 18 / 091,925; 18 / 148,957; 18 / 148,880; and 18 / 148,930.

[0049] For the device described above, due to the different limitations caused by different disabilities, understanding what level of assistance is needed to provide a useful / accurate assisted makeup application experience (i.e., how many degrees of freedom and how much automation of the device) can be challenging. The embodiments below provide a simple self-guided diagnostic tool for home use. Users use an online or app-based tool to repeat simple exercises that will help diagnose how much assistance they need from the device and can make a recommendation on which device options are best suited to their needs (if any).

[0050] [Fig. 5] shows a system 500 according to one embodiment comprising a mobile user device 510 and the motion stabilizer 520 described above. The system further comprises a cloud server device 530 which connects to both the smartphone and the motion stabilizer. The smartphone will offer the user multiple challenges and possibly a questionnaire to diagnose the assistance he will need in terms of motion stabilization when using the device.

[0051] The system measures: shaking, challenge execution time, model accuracy, detects phone drop, asks about pain / discomfort and records sound. Concretely, the smartphone is used to ask users to perform movements such as: drawing a line (shake check), drawing a circle (prediction check), bringing the smartphone to the face (elbow mobility check), rotating from portrait to landscape (wrist mobility check), detecting a fall (finger grip check). The smartphone records the position in real time using an accelerometer / gyroscope / camera.

[0052] Figures 6A and 6B show two challenges involving the user attempting to draw objects on the smartphone itself. [Fig.6A] asks the user to draw straight lines, and [Fig.6B] asks the user to draw circular patterns. It is possible to display a target shape that the user will attempt to draw within a shaped region.

[0053] Figures 6C and 6D show examples of how results are detected based on the challenges shown in Figures 6A and 6C. As shown in Figures 6A and 6B, the target shape has a certain thickness within which the user essentially draws. The centroid of the user's touch on the touchscreen is detected, as understood in the art. [Fig.6C] shows an example where the user draws a rather straight line that stays with the displayed target region. When the user keeps the line within the region, it can be considered to have a deviation of 0%. In contrast, [Fig.6D] shows an example when the user is unable to keep the line straight and within the displayed region. In this situation, half of the user's touch is outside the region and this therefore represents a deviation of 50%. The same method of deviation detection applies to the circle example shown in [Fig. 6B]..

[0054] Although the above method describes a way to detect whether a user has successfully drawn a line or circle, other methods may be used as understood in the art. For example, a method for recognizing graphical objects, such as lines and circles, is described in U.S. Patent No. 10,372,321. In addition, image recognition techniques may be used to determine whether the user has successfully drawn a recognizable line or circle.

[0055] Figures 7A-7D show four challenges related to moving the smartphone itself in space. [Fig.7A] shows a challenge in which the user is asked to bring the phone close to a target area, such as the lips or eyes. This challenge aims to demonstrate a user's ability to control a device while bringing it close to their face.

[0056] [Fig.7B] shows a challenge in which the user is asked to attempt to rotate the smartphone forward or backward in landscape mode. [Fig.7C] shows a challenge in which the user is asked to rotate the smartphone clockwise or counterclockwise. These challenges are intended to demonstrate a user's ability to perform wrist movements while using the device during makeup application.

[0057] [Fig.7D] shows a challenge in which the user is asked to hold the smartphone still. This challenge aims to determine the level of involuntary movement of the user's hands when simply holding the device in space.

[0058] Figures 7E and 7F show how the results are received for any of the challenges shown in Figures 7A-7D. [Fig.7E] shows the vibration amplitude for a user who does not show signs of involuntary hand movements while performing one of the challenges. However, 7F shows the vibration amplitude for a user who shows signs of involuntary hand movements while performing one of the challenges. As shown in [Fig.7F], the vibration amplitude is beyond a threshold amount X.

[0059] [Fig.8] shows additional information about collecting information about the user with a questionnaire. These questions may ask for age, gender, and health conditions. In addition, the user will be asked if he has a particular health condition that affects the movement of his hands.

[0060] Data collection from different tests and questionnaires can take different forms. For example, a percentage of line-keeping accuracy when drawing lines or circles can be collected. In addition, the nature of the drawing (such as a "wobbly" drawing pattern) will also be detected.

[0061] Similarly, shaking of the smartphone while the user attempts to bring the smartphone to a target area of ​​the face, or during rotation exercises, will be detected.

[0062] The data collected during the challenges is transmitted to the server device 530. The server device will analyze the data to determine the amount and type of support that the motion stabilizer device should provide.

[0063] [Fig.9] shows that on the server device 530, the results of the various challenges are provided as input to a diagnostic engine 901, which is implemented by processing circuitry at the server device 530.

[0064] [Fig. 10] illustrates that one method of applying data collection to the motion stabilizer is to make a binary decision on whether or not to use the motion stabilizer during certain types of cosmetic applications. At step 1001, the results that are passed to the diagnostic engine are normalized and combined. For example, all of the results can be transformed into an integer value. When the user attempts to draw the line or circle, each time the user deviates from the path, a counter will be incremented to give an integer value. To address challenges when the smartphone is brought closer to the face or rotated to landscape mode, each time the user shakes the phone in the process, a counter will be incremented. In addition, certain questions asked in the questionnaire will cause a counter to be incremented.For example, if the user answers "yes" to the presence of tremors, then this will increase a counter.

[0065] In step 1002, the combined integer value of all counters is compared to a threshold number. This number may be predetermined based on combined data from multiple users. In step 1003, if the number is greater than or equal to the number threshold, it is then determined that motion stabilization should be enabled. In step 1004, if the number is not greater than or equal to the threshold number, then motion stabilization should not be enabled (i.e., the device should be static).

[0066] While the above process of [Fig. 10] represents a simplified method of determining a binary setting for the motion stabilization feature on the device, a customized approach can also be used. For example, some results indicate that the user may need motion stabilization for one application, but not for another. [Fig. 11] shows a process that relies specifically on the results of the challenge shown in [Fig. 6A]. In step 1101, the results of the straight line challenge are normalized. In step 1102, the results are compared to a threshold value. Then, in step 1103 or 1104, motion stabilization will be enabled or disabled for lipstick, eye shadow, or mascara applications based on the results.

[0067] Alternatively, [Fig. 12] shows a process that is specifically based on the results of the challenge shown in [Fig.6B], where a user is asked to draw a circle. In step 1201, the results of the circle line challenge are normalized. In step 1202, the results are compared to a threshold value. Then, in step 1203 or 1204, motion stabilization will be enabled or disabled for skincare applications.

[0068] The above processes show considerations of the diagnostic engine when adjusting the motion stabilizer. However, if the results show a shaky nature of either of the challenges in [Fig. 7A] or 7B, then the diagnostic engine can overwrite the results of the processes in [Fig. 11] or 12, while still enabling motion stabilization.

[0069] It is also possible to define certain parameters in the motion stabilizer based on the results obtained from the diagnostic engine. For example, the results can be used to enable / disable different variables, or weight variables, relating to rotation or flexion. Since a specific user profile can be complex to customize, machine learning can also be used to determine the optimal settings for a user.

[0070] [Fig. 13] is a diagram showing how machine learning can help determine motion stabilization settings. During training, data from previous users is collected and combines the results of the diagnostic challenges described above and the optimal motion stabilization settings profile that was used for a respective user. These inputs are provided in step 1301, where normalized and combined results similar to those described above are provided as input with the motion stabilization profile which essentially acts as a label.

[0071] Inputs are provided to a deep learning algorithm in step 1302. The deep learning algorithm used may be based on available software as known in the art, such as Tensorflow, Keras, Mxnet, Caffe, or Pytorch. The labeled training result will be a neural network in step 1303. The created neural network has nodes of each layer that are grouped together, the groupings overlap, and each grouping passes data to multiple nodes of the next layer.

[0072] [Fig. 14] shows the use of the deep learning model once training has reached an adequate level. This is called the “inference time” because the recommendation will be inferred from the unlabeled input data. It can be seen that the input stage does not have a label of a motion stabilization profile. The inputs are fed to the trained neural network in step 1402, which will provide an output in step 1403 of the motion stabilization profile that best fits the normalized and combined input results of the user. With the neural network model described here, complex diagnostic results can be leveraged to determine a personalized motion stabilization profile for a user without having to devise predetermined manual adjustments.

[0073] [Fig. 15] shows an example of a display to a user based on the diagnostic results in the form of a "fit graph." As shown, different types of cosmetic applications may populate the points along a perimeter of the graph, and color coding may be used to indicate which of the cosmetic applications will have motion stabilization, and which will not.

[0074] The embodiments described above make it possible to characterize the level of mobility of a user to verify whether a motion stabilizer will be useful or not, which will allow the consumer to determine whether the device will be useful to him or not, even before purchase.

[0075] Further, although the embodiments described above describe functionality performed by a server device 530, it will be appreciated that the functionality may be performed by the user device 510 or a personal computer (not shown) of the user.

[0076] [Fig. 16] is a more detailed block diagram illustrating a mobile user device 510 according to certain embodiments of the present disclosure. In certain embodiments, the user device 510 is a smartphone. However, those skilled in the art will appreciate that the features described herein may be adapted for implementation on other devices (e.g., a laptop, tablet, server, e-reader, camera, navigation device, etc.). The exemplary user device 510 includes a controller 3110 and a wireless communication processor 3102 connected to an antenna 3101. A speaker 3104 and a microphone 3105 are connected to a speech processor 3103.

[0077] The controller 3110 may include one or more central processing units (CPUs), and may control each element of the user device 510 to perform functions relating to communication control, audio signal processing, control of audio signal processing, processing and control of still and moving images, and other types of signal processing. The controller 3110 may perform these functions by executing instructions stored in a memory 3150. Alternatively or in addition to local storage of the memory 150, the functions may be performed using instructions stored on an external device accessed over a network or on a non-transitory computer-readable medium. As described above in connection with [Fig.16], the controller 3110 can execute instructions enabling the controller 3110 to operate as the display control unit 3211, the operation management unit 3212 and the game management unit 3213 shown schematically in [Fig. 16].

[0078] Next, a hardware description of the server device 530 according to exemplary embodiments is described with reference to [Fig. 17]. In [Fig. 17], the server device 530 includes a CPU 1700 that performs the processes described above / below. The process data and instructions may be stored in the memory 1702. These processes and instructions may also be stored on a storage media disk 1704 such as a hard disk drive (HDD) or a portable storage medium, or may be stored remotely. Furthermore, the claimed advances are not limited by the form of the computer-readable media on which the instructions of the inventive process are stored.For example, instructions may be stored on CD, DVD, in FLASH memory, RAM, ROM, PROM, EPROM, EEPROM, hard disk, or any other information processing device with which the [device] communicates, such as a server or a computer.

[0079] Further, the claimed advances may be provided as a utility application, background daemon, or component of an operating system, or a combination thereof, executing in conjunction with the X00 CPU and an operating system such as Microsoft Windows 7, UNIX, Solaris, LINUX, Apple MAC-OS, and other systems known to those skilled in the art.

[0080] The hardware elements in order to obtain the [device] can be made by various circuitry elements, known to those skilled in the art. For example, the CPU 1700 may be a Xenon or Core processor from Intel of America or an Opteron processor from AMD of America, or may be other types of processors that would be recognized by those skilled in the art. Alternatively, the CPU 1700 may be implemented on an FPGA, ASIC, PLD, or using discrete logic circuits, as would be recognized by those skilled in the art. Further, the CPU 1700 may be implemented as multiple processors working cooperatively to execute the instructions of the inventive processes described above.

[0081] The [device] of [Fig. 17] also includes a network controller 1706, such as an Intel Ethernet PRO network interface card from Intel Corporation of America, for interfacing with the network 1717. As can be appreciated, the network 1717 may be a public network, such as the Internet, or a private network such as a LAN or WAN, or any combination thereof and may also include PSTN or ISDN subnets. The network 1717 may also be wired, such as an Ethernet network, or wireless, such as a cellular network including EDGE, 3G, and 4G wireless cellular systems. The wireless network may also be WiFi, Bluetooth, or any other known form of wireless communication.

[0082] The [device] further includes a display controller 1708, such as an NVIDIA GeForce GTX or Quadro graphics adapter from NVIDIA Corporation of America for interfacing with the display 1710, such as a Hewlett Packard HPL2445w LCD monitor. A universal I / O interface 1712 interfaces with a keyboard and / or mouse 1714 as well as a touchscreen panel 1716 on or separate from the display 1710. The universal I / O interface also connects to various peripherals 1718, including printers and scanners, such as a Hewlett Packard OfficeJet or DeskJet.

[0083] A sound controller 1720 is also provided in the [device], such as Creative's Sound Blaster X-Fi Titanium, to interface with speakers / microphones 1722 and thereby provide sounds and / or music.

[0084] The universal storage controller 1724 connects the storage media disk 1704 to the communication bus 1726, which may be an ISA, EISA, VESA, PCI, or the like, to interconnect all components of the [device]. A description of the general features and functionality of the display 1710, keyboard and / or mouse 1714, as well as the display controller 1708, storage controller 1724, network controller 1706, sound controller 1720, and universal I / O interface 1712 is omitted here for brevity because these features are known.

[0085] Obviously, numerous modifications and variations of the present invention are possible in light of the above teachings. It is therefore to be understood that, within the scope of the appended claims, the invention may be practiced otherwise as specifically described herein.

Claims

Claims

1. An accessibility diagnostic system (500) for a motion stabilization device (520) for stabilizing a cosmetic applicator, comprising: a mobile user device (510) that includes a touchscreen and a motion sensor, the mobile user device including processing circuitry (3110) configured to: display a request to a user for input of a specific tracing motion or movement of the mobile user device (510), and collect information indicative of a movement pattern of the user's hands based on the results of the user's input in response to the request;and a server device (530) that is connected to the mobile user device via a network, the server device (530) having processing circuitry (1700) configured to receive the collected information from the mobile user device (510), determine an amount of motion stabilization to be established for the motion stabilization device based on the collected information, and generate the determined amount of motion stabilization.;

2. The accessibility diagnosis system of claim 1, wherein the input of a specific tracing motion comprises at least one of tracing a straight line and tracing a circular pattern.

3. The accessibility diagnostic system of claim 1, wherein the input of a specific movement of the mobile user device (510) comprises at least one of a movement of the mobile user device (510) near the user's face and a rotation of the mobile user device in a predetermined direction.

4. The accessibility diagnostic system of claim 1, wherein the mobile user device (510) is configured to provide a questionnaire to the user and the amount of motion stabilization to be established for the motion stabilization device is further based on the user's responses to the questionnaire.

5. An accessibility diagnostic system according to claim 1, in wherein the processing circuitry (1700) of the server device (530) is configured to combine the information collected from the mobile user device (510) and determine whether motion stabilization is active or static based on comparing a value associated with the collected information to a threshold.

6. The accessibility diagnostic system of claim 1, wherein the processing circuitry (1700) of the server device (530) is configured to determine whether motion stabilization is active or static for at least one cosmetic application based on a comparison of a value associated with the collected information to a threshold.

7. The accessibility diagnostic system of claim 1, wherein the server device (530) of processing circuitry (1700) determines the amount of motion stabilization by inputting the collected information into a neural network that is trained to generate a motion stabilization profile based on pre-existing combinations of collected information about the motion stabilization profiles.

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