Laminated elastomeric sensing device and method of manufacture

Abstract

This disclosure relates to a laminated elastomer sensing device and a method of manufacturing the same. Aspects of this technology include smart wearable devices, including the device having multiple sensors configured to detect the position and / or orientation of one or more limbs of a user. A further aspect of this technology includes a laminated elastomer sensing device having multiple electrically insulating and conductive layers positioned to provide a dielectric layer.

Description

1. Technical Field

[0002] This technology relates to laminated elastomer sensing devices and methods of manufacturing the same. This technology is particularly applicable to capacitive sensing devices and methods of manufacturing the same, and in some examples, the elastomer sensing devices may be suitable for use with smart wearable devices (e.g., gloves) and / or for virtual / augmented / mixed reality applications; however, this should not be considered a limitation of the technology. 2. Background Technology

[0004] 2.1 Human-Machine Interface Device

[0005] Human-computer interface devices (HCIs) are peripheral devices for computers that provide a limited range of input to control or trigger functions on the computer. For example, a mouse can provide: two movement axes that are typically mapped to a two-dimensional plane of the computer monitor; a mouse wheel to allow scrolling in the two-dimensional plane; and one or more buttons to provide limited input to the computer.

[0006] However, in many applications, a greater range of control is desired, such as when controlling objects in three-dimensional space or otherwise interacting with them. Video game controllers exist that provide the user with multiple joysticks, each offering independent dual-axis inputs, multiple buttons, and, in some cases, additional analog inputs. However, these devices are typically bulky and still offer limited interactive capabilities. For example, when interacting with virtual objects in three-dimensional space, the ability to quickly move, scale, rotate, transform, modify the geometry of objects, shade, color, or render them, or change the position or perspective of a virtual camera providing the object's viewport, can be advantageous. Currently, the industry standard for selecting between these modes is typically using a series of keyboard inputs (which users usually need to remember) or detailed menus.

[0007] Another limitation of existing input devices is their unsuitability for mixed reality applications, which blend the real world with a virtual environment. For example, when interacting with objects in the real world, it can be important for users to be able to free their hands to pick up objects or interact with controls. Therefore, it is generally impractical for users to carry peripheral devices such as video game controllers or keyboards while interacting with the real world.

[0008] Controllers designed for virtual environments, such as game controllers, can allow for coarse positional tracking and one or more buttons to provide input to the virtual world. However, these offer limited control in virtual environments, and while pointing and clicking are provided, these systems still rely on menu structures that can be cumbersome or tedious for navigating in 3D space. Furthermore, existing controllers used in virtual environments are typically handheld devices, so users cannot perform other functions with their hands simultaneously, which can be significant, especially in augmented reality and mixed reality applications.

[0009] 2.2 Virtual Environment

[0010] This technology relates to systems, methods, and / or apparatuses for interacting with virtual environments. This should be understood to include:

[0011] Computer interfaces, such as those typically presented on one or more two-dimensional screens;

[0012] Virtual reality, such as simulated three-dimensional environments;

[0013] Augmented reality, in which computer-generated images are overlaid on the user's view of the real world;

[0014] Mixed reality merges real-world environments with computer-generated environments, allowing objects to coexist in both environments.

[0015] Extended reality is a term that encompasses virtual, augmented, and mixed reality applications, and throughout this specification, references to virtual environments should be understood to include any or more of the aforementioned environments, including environments presented on a conventional two-dimensional computer screen.

[0016] 2.3 User Tracking

[0017] One approach to address some of the shortcomings of traditional human-machine interface devices is to implement user tracking in order to more generally identify the user's location, orientation, and actions. Various user tracking systems have been used in the past, but each of these systems has limitations that restrict its applicability to certain applications.

[0018] This technology may be intended to at least partially address any or more of these limitations, or at least provide the public with an alternative.

[0019] 2.3.1 Camera

[0020] Cameras can be used to track a user's body position in real time, making information about the position of the user's head, hands, and other limbs available. However, these systems typically require a dedicated, fixed space to function effectively. For example, one or more cameras might be positioned in a corner of a room, facing inward, to detect the movement of occupants within the room. As a result, the movement of individuals within the room can be used to control objects in a virtual environment or otherwise interact with them. However, these systems generally confine the user to a fixed space within the camera's viewport and therefore cannot be easily used in other rooms.

[0021] Detailed calibration procedures are typically performed as part of the setup and configuration of these camera-based systems, such as determining the relative positions of the cameras to each other and taking environmental conditions, such as room lighting, into account. Therefore, moving these systems between different rooms or environments is inconvenient.

[0022] User cameras can be used to at least partially address spatial constraints. For example, in augmented reality or mixed reality systems, users can hold a smartphone to capture video of a scene or environment, or they can use head-mounted cameras, as is becoming increasingly common in extended reality applications. However, because these devices require user installation, they are bulky, often uncomfortable, and have limited runtime due to battery limitations. Furthermore, handheld cameras occupy the user's hands, thus limiting the user's ability to perform other functions simultaneously.

[0023] Another limitation of camera-based tracking systems is that they often suffer from occlusion problems, where the camera loses tracking of parts of the body due to being blocked by the user's own body or by being blocked from seeing the user once the user interacts with objects in the environment.

[0024] Traditional camera-based systems that perform finger tracking also have many limitations. Due to the similarity of user fingers, it is difficult to determine which finger of the user's hand a detected finger corresponds to in any given image. Therefore, these systems are prone to errors in accurately mapping user fingers from the real world to the virtual environment.

[0025] Accurately tracking user movement in three-dimensional space is also challenging. For example, accurately tracking the position of a user's hand might require tracking a large number of positional variables, all contained within a relatively small area and potentially existing anywhere in three-dimensional space. Therefore, when using camera tracking, providing accurate tracking typically requires a large number of high-resolution cameras, relatively complex software, and significant user costs, while remaining susceptible to the aforementioned occlusion problems, lighting and environmental conditions, and the substantial computational resources required to process video images at high frame rates.

[0026] 2.3.1.1 Depth Camera

[0027] Some cameras possess the ability to measure distances to other cameras. These cameras are called depth cameras. For example, these cameras can combine time-of-flight techniques to infer distance information from the camera. However, these cameras tend to have limited ranging capabilities, can be sensitive to reflective and transparent objects, and require relatively expensive hardware and significant output power for their transmitters, making them less suitable for portable, battery-powered operation. Furthermore, like regular cameras, depth cameras require high computational resources to process the data they generate.

[0028] 2.3.1.2 Camera Constellation

[0029] External camera (ordinary or depth-based) constellations that directly track the hand or markers on the hand can reduce the effects of occlusion, but this comes at the cost of excessive camera redundancy and a large power budget, and is still susceptible to hand occlusion by other parts of the body or by the hand itself, and limits hand tracking to a fixed location and volume.

[0030] 2.3.2 Inertial Measurement System

[0031] Motion sensing electronics, such as accelerometers, gyroscopes, and magnetometers, can be used to track the relative movement of objects in three-dimensional space, and have relatively low weight and power consumption, and do not suffer from occlusion problems like camera-based systems.

[0032] Because these motion sensing devices typically lack a fixed external reference, they require integration of received data to determine how the device moves in three-dimensional space. This motion tracking method, known as dead reckoning, is prone to drift over time, making it unsuitable for applications requiring consistent accuracy. Catastrophic drift can occur within seconds without additional constraints and assumptions. Furthermore, since these devices operate by periodically sampling sensor values, measurement accuracy can be negatively impacted by violent movements and shocks.

[0033] Furthermore, since these devices only track a single point in three-dimensional space, a large number of these sensors may need to be incorporated into the user's entire body in order to track the user's entire body, especially in cases requiring complex tracking, such as hand tracking applications.

[0034] Although some devices incorporate multiple motion sensing units (called inertial measurement units or IMUs) in a single package, these devices remain rigid and require power and communication to transmit their information to external devices (such as computers). As a result, the system becomes more complex and, in some cases, more uncomfortable, as the number of sensors attached to the human body increases.

[0035] 2.3.3 Stress and Strain Sensors

[0036] Various aspects of this technology may relate to devices including stress and / or strain sensors (e.g., capacitive sensors). Capacitive sensors can be disposed in flexible membranes, such as those described in PCT Publication No. WO2015053638A1. These capacitive sensors are typically soft, flexible devices capable of easily adapting to the shape of the hand, both statically and as the hand undergoes complex movements. They are highly repeatable, do not drift, and consume very little power during operation.

[0037] However, when these capacitive sensors are incorporated into wearable devices such as gloves, they typically require calibration for a specific user or hand size to accurately map capacitance readings to hand position data. Furthermore, relatively complex control algorithms are needed to address the non-ideal electrical properties of the stretchable electrodes. Additionally, because these types of sensors only measure capacitance, they do not inherently provide information about the user's hand position in a three-dimensional environment.

[0038] 2.3.3.1 Sensor Manufacturing

[0039] Currently, various methods are used in the manufacture of capacitive sensors; however, in wearable devices such as gloves, it may be advantageous to use laminated elastomer layers to manufacture these sensors, so as to allow the sensors to be flexible and adaptable to the user's body.

[0040] U.S. Patent No. 10,228,231 B2 discloses a method for manufacturing an elastomeric capacitive sensor, the entire contents of which are incorporated herein by reference. The method describes the steps of bonding flexible compliant layers together using one or more sacrificial layers, which can be removed as needed during the manufacturing process, for example, by using a solvent.

[0041] Other methods for manufacturing sensors may include the process of printing electrodes on opposite sides of an elastomeric dielectric material. However, proximity to both sides of the dielectric typically requires suspending the dielectric within a frame, which significantly increases the complexity of handling the film, particularly in transferring the dielectric to the frame, handling the frame, and preventing deformation or distortion of the dielectric during electrode printing. Printing and stacking dielectric / electrode layers on a single side is possible, but forming electrodes in the appropriate locations is difficult due to the tendency of wet / uncured electrode materials to damage the dielectric, and there are significant constraints on the chemical composition of uncured electrode materials to enable printing. Lower viscosity electrode compositions can be made into thinner layers and are easier to pattern, but disadvantageously have higher base resistance and are more sensitive to stretching, cause more damage to the dielectric due to high solvent content, and have lower flexibility and are less robust when stretched. Higher viscosity electrode compositions offer advantageous lower resistance and desired stretchability and robustness, but produce thicker electrode layers and cannot be printed by any conventional methods. Furthermore, the suboptimal nature of the electrode material when depositing uncured electrode material onto the dielectric layer inevitably leads to variations in layer thickness. This can result in aesthetic and functional defects on the stack surface, such as wrinkles or localized depressions / voids when these electrodes are used in multilayer stacks. The abrupt changes in layer height due to the higher thickness at the electrode edges also create areas where air bubbles or voids can be trapped, potentially leading to the same failure mode. This problem is further exacerbated when adding higher layers to the sensor stack, as subsequent layers become less flat, increasing the likelihood of defects leading to visual or functional failure points. Casting a dielectric layer on top of an uneven surface can reduce but not eliminate the unevenness, as shrinkage is an inherent part of the curing process, resulting in raised areas above the electrode material. Therefore, the associated properties leading to failure risk cannot be completely eliminated.

[0042] 2.4 Hand tracking

[0043] This technology relates to systems, methods, and apparatuses for tracking the movement of a user's hand in three-dimensional space. User hand tracking presents each of the problems outlined above regarding body tracking, and has the added challenges of increased complexity, greater degrees of freedom of movement, relatively small space on the human body for mounting tracking hardware, and the need to provide the user with the ability to use their hand during the tracking process.

[0044] The human hand is a complex object that is difficult to model or track accurately. The index, middle, ring, and little fingers each have four joints: the carpometacarpophalangeal (CMC), metacarpophalangeal (MCP), proximal interphalangeal (PIP), and distal interphalangeal (DIP). Each joint has three theoretical degrees of freedom, which can be considered as rotations about three orthogonal axes X, Y, and Z. However, for practical purposes, the DIP and PIP joints can be simplified to one DOF (flexion), the MCP joint to two DOFs (flexion and spread), and the CMC to one DOF (flexion). The thumb has five DOFs, the CMC to three, the MCP to one, and the DIP to one, with the wrist adding two more DOFs (excluding rotation about the forearm axis, which is controlled by the forearm). If we only consider two points on the range of motion of each degree of freedom, namely the minimum and maximum values, there are 2^27 possible combinations or 134,217,728 possible hand orientations.

[0045] While not all degrees of freedom (DOF) are entirely independent, the number of possible hand poses becomes enormous, considering that each of these DOFs can be continuously moved through a maximum angular rotation between 30 and 100 degrees, depending on the DOF, and also considering the need for additional DOFs to describe the hand's position in space relative to external reference points (e.g., the viewpoint of the person to whom the hand belongs or the observer's viewpoint). This is further complicated when considering interpersonal differences in hand features: significant variations exist across the world's population in multiple dimensions such as size, shape, finger length, bone length, range of motion, and skin color. Each hand is unique in one aspect or combination of aspects.

[0046] 2.5 Purpose of the Invention

[0047] The purpose of this technology is to provide a control system, method, and / or apparatus configured to solve any one or more of the aforementioned problems.

[0048] Alternatively, the purpose of this technology is to provide a smart wearable device that can be used for user tracking purposes.

[0049] Alternatively, the purpose of this technology is to provide a laminated elastomer sensing device and / or a method for manufacturing it.

[0050] Alternatively, the purpose of this technology is to provide a method for manufacturing laminated elastomer sensing devices more reliably and / or with fewer surface defects.

[0051] Alternatively, the purpose of this technology is to at least provide the public with an alternative. 3. Summary of the Invention

[0053] According to one aspect of the present technology, a laminated elastomer sensing device and / or a method of manufacturing thereof are provided.

[0054] According to another aspect of the present technology, a smart wearable device is provided.

[0055] According to another aspect of the present technology, a smart wearable device is provided, which is provided with a plurality of sensors configured to detect the position and / or orientation of one or more limbs of a user.

[0056] According to another aspect of the present technology, a laminated elastomer sensing device is provided, comprising:

[0057] First electrical insulating layer;

[0058] Second electrical insulation layer;

[0059] Third electrical insulation layer;

[0060] First conductive layer;

[0061] Second conductive layer;

[0062] Wherein, at least one of the electrically insulating layers is positioned between the first conductive layer and the second conductive layer to provide a dielectric layer, and

[0063] Wherein, the first conductive layer is at least partially compressed into the first electrical insulating layer or the second electrical insulating layer, and wherein the second conductive layer is at least partially compressed into the second electrical insulating layer or the third electrical insulating layer.

[0064] According to another aspect of the present technology, a laminated elastomer sensing device is provided, comprising:

[0065] First electrical insulating outer layer and second electrical insulating outer layer;

[0066] First conductive electrode layer, second conductive electrode layer and third conductive electrode layer;

[0067] First electrically insulating dielectric layer and second electrically insulating dielectric layer;

[0068] Wherein, the first electrically insulating dielectric layer is positioned between the first conductive electrode layer and the second conductive electrode layer, and the second electrically insulating dielectric layer is positioned between the second conductive electrode layer and the third conductive electrode layer; and

[0069] in:

[0070] The first conductive electrode layer is at least partially compressed into the first electrically insulating outer layer.

[0071] The second conductive electrode layer is at least partially compressed into the first electrically insulating dielectric layer; and

[0072] The third conductive electrode layer is at least partially compressed into the second dielectric insulating layer.

[0073] According to another aspect of the present technology, a method for manufacturing a stacked body for a capacitive sensor is provided, the method comprising the following steps:

[0074] This allows the first conductive layer to bond with the second electrically insulating layer.

[0075] A compressive force is applied to cause the first conductive layer to align with the second electrical insulating layer.

[0076] According to another aspect of the present technology, a method for manufacturing a capacitive sensor is provided, the method comprising the following steps:

[0077] Position at least two stacked bodies within a compression device; and

[0078] The compression device is used to apply a compressive force between the at least two stacked layers.

[0079] In examples of this technology, the electrically insulating layer may be formed of an elastomeric material. For example, the elastomeric material may be silicone.

[0080] In an example of this technology, the conductive layer may include carbon.

[0081] In examples of this technology, the conductive layer may include carbon particles doped into an elastomeric material matrix. For example, the elastomeric material may be silicone.

[0082] In examples of this technology, the conductive layer may have a stiffness similar to that of the electrically insulating layer.

[0083] In examples of this technology, the conductive layer may have a stiffness greater than that of the electrically insulating layer. For example, the stiffness of the conductive layer may be at least 10 times greater than that of the electrically insulating layer.

[0084] In an example of this technology, when the electrical insulating layer is in an uncured or more preferably partially cured state, compression of the one or more conductive layers into the one or more electrical insulating layers may occur.

[0085] In an example of this technology, the method may further include the step of heating the one or more electrical insulating layers to transform the layers from an uncured or partially cured state to a cured state.

[0086] In an example of this technology, the conductive layer may include electrically doped silicone, such as carbon-doped silicone.

[0087] In an example of this technology, the conductive layer may be substantially cured or cross-linked before contacting the electrically insulating layer, thereby improving the dimensional stability of the conductive layer during processing.

[0088] In examples of this technology, the compression device can be a press. For example, the press can be a hydraulic, pneumatic, or mechanical press.

[0089] In examples of this technology, the compression device may be a roller. For example, the roller may be a laminator, a calender, or a cold rolling mill.

[0090] In an example of this technology, the press may include a positioning device configured to assist in positioning and / or securing the stacked body within the press.

[0091] In an example of this technology, the positioning device may include a frame configured to limit the lateral expansion of the stacked body in a direction substantially perpendicular to the direction of the compressive force.

[0092] In an example of this technology, the frame can be configured to restrict the compression of the layer stack within the press.

[0093] In an example of this technology, the framework may include a support platform configured to receive and support at least a portion of the layer stack.

[0094] In this example of the technology, the positioning device may be removable.

[0095] In an example of this technology, the conductive layer may be exposed within the capacitive sensor to facilitate connection to sensing electronics.

[0096] In one example of this technology, the capacitive sensor may include:

[0097] First electrical insulation support layer.

[0098] The first conductive electrode layer is supported by the first electrically insulating support layer.

[0099] A first electrically insulating dielectric layer, which is supported by a first electrically insulating support layer and / or a first conductive electrode layer, while keeping at least a portion of the first electrode layer uncovered within the capacitive sensor.

[0100] The second conductive electrode layer is supported by the first electrically insulating dielectric layer.

[0101] A second electrically insulating dielectric layer is supported by the first electrically insulating dielectric layer and / or the second conductive electrode layer, while at least a portion of the second conductive electrode layer remains uncovered within the capacitive sensor.

[0102] The third conductive electrode layer is supported by the second electrically insulating dielectric layer.

[0103] An electrically insulating top layer, supported by the second electrically insulating dielectric layer and / or the third conductive electrode layer, while keeping at least a portion of the third conductive electrode layer uncovered within the capacitive sensor.

[0104] In an example of this technology, the capacitive sensor may include at least one adhesive between any one or more layers.

[0105] In an example of this technology, the compression device can be configured to move a predetermined distance during use.

[0106] In an example of this technology, the compression device can be configured to apply a predetermined force during use.

[0107] Further aspects of this technology, which should be considered in all its novel aspects, will become apparent to those skilled in the art upon reading the following description which provides at least one practical application example of this technology. 4. Description of the attached drawings

[0109] The following description, by way of example only and not intended to be limiting, refers to one or more embodiments of the present technology with reference to the following figures, in which:

[0110] Figure 1 A three-dimensional view of a user tracking system configured to track the user's location in real-world space is shown.

[0111] Figure 2A An example is shown of a user wearing a motion capture suit and the corresponding representation of the user's skeleton in a virtual environment;

[0112] Figure 2B An example of a depth image of a hand is shown;

[0113] Figure 3A A first example of a system diagram according to one aspect of the present technology is shown;

[0114] Figure 3BA second example of a system diagram according to another aspect of the present technology is shown;

[0115] Figure 3C Another example of a system diagram according to another aspect of the present technology is shown;

[0116] Figure 3D An example of a rear view of a smart wearable device according to one aspect of the present technology is shown;

[0117] Figure 3E It shows Figure 3D A side view of a smart wearable device;

[0118] Figure 3F A system diagram of a smart wearable device according to the present technology is shown;

[0119] Figure 3G A block diagram of an electronic device housing according to an example of the present technology is shown;

[0120] Figure 4A An example of a roll forming apparatus for connecting layers of a capacitive sensor according to one aspect of the present technology is shown;

[0121] Figure 4B An example of a capacitive sensor according to one aspect of the present technology is shown;

[0122] Figure 4C A side cross-sectional view of a seven-layer capacitive sensor stack according to the present technology is shown;

[0123] Figure 4D An alternative side cross-sectional view of another form of a 7-layer capacitive sensor stack according to the present technology is shown;

[0124] Figure 4E A side cross-sectional view of another form of a 5-layer capacitive sensor stack according to the present technology is shown;

[0125] Figure 4F A side cross-sectional view of a compressed 7-layer capacitive sensor stack according to the present technology is shown.

[0126] Figure 5A A side cross-sectional view of one form of a two-layer stacked body according to the present technology is shown;

[0127] Figure 5B An example of a layer stack in one form of compression system according to the present technology is shown;

[0128] Figure 5C It shows Figure 5A A side cross-sectional view of the two-layer stacked body under compression.

[0129] Figure 5D An exploded side cross-sectional view of a stacked body according to an example of the present technology is shown;

[0130] Figure 5E A compressed side cross-sectional view of a 7-layer stack according to an example of the present technology is shown;

[0131] Figure 6A A perspective view of one form of capacitive sensor according to the present technology is shown;

[0132] Figure 6B A perspective view of a compression system with a positioning device according to the present technology is shown;

[0133] Figure 7A A side cross-sectional view of a three-layer stack according to the present technology is shown; and

[0134] Figure 7B A side cross-sectional view of a capacitive sensor comprising a three-layer stack, according to another form of the present technology, is shown. 5. Detailed Implementation

[0136] 5.1 Overview of User Tracking System

[0137] In some forms of this technology, a user tracking system 100 is provided. Figure 1 A first example of the present technology is shown, wherein a user tracking system 100 includes a user location tracking module 102 coupled to one or more sensors 104, and a processor 106 configured to receive location information from the user location tracking module 102.

[0138] In use, sensor 104 is configured to capture information about the location of user 108 within environment 110. For example, in the illustrated environment, sensor 104 includes cameras 112 that are raised above a surface 114 of the environment, such as mounted on a wall 116 or a bracket (not shown). By raising the cameras 112 above the surface where user 108 will walk, the likelihood of the cameras' field of view being obstructed or their view of user 108 being blocked is reduced.

[0139] exist Figure 1 In the example, the environment has been configured as an extended reality environment, such as a virtual reality (VR), augmented reality (AR), or mixed reality (MR) environment. Although not required for this technology, the user 108 in the illustrated example is equipped with an extended reality head-mounted device 118, which may include any one or more of a display, a sound device, a microphone, an inertial measurement system, and / or one or more cameras.

[0140] In use, when user 108 moves in the environment, sensor 104 can track the position of user 108, for example, by taking a series of photos or a video showing the user's position when using camera 112.

[0141] In some examples of this technology, sensor 104 can be configured to track specific shapes or colors presented within the environment as a way to reduce the computational complexity of the captured image. For example, in Figure 1 In this system, user 108 is equipped with a handheld controller 120, and sensors can be specifically configured to track the position of the handheld controller. For example, controller 120 may have a unique, identifiable shape that is unlikely to appear in other locations within the image. By using a unique shape, the user position tracking module 102 can be pre-programmed with information about the shape, such as its geometry and color. This allows for simplified tracking by being able to determine the distance to the sensor without requiring an expensive depth-sensing camera, for example, by taking into account the camera's properties and the size of the shape in the resulting image.

[0142] In another example of this technology, the controller 120 and / or may be configured to emit light of a specific frequency, which a sensor can detect, including light in the non-visible portion of the electromagnetic spectrum, such as infrared or ultraviolet light. The aforementioned passive and active technologies may be referred to as motion capture (“mocap”) tags, as those skilled in the art will know.

[0143] For example, such as Figure 2A As shown, in some motion capture applications, such as those used in film and television, actors may wear a bodysuit 202 comprising a series of unique markers 204, and sensors 104 are configured to detect these markers in order to map these positions onto corresponding bones 206 in a 3D model. Therefore, it is desirable that the motion capture markers be positioned at either end of a skeleton within the human body so that the corresponding bone in the "rigged" skeleton 208 can be mapped accordingly.

[0144] User location information can be provided to processor 106 by location tracking module 102. For example, the location information can be a series of images, which processor 106 processes to extract the desired location information; alternatively, the location information can be provided to the processor in a usable format, such as a series of three-dimensional coordinates corresponding to key user features. For example, the three-dimensional coordinates can include one or more handheld controllers 120, an extended reality headset 118, or other devices corresponding to user features. Figure 2A The position and / or rotation of the user's key body points (such as the position of the hands, feet, knees, elbows, pelvis, shoulders, and arms) shown in the diagram.

[0145] In some examples, location information may include depth images, point clouds, or other three-dimensional representations of points on the user's body. For example, Figure 2B The diagram illustrates a representation of a hand using depth images. When using depth images or point clouds, it becomes possible to determine the overall contours of the user's body, including, for example, the relative location of the hand. However, doing so can be computationally intensive, and as in the previous example, these camera-based systems are susceptible to occlusion.

[0146] Furthermore, in the example shown, Figure 2B The depth image shown corresponds to a part of the user's body. To obtain this depth image, point cloud, or other 3D representation of the body, further signal / image processing techniques may be required, such as distance-based removal of data points corresponding to the foreground or background of the image, compensation for occlusion and shadows, or other image processing techniques. Therefore, depth image processing is computationally intensive and is generally unsuitable for high frame rate applications or power / cost-sensitive applications.

[0147] 5.2 Application of this technology

[0148] Once the tracked location data is determined, this technology has many potential applications. In many applications such as animation, film, and games, the goal of a user tracking system can be to extract information that can be mapped to a skeleton in 3D software, so that the user's movements cause corresponding movements of the skeleton or a bound model around the skeleton in the virtual environment. For example, this technology can be used for:

[0149] Add natural human movement to animated characters;

[0150] Placing users in different environments, such as environments that would be expensive or dangerous to reproduce in a non-digital way;

[0151] Moving a character past and / or interacting with virtual objects in a 3D environment, such as in a VR game.

[0152] Therefore, in some examples of this technology, it is advantageous to extract the minimum set of information required to determine the user's skeletal position, thereby reducing the required computational processing power and potentially lowering the system's cost, size, and power consumption requirements.

[0153] In some cases, the location information described herein can be mapped to one or more poses or gestures. Generally, the reference to pose here should be understood as referring to a specific shape or orientation of a body part (e.g., a body part equipped with a smart wearable device). In contrast, a gesture is defined as a predetermined movement and can include pose information. For example, in the game of rock-paper-scissors, each of the hand positions for rock, paper, and scissors can be considered a pose, and the action of performing that pose—that is, extending the index and middle fingers to form the scissors gesture—would be considered a gesture.

[0154] For example, when a user opens their hand with their palm facing the sensor, this gesture can be detected as a "stop" command, which can then be used to trigger an action within the system. For instance, in a game console, this gesture can be used to pause the game, or in streaming video, it can be used to stop playback, pause playback, or mute audio.

[0155] While these large, obvious gestures can be detected by some systems, they are prone to false alarms, such as when a user reaches out to touch something in a virtual environment. As the ability to track a user's body and hands improves, users will be able to perform more precise and accurate movements; therefore, gesture detection technology may be advantageous in detecting more subtle gestures. For example, a user might be expected to perform subtle gestures, such as raising or lowering a finger to perform a specific action, such as zooming in or out of a camera, while the rest of the hand or both hands may be manipulating other functions of the robotic system.

[0156] Therefore, a feature of this technology is a method, hardware, and system for triggering actions using subtle gestures and postures, and for using one or more conditions to ensure that actions are not unintentionally triggered inappropriately.

[0157] Another limitation of existing gesture detection systems is addressing the aforementioned occlusion-related issues while balancing the computational cost of position detection systems, which increases with the amount of data processed. For example, in portable battery-powered systems, it may be advantageous to provide control and gesture detection using as little processing power (and therefore energy, and battery capacity in the portable system) as possible.

[0158] Therefore, the aspects of the technology described herein relate to providing any one or more of the following: systems, methods, and apparatus for providing location information that can be easily converted into gesture information; systems, methods, and apparatus for sending control commands based on gestures; and systems, methods, and apparatus for providing user-mappable gesture control in a user tracking system.

[0159] 5.3 Hardware

[0160] Figures 3A to 3DAn exemplary system diagram according to various aspects of the present technology is shown. For example, Figure 3A An example of the hardware used in the user tracking system 100 described herein is shown. In this example, the user tracking system 100 may include one or more location tracking modules 102, one or more sensors 104, and one or more processors 106.

[0161] Each of the foregoing will be described in more detail. However, it should be understood that any one or more of the components described herein may be housed in a single device or module. For example, position tracking module 102 may include sensor 104, or both sensor 104 and processor 106.

[0162] Furthermore, it should be understood that the location tracking module 102, one or more sensors 104, and one or more processors 106 can be configured to communicate with each other using any method known to those skilled in the art. For example, these components can be electrically connected to each other, such as using conductive traces on a printed circuit board (PCB) or one or more wires; alternatively, they can be configured to use one or more wireless communications (e.g., Bluetooth). TM They can communicate with each other. In another example of this technology, any or more of the components described herein can be configured to read and / or write to a shared memory device, such as random access memory (RAM), or a non-volatile memory device, such as electrically erasable programmable read-only memory (EEPROM), flash memory, hard disk, or solid-state memory.

[0163] exist Figure 3A In the first example of this technology shown, sensor 104 is configured to communicate with position tracking module 102, such that sensor 104 can provide information to position tracking module 102. For example, position tracking module 102 may be configured to send periodic information requests to one or more sensors, or alternatively, sensors may be configured to periodically generate information without requiring requests from position tracking module 102.

[0164] After receiving information from a sensor, the position tracking module can process that information to extract one or more positional information points from the sensor. For example, the positional information may include one or more positions and / or rotations in three-dimensional space. This positional information can then be provided to a processor, which is configured to perform actions based on the positional information, such as updating the corresponding positional information of a virtual object (e.g., a skeleton or digital twin).

[0165] In some examples, processor 108 may be configured to communicate with sensor 104 and / or position tracking module 102, and vice versa. For example, the processor may request position information from position tracking module 102 as needed, or the position information may be provided periodically. In other examples, processor 108 may be configured to communicate directly with the sensor. For example, enabling or disabling the sensor, or changing one or more operating parameters of the sensor, such as the sampling rate.

[0166] Another example of this technology is... Figure 3B As shown in the figure. In this example, the processor 106 in the form of a computer can be configured to connect to any one or more of the following: sensor 104 (e.g., a camera), display 302 (e.g., a computer monitor or VR headset 118), peripheral input device 304 (e.g., a handheld controller 120), and smart wearable device 306.

[0167] For example, processor 106 can be configured to render a virtual environment and present it to user 108. When cameras 112 are included, these cameras can be configured to capture a series of images, which can be processed by position tracking module 102 to determine the position and / or rotation of the user or key user features (e.g., hands, arms, feet, etc.). For example, position tracking module 102 can be provided by a camera, i.e., the camera can be configured to take photos and / or videos and process these photos and / or videos to extract the position and / or rotation of the user or key user features 108. Alternatively, images and / or videos can be provided to processor 106, and processor 106 can include position and tracking module 102 configured to extract position and / or rotation information from images / videos.

[0168] Therefore, when a user moves in the real world, the location tracking module 102 can track the user's position and / or orientation in the real world and trigger movement or actions in the virtual environment based on the user's movement in the real world, which can be displayed to the user via the display 302. For example, a character or avatar in the virtual environment can move in a manner corresponding to a person in the real world, such as 1:1 movement or any other suitable movement, including faster movement (i.e., greater than 1:1) or slower, more precise movement (e.g., less than 1:1).

[0169] In some examples, processor 106 may not make any corresponding changes in the virtual environment until a specific movement, gesture, or series of movements or gestures is detected. For example, when presenting video to a user, the user's movement may have no effect unless a specific action, such as a "stop" or "pause" gesture, is presented, or for example, if the user walks out of the camera's field of view.

[0170] In this technical example using the smart wearable device 306, the camera can be configured to track the position of the smart wearable device 306 rather than specific characteristics of the user 108. For example, the smart wearable device 306 may include one or more markers (e.g., active or passive markers, such as reflective markers) configured to facilitate simple detection by the position tracking module 102. Examples of active and passive markers should be known to those familiar with motion capture techniques used in film and media.

[0171] In some examples of this technology, the smart wearable device 306 may include a sensor 104 configured to send information to the processor 106. For example, where the smart wearable device includes strain and / or stress sensors (such as the capacitive sensors described herein), it may be advantageous for the smart wearable device to include a position tracking module that, in use, converts sensor readings (i.e., capacitance values) into hand position information, such as finger positions relative to the user's hand. In other examples, the smart wearable device may be configured to transmit sensor readings directly to the processor 106, and the processor 106 may include a position tracking module configured to convert sensor readings into position information as described herein.

[0172] In some examples of this technology, the smart wearable device 306 may further include a sensor 104, such as an inertial motion sensor, configured to transmit hand position information in three-dimensional space. For example, an accelerometer, gyroscope, and / or magnetometer may be used to track the position and / or relative movement of the user's hand in space.

[0173] In some examples of this technology, it may be beneficial to combine location information provided by the smart wearable device 306 with location information from one or more cameras (e.g., wall-mounted or head-mounted cameras). For example, one or more cameras can be used to determine the position of a user's hand in the environment, while one or more sensors installed within the smart wearable device can be configured to transmit information related to the position of the user's fingers. By using multiple sources of location information, it becomes possible to track the user's location more accurately within the environment.

[0174] Although Figure 3BThe example illustrates one example of a system providing a central processing unit 106, but this should not be considered a limitation of the art. For example, system 100 may be configured to operate as a mesh network, and any or more of the components described herein may be configured to communicate with any other component of the system. For example, one or more cameras 112 may be configured to communicate directly with head-mounted device 118 (e.g., head-mounted device 118) to share information among them. For example, in some examples of the art, the head-mounted device may include an inertial sensor 104 that provides information about the user's head movement, which may be combined with image or video information from one or more cameras to obtain an accurate model of the user's head position in the environment. Thus, in this example, head-mounted device 118 may include a position tracking module 102 configured to provide position information to processor 106, wherein head-mounted device 118 transmits position information from one or more sources (which may include smart wearable devices) to the processor.

[0175] Figure 3C Another example of the present technology is shown, in which the processor is located within the head-mounted device 118. In other words, there may be no external processor 106. In this example, the head-mounted device 118 is configured to generate a virtual environment and present it to the user. The head-mounted device 118 may also communicate with one or more peripheral devices, such as handheld controllers, smart wearable devices, and cameras, to allow the user to interact with the environment. In some examples, the head-mounted device 302 may include a camera 112, and in some examples, an external camera 112 may not be present.

[0176] It should also be understood that while not all components of the system are shown in these examples, common electronic components may be provided, such as a power supply configured to power one or more electronic devices. For example, the power supply may be a DC power supply, such as a battery, or an AC power supply, such as AC power supplied from the power grid or a transformer. Furthermore, examples of this technology may include one or more regulators configured to regulate the voltage and / or current supplied to one or more components described herein.

[0177] For example, Figure 3F An exemplary connection diagram of a smart wearable device according to the present technology is shown. As illustrated, the device may include connectors for power and / or data. For example, the connectors may allow charging of the internal battery between uses, data transfer during use, diagnostic connectivity, and / or interfaces that allow updates to firmware or software on the device.

[0178] The device includes an internal battery with optional power regulation circuitry. For example, the power regulation circuitry may include one or more linear or switching regulators configured to maintain a regulated voltage output.

[0179] In some examples of this technology, the device may include:

[0180] User input and output (I / O), such as buttons for controlling the device (turning the device on / off, pairing Bluetooth, changing the operating mode, etc.).

[0181] Wireless connectivity, such as WiFi or Bluetooth, allows for the transmission of information during use, such as hand / finger capacitance or location values.

[0182] One or more sensors 104 as described herein, such as capacitive sensors, and one or more sensor ICs to facilitate the measurement of capacitance from the capacitive sensors.

[0183] Non-volatile memory, such as storing firmware or software configured to control the operation of a smart wearable device in use.

[0184] Massive storage devices, such as those storing configuration settings, usage information, user-defined conditions, or any other suitable information that may be useful to the software or firmware during use.

[0185] 5.3.1 Position Tracking Module

[0186] In one example of this technology, the position tracking module 102 can be configured to use any commercially available motion tracking or matching motion solution. For example, when using a camera, the position and / or rotation of one or more objects within the camera's field of view can be determined using any computer vision techniques known to those skilled in the art, including but not limited to machine learning-based semantic segmentation and object detection algorithms, motion capture of active and passive markers, and identification of markers of known size.

[0187] In this technical example using multiple cameras, the position tracking module 102 can use triangulation techniques to determine the position of objects within the field of view.

[0188] In this example of the technique, which includes an inertial motion sensor, the position tracking module 102 can be configured to track the movement of the sensor 104 using techniques known to those skilled in the art, such as detecting rotation relative to the Earth's magnetic field (in the case of a magnetometer), detecting changes in rotation using a gyroscope, and detecting acceleration using an accelerometer. In some examples, the position tracking module 102 can estimate velocity data from acceleration data provided by one or more inertial sensors by integrating the acceleration data over time. Similarly, position / displacement data can be estimated by doubly integrating the acceleration data.

[0189] In this technical example, stress and / or strain sensors (e.g., when using capacitive sensors as described herein) are included. The position tracking module 102 may include an electronic module that provides electronic excitation, such as an oscillating voltage, which allows measurement of the impedance of the individual sensors, and thus the capacitance.

[0190] For any given sensor within a smart wearable device, a series of capacitance values ​​can be defined corresponding to the sensor being in a loaded or unloaded state. For example, the minimum capacitance value could represent a fully extended finger, while the maximum capacitance value could represent a clenched fist, where the intermediate position between full extension and clenching can be mapped using any suitable equation.

[0191] In some examples of this technology, the location tracking module 102 may include one or more machine learning algorithms configured to map sensor 104 readings to location data, as described in more detail herein.

[0192] Further details of the capacitive sensing algorithm that can be used with this technology are described in more detail in U.S. Patent Publication No. 2020 / 0319236 A1, the entire contents of which are incorporated herein by reference.

[0193] 5.3.2 Sensors

[0194] This technology may include any number of sensors configured to provide position information as described herein. For example, sensors may include cameras, time-of-flight sensors, inertial measurement units, and stress and strain sensors, such as capacitive sensors.

[0195] In some examples of this technology, combining multiple sensors to provide detailed positional information can be advantageous. For instance, by combining visual information from one or more cameras with relative positional information from inertial measurement units and / or stress and strain sensors, accurate positioning information can be obtained, overcoming the individual limitations of these technologies when used alone. For example, inertial motion units and / or stress and strain sensors may be able to provide positional information when a user's body part is obscured from the camera's field of view. Similarly, when incorporated into a glove, stress and strain sensors, such as capacitive sensors, may be able to provide accurate and repeatable finger positional information relative to the user's palm, which may be difficult to obtain using conventional camera-based imaging techniques.

[0196] 5.3.2.1 Stress / Strain Sensors

[0197] Examples of this technology relate to stress and strain sensors using soft electronic components in the form of capacitive sensors. Details of suitable capacitive sensors and methods of their manufacture are described in more detail in U.S. Patent Nos. 9,816,800, 10,228,231, 10,539,475, and PCT Publication No. WO2019172781A1, the entire contents of which are incorporated herein by reference.

[0198] Generally, the capacitive sensor described herein is a laminated sensor device comprising two or more conductive layers, referred to herein as electrode layers 1a, 1c. These electrode layers are preferably made of or additionally comprise an elastomeric material, as shown in Figure 4. The electrode layers have a dispersion of conductive particles, making the electrode layers compliant and conductive. Electrodes 1a, 1c are separated by one or more electrically insulating layers (referred to herein as dielectric layer 1b). In examples of this technology, these layers may also be made of compliant or elastomeric materials. This laminated multilayer structure 403 serves as a capacitor, whereby the capacitance of the capacitor varies with the deformation of the membrane. This capacitance change can be detected using any capacitance measurement technique familiar to those skilled in the art, such as resonance or impedance measurement.

[0199] In some examples of this technology, the capacitive sensor is formed by providing a first membrane 1b on a non-compliant substrate 2a, bonding the first membrane 1b to a second membrane 1a, while the first membrane 1b is releasably bonded to the substrate 2a, for example to mitigate strain occurring in the first membrane 1b during bonding. For example, the first membrane can be releasably bonded to the substrate 2a using a first sacrificial layer (e.g., an adhesive soluble in the presence of a solvent or water). In some examples described herein, the sacrificial layer can be a backing layer, such as a membrane or sheet with an adhesive liner.

[0200] Subsequent layers can be formed in a similar manner, for example, using a second and third substrate and a sacrificial layer 3c. The flexible compliant electrodes 1b, 1c and the dielectric layer 1a can be bonded together using any technique known in the art, such as roll forming using one or more rollers 405, compression forming (e.g., using a press (not shown)) and / or using adhesive 401.

[0201] In a finished capacitive sensor, each membrane is preferably a different membrane, and the movement of each membrane from the supporting substrate can press the corresponding membrane layers together.

[0202] Generally, when incorporated into smart wearable devices such as gloves, capacitive sensors can detect the movement of a user's fingers and wrist. For example, when the hand's posture changes / joints move, stretch is applied to the sensor's sensing area. This causes a change in the sensor's electrical properties, which can include the capacitance and resistance of the electrodes, each of which can be affected by stimuli such as deformation caused by stretching or compression.

[0203] In terms of capacitance measurement, the capacitance of a sensor is proportional to the area of ​​the sensing region divided by the thickness of the sensor. Therefore, when the thickness of the sensor changes (e.g., due to stretching or compression of the dielectric layer), or when the area of ​​the electrodes changes due to stretching, these changes can be detected as changes in capacitance. The position tracking module 102 described herein can map these capacitance changes to the amount of stretch applied to the sensor, and thus, when incorporated into a wearable device, map how the stretch relates to the movement of the user's muscles and joints.

[0204] In normal operation, the sensor functions as an incompressible material. Therefore, stretching the sensor results in an increase in its area and a decrease in its thickness, both of which contribute to an increase in the sensor's capacitance. This particular type of sensor is highly insensitive to other stimuli such as temperature, time, speed, and humidity. Furthermore, the capacitance is proportional to the relative permittivity of the sensor's dielectric material, which is silicone and typically has a value of around 2.5, and is not strongly dependent on any of the aforementioned stimuli. Therefore, changes in capacitance are an excellent proximity indicator of changes in sensor shape, making them excellent deformable sensors.

[0205] Another advantage of capacitive sensors is their high repeatability; that is, if you do the same thing to the sensor, you will get the same result. Against the backdrop of a glove, moving the joint in the same way each time will generate essentially the same sensor signal.

[0206] This effect can be further enhanced by placing multiple sensors around the hand. Having multiple sensors to measure multiple degrees of freedom creates a richer description of a particular pose, making it easier to resolve more hand poses. Each sensor acts as a coordinate in a multidimensional system. These physical hand poses generate a multidimensional coordinate array that includes the values ​​from each sensor.

[0207] For example, flexible and compliant circuits incorporating soft capacitors or other flexible and compliant sensing devices are excellent sensors for soft structures such as the human body. Flexible, compliant, and lightweight sensing devices minimize any impact on the structure being measured, allowing it to more accurately represent its natural strain or deformation response. As is typical of soft structures, the human body is capable of large, complex movements in 3D space. Digitizing large-amplitude movements, such as human motion, has wide applications in sports, health and fitness, physical therapy, medicine, human-machine interfaces, and entertainment industries, particularly in wearable motion capture systems.

[0208] Flexible and compliant sensors can be incorporated into wearable clothing, such as gloves, to acquire data related to user movement. Gloves with such sensors can be used to obtain data related to the movement and position of the user's hand, particularly the fingers. Furthermore, they are capable of withstanding large stretches and have low stiffness so as not to significantly restrict the range of motion of the hand.

[0209] 5.3.3 Processor

[0210] Throughout this specification, the reference to a processor is used in a broad sense and refers to any device or system capable of executing machine instructions. For example, it can include application-specific integrated circuits (ASICs), computer processors (such as x86 or x64 processors), and / or microcontrollers.

[0211] For example, the processor 106 can be included in an extended reality headset or in a personal computing device, such as a smartphone, tablet, desktop or laptop computer.

[0212] In some examples, the processor is configured to execute computer-readable instructions. These computer-readable instructions include steps such as receiving sensor data from multiple sensors, and either A) transmitting the sensor data to an external processor, or B) processing the sensor data to determine hand position data indicating a gesture.

[0213] In some examples, the processor can be configured to execute code stored in memory (such as RAM, flash memory, or ROM). In some implementations, the memory can also be removable or external memory, such as memory connected to an SD card, server, USB flash drive, or optical disc. In other implementations, the memory can include a combination of external and internal memory. The memory can include stored data and processor control instructions (code) adapted to configure the processor to perform certain tasks, such as reading sensor values, converting sensor values ​​to finger / hand positions, detecting gestures or postures, and / or transmitting information to an external processor.

[0214] The processing power of a processor can be provided, for example, through one or more general-purpose processors, one or more dedicated processors, or through cloud computing services that provide access to a pool of shared computing resources configured according to desired characteristics, service models, and deployment models.

[0215] Although the processors and memories described herein are described in the context of a single unit, it should be understood that this is not intended to be limiting, and the functions of each described herein may be performed by multiple processors and memories that may or may not be remote to each other and to the rest of the system.

[0216] 5.3.3.1 Machine Learning

[0217] Some aspects of this technology can utilize machine learning techniques to ensure an accurate mapping of sensor values ​​to hand position.

[0218] In one example of this technique, the machine learning model is trained in the following way:

[0219] A) Equip hands with smart wearable devices in the form of gloves;

[0220] B) Manipulate the hand into the predetermined position; and

[0221] C) Obtain the capacitance value from the wearable device.

[0222] The above steps can be repeated for a range of different hand positions, a range of different users, and glove sizes and configurations. Therefore, a database of capacitance values ​​can be obtained, which can be mapped to various hand positions.

[0223] In some examples of this technology, the hand can be an electromechanical hand, where the angles and positions of the individual fingers can be acquired digitally. In other examples of this technology, the hand can be a user's hand, and the user can be instructed to manipulate their hand into a predetermined position.

[0224] In other examples of this technology, the hand can be positioned within the viewport of one or more cameras configured to monitor the position and orientation of the user's fingers. Thus, in this example, the user can move their hand within a range of motion, and the cameras record the corresponding finger and hand positions, mapping them to corresponding capacitance values ​​provided by a smart wearable device. In this way, one or more models can be trained for each user's hand size.

[0225] Using these machine learning techniques, a machine learning algorithm can be trained to create boundaries in a multidimensional system fed by sensors and to use mathematical operations to output which of the training poses the wearer's hand most closely resembles. In this example, there is no gap space between the training poses, so the output is guaranteed to be one of the training poses. This is particularly useful when there are only a specific number of desired outputs, and any other poses are irrelevant / unnecessary. This mechanism can be used, for example, as a filter.

[0226] This allows the system to interpolate between the boundaries of the range of motion captured during training. For example, by training the system with two static poses (flat hand and fist), the system can reliably predict the intermediate phase of finger flexion by acquiring instantaneous raw sensor values ​​and calculating a weighted average of the individual reference poses. Alternatively, a regression algorithm can be used to define a line of best fit to the data, representing the relationship between the raw sensor values ​​and the position within the range of motion.

[0227] This can be further enhanced by breaking down the raw sensor data into subsets and, for example, focusing on individual fingers, making the training data available for predicting the position of each degree of freedom independently of the others. In glove applications, this allows for the independent prediction of fingers, e.g., the index finger may be partially curled while the other fingers are extended.

[0228] In addition to selecting the closest output pose, a confidence score can be obtained, which provides an indication of how close the wearer's hand is to the closest known pose. This can be mathematically derived, for example, by comparing instantaneous raw sensor values ​​with sensor values ​​captured during training. That is, where the average sensor value corresponds to a first pose more strongly than to a second pose, the system may be able to provide a confidence score indicating the percentage difference between the expected pose value and the observed pose value. It should be understood that these confidence scores can generally be provided for the gesture as a whole, or for any one or more sensors within the smart wearable device, such as each finger, or each degree of freedom monitored by the sensors described herein.

[0229] Therefore, an additional fidelity layer can be added, in which, for example, a default state can be output if the confidence score of the most likely pose is not higher than a user-defined threshold.

[0230] The inventors have discovered that, crucial for pose reproduction, it is essential to train the machine learning model using consistent training data. That is, when physical joints are in the same position between two different poses, they must also be in the same position in the reference data.

[0231] Whether using gloves and algorithms to detect the closest applicable pose (which may or may not need to meet a certain threshold / be within the desired proximity of the pose), or whether a weighted average or regression model of all training information is required, the process is highly flexible. A specific array of sensor data obtained by the wearer posing their hand in the desired pose can be correlated with a specific output. Users can arbitrarily define the desired state they want the system to enter after recognizing the pose, and use the state itself or state changes to trigger specific actions or events.

[0232] Therefore, machine learning algorithms can be trained to recognize one or more specific hand gestures, including but not limited to: clenched fist, open hand with all fingers touching, open hand with all fingers apart, clenched fist with any combination of fingers extended, and any combination of gestures between them.

[0233] In some examples of this technology, including one or more wrist-worn sensors may be advantageous, said sensors being configured to detect the position or orientation of the wrist during use. For example, an accelerometer mounted to the wrist may be able to detect the downward direction (i.e., the down direction, or the direction facing the ground), due to acceleration under the influence of gravity. Thus, orientation relative to the downward direction can be determined by the axis of the accelerometer receiving a value indicating gravity.

[0234] In other examples of this technology, one or more wrist-worn sensors may include capacitive sensors configured to detect twisting or bending of the wrist, thereby changing the position of the user's hand relative to the user's forearm or elbow.

[0235] Simultaneously acquiring snapshots of each sensor value defines the position within the multidimensional system, which incorporates at least the individual sensor values ​​as coordinates within the system. These coordinates can be correlated with any reference output selected by the user. They can be correlated with the matched pose of the virtual hand to create a real-time digital representation of the user's hand, for example, using the machine learning model described herein, or alternatively, correlated with an event name or similar definition that can be used to trigger further actions.

[0236] When hand pose is related to a digital twin of the hand, all reference data can be used to train machine learning algorithms.

[0237] 5.3.3.2 Digital Hand Modeling

[0238] One method for visualizing detected user hand movements in real time is to generate a digital copy of the user's hand (often called a digital twin). This digital hand can be presented to the user, allowing them to see changes in hand orientation and / or position in real time or near real time.

[0239] Therefore, for any given capacitance value or combination of capacitance values, the possible positions of individual fingers within the virtual model can be determined, for example by using the defined minimum and maximum capacitance values ​​described herein, or alternatively by the aforementioned machine learning model.

[0240] 5.3.4 Smart Wearable Devices

[0241] The first example of wearable device 306 is in Figure 3D and Figure 3E As shown in the illustration, in this example, wearable device 306 is provided as a glove. The use of a glove should not be considered a limitation of this technology and is described herein as one of the most complex shapes to track on the human body due to the large number of joints and the high degree of freedom of each joint. In other examples, this technology can be used to track the movement of a user's feet and ankles, for example, by integration into socks. In another example, this technology can be used to track the body, for example, by incorporating it into a shirt or similar garment. Similarly, this technology can be used in non-human applications, such as monitoring and / or obtaining digital motion captures of animals (e.g., dogs, cats, or horses).

[0242] Gloves are generally familiar to the public, but for completeness, a glove includes a body 302 configured to receive a user's hand in use. In some examples of this technology, the body of the glove may include individual finger compartments 322 configured to receive the user's individual fingers. In some examples, these finger compartments 322 may be open to provide a "fingerless glove," as will be familiar to those skilled in the art.

[0243] In use, multiple sensors 104 can be attached to the glove, such that deformation of the glove causes detectable changes in the sensors 104. For example, a capacitive sensor, as described herein, can be used, which allows strain to be measured at a location within the glove corresponding to the user's hand position.

[0244] In a preferred embodiment of this technology, multiple sensors can be positioned at locations corresponding to one or more joints and / or degrees of freedom for each of the user's fingers and wrist. For example, for each finger, a first sensor 104A can be positioned near the metacarpophalangeal joint, a second sensor 104B can be positioned near the proximal interphalangeal joint, and a third sensor 104C can be positioned near the distal interphalangeal joint. In this way, changing the user's hand from a flat, extended position to a closed, clenched fist position may cause the sensors to stretch, resulting in deformation that can be measured by the position tracking module 102 described herein. For example, each of the first, second, and third sensors described above can be mounted on the back of a glove such that they are close to the user's corresponding joint on the back of the hand.

[0245] In this technical example, which includes fingerless gloves, the third sensor 104C can be omitted, and data from the first sensor 104A and the second sensor 104B can be used to estimate the angle of the distal interphalangeal joint, since for most users, the angle of this joint directly corresponds to the angle of the proximal interphalangeal joint.

[0246] For the user's thumb, it should be understood that there is only a single interphalangeal joint, and therefore for the purposes of this discussion, this has been designated as the second sensor 104B, although it may be omitted in this technical example using fingerless gloves.

[0247] In some examples of this technology, such as when it may be desirable to detect the opening or spreading of one or more fingers, it may be advantageous to position one or more sensors (referred to herein as the fourth sensor 104D) on or near the metacarpophalangeal joint (knuckle). In this way, when a finger moves laterally relative to the user's palm within the plane of the user's hand, the movement can be detected as compression or extension of the corresponding fourth sensor 104D.

[0248] In other examples of this technology, the glove may include one or more sensors 104 (referred to herein as fifth sensor 104E) positioned on or near the user's wrist joint, such as above the radiocarpal joint (i.e., on the back of the user's wrist), on the inside of the user's wrist, and / or on the side of the radiocarpal joint, such as the radial or ulnar regions near the sides of the wrist.

[0249] In use, the various sensors 104 in the wearable device 306 are operatively connected to the position tracking module 102. For example, the position tracking module may be configured to perform measurements on the sensors to obtain one or more parameters of the sensors, such as the capacitance of sensor 102. In some examples of this art, the position tracking module 102 may further convert this capacitance information into position information in the form of joint angle or finger position information; however, this should not be considered a limitation, and in other examples, the processor 106 may be configured to determine the position information.

[0250] In some examples of this technology, wearable device 306 may include, for example: Figure 3G The illustrated electronic housing 310 is configured to house one or more of the following: a position tracking module 102, a power supply 312, and a communication module 314, such as a wireless communication module or Bluetooth. TM Module.

[0251] For example, the electronic device housing 310 may be a substantially rigid plastic housing with a waterproof seal to prevent water ingress that could otherwise damage the components contained therein. The position tracking module 102 may be configured to communicate with one or more sensors, for example using electrical interconnects 316, such as conductive traces on a flexible printed circuit, or using wires. Methods for connecting capacitive sensors to sensing electronics are described in more detail in PCT Publication No. WO 2019 / 022619, the entire contents of which are incorporated herein by reference.

[0252] In some examples, the glove body 320 may be formed of a single-layer or multi-layer material structure. For example, the material may include any one or more of the following: fabrics, such as cotton, polyester, linen; animal hides, such as raw hides and leather (including synthetic leather); polymers, such as nitrile rubber, latex, polyurethane; and fibrous materials, such as Kevlar.

[0253] In examples of this technology, where the body 320 is composed of a single layer of material, the sensor 104 can preferably be mounted on the non-user contact side of the glove, adjacent to the back or back of the user's hand. In other examples, the sensor 104 can be mounted on the patient contact side of the glove, and / or adjacent to the inside / palm of the user's hand.

[0254] In some examples of this technology, the body of the glove may consist of multiple material layers, such as a user contact layer configured to engage with the user's skin, and a non-user contact layer facing outwards away from the user's skin.

[0255] In some examples, the non-user contact layer may have gripping features in one or more areas of the glove, such as in the palm of the user's hand and / or on the inside of the fingers. The use of gripping features can advantageously help the user grasp objects when using the smart wearable device described herein.

[0256] In some examples, the non-user-contact layer may be provided with one or more active or passive markers configured to be detected by the camera during use. For example, active or passive markers may be placed on the hand area adjacent to the user's wrist, the back of the user's hand, and / or the side of the user's wrist. The use of active or passive markers can advantageously reduce the processing burden of camera tracking systems as described herein.

[0257] In some examples of this technology, sensor 104 may be positioned between the user contact layer and the non-user contact layer. For example, the sensor may be mounted to the non-user contact side of the non-user contact layer using any technique known to those skilled in the art, including thermoforming, welding, stitching, and the use of adhesives.

[0258] 5.3.5 Other devices

[0259] While the foregoing discussion has primarily focused on smart devices (i.e., gloves) configured to detect user hand movements, this should not be considered a limitation of the technology. For example, as described herein, the technology can be applied to any clothing, such as socks, shirts, shoes, headbands, wristbands, knee pads, shoulder pads, and wrist guards.

[0260] The use of the term "user" in this article should not be considered a limitation; for example, in some cases, the user may be an animal or a robot, rather than a more conventional human application.

[0261] Therefore, in a general sense, the smart wearable device 306 described herein includes a body comprising a user contact side configured to contact a user in use. In examples, the body includes one or more sensors configured to detect user movement via deformation of one or more sensors. In some examples of this art, the smart wearable device 306 includes a position tracking module 102 configured to receive information from one or more sensors, and optionally includes a processor configured to trigger one or more actions based on movement detected by the smart wearable device.

[0262] 5.4 Exemplary Device

[0263] 5.4.1 Unmanned Aerial Vehicle (UAV) Control System

[0264] One advantage of this technology is that the control systems and devices described herein can be used to control any software, electronic, or electromechanical hardware. For example, one application of this technology is to provide a drone control system that includes a smart wearable device as described herein. For instance, parameters such as the drone's altitude, position, pitch, yaw, roll, speed, elevation, and the operation of any connected devices (e.g., cameras) can be controlled using the user's hand position through subtle finger and hand movements, or by performing predefined gestures and postures.

[0265] 5.4.2 Surgical Control System

[0266] Another application of this technology is in precision surgery. For example, smart wearable devices can be used to control remote robotic arms used to perform surgery on humans or animals.

[0267] One advantage of this system is that it allows certain movements of the user's hand to be ignored during use. For example, the system can be configured with a condition, such as requiring the surgeon performing surgery to perform a grasping gesture (index finger and thumb contact) when controlling the remote robot, so that the remote robot can, for example, mimic the surgeon's movements with a scalpel. Once the surgeon wishes to stop controlling the robot, they can separate their index finger and thumb and be highly confident that the robot will not move.

[0268] Furthermore, as described in this article, movements performed using gloves can result in controlling avatars or robots with non-1:1 movement mappings. For example, for every centimeter a surgeon moves, the corresponding robot can be configured to move one millimeter.

[0269] One aspect of this technology is to provide a smart wearable device including multiple sensors configured to provide position information to a processor 106. For example, the smart wearable device may include at least one capacitive stress or strain sensor for each joint in the user's hand; in another example, the smart wearable device may include at least one capacitive stress or strain sensor for each degree of freedom in the user's hand.

[0270] In some examples, a smart wearable device may include a location tracking module 102 configured to extract location information from multiple sensors 104.

[0271] 5.4.3 General Input Devices

[0272] In another example of this technology, the smart wearable device can be configured to function as a general peripheral device in a manner similar to a keyboard or mouse. Therefore, in one example of this technology, the smart wearable device may include: one or more sensors configured to sense stress or strain characteristics in the smart wearable device; a position tracking module 102 configured to convert the stress or strain characteristics into position and / or rotation information relating to at least one finger in the user's hand; and a processor 106 configured to detect when a gesture has been executed.

[0273] For example, smart wearable devices can be equipped with wireless connectivity, such as Bluetooth, which allows them to connect to the device during use. The use of wireless connectivity should not be considered a limitation of this technology, and in other examples, wired connections, such as USB connections, can be used.

[0274] In some examples of this technology, when connected to a computing device (such as a personal phone, tablet, or computer), a smart wearable device can be configured to identify itself as a human-machine interface device, such as a keyboard and / or mouse. Therefore, this technology can provide keyboard and mouse input to a system without requiring the installation of custom drivers or software on said system.

[0275] In use, the position and rotation information provided by the glove can be used to trigger actions on the connected computing device. For example, when controlling a presentation, a simple swipe right can be used to move to the next slide, while a simple swipe left can be used to switch to the previous slide. Similarly, gestures familiar to those accustomed to touchscreen interfaces, such as pinch-to-zoom, can be virtually implemented on the computing device by making corresponding gestures or postures.

[0276] 5.4.4 Sign Language Interpretation

[0277] In another example of this technology, the smart wearable device can be configured to detect one or more gestures or postures corresponding to sign language, and upon detection of appropriate sign language, the smart wearable device can be configured to send a series of key press responses corresponding to the words and phrases expressed using sign language. It should be understood that not all sign language systems involve only gestures, and in some examples of this technology, combining sensor information from the smart wearable device with camera information (e.g., extracting facial expressions from the user using any computer vision techniques known to those skilled in the art) may be advantageous.

[0278] For example, a condition can be added to the system that a series of hand movements will not generate a predetermined sequence of words as output unless the corresponding facial expression condition is also met.

[0279] 5.4.5 Smart Wearable System

[0280] One aspect of this technology is to provide a tracking system comprising a smart wearable device including multiple sensors configured to provide data indicating stress or strain measured within the wearable device, and a position tracking module 102 configured to extract position information from the stress or strain. In some examples, the position tracking module 102 may be configured to provide the position information to a processor to trigger an action.

[0281] 5.5 Sensor Construction

[0282] Various aspects of this technology relate to flexible, compliant sensors, such as capacitive sensor 104. To manufacture these sensors, at least two electrodes separated by a dielectric layer are required. Figure 4B An example of this technology is shown, in which two electrode stacks 402 are connected to each other.

[0283] In the illustrated examples, each electrode stack 402A, 402B includes an electrode 404, a dielectric layer 406, and a sacrificial layer 408, such as a backing paper or film. It should be understood that a single dielectric layer can be used; for example, the first electrode stack 402A or the second electrode stack 402B may not include a dielectric layer 406 in some examples. Similarly, although the sacrificial layer 408 is... Figure 4B These layers are shown, but are not essential to the present invention and are used in some forms of the art to aid in the assembly of the capacitive sensor 104. These sacrificial layers 408 are typically removed during manufacturing to provide the capacitive sensor 104. Further details of the sacrificial layers can be found in U.S. Patent No. 9,816,800, the entire contents of which are incorporated herein by reference.

[0284] The first electrode stack 402A can be bonded to the second electrode stack 402B using any method familiar to those skilled in the art, including the use of pressure, heat and / or adhesives.

[0285] In some examples of this technology, the dielectric layer 406 may be formed of an elastomeric material (e.g., silicone). When using silicone, the dielectric layer may be provided as uncured or, more preferably, partially cured silicone (e.g., silicone gel). Using uncured or, more preferably, partially cured silicone offers numerous advantages, including a softer construction capable of deforming under compressive forces, and the ability to bond with one or more adjacent layers of the sensor during the curing process as described herein. A primary benefit of using partially cured silicone as the dielectric layer is that it retains its shape between small deformable / molded dielectric layers and cured dielectric layers.

[0286] Electrode 404 can be formed of any suitable conductive material, and in a preferred example, carbon is used as conductive particles. In some examples of this technology, electrode 404 can be configured to be bonded to dielectric layer 406 to provide flexible electrode 404. For example, the dielectric layer may comprise an uncured or more preferably partially cured silicone material to which the electrode can be bonded during the manufacturing process. For example, electrode 404 may comprise a carbon-doped silicone layer that can be bonded to the silicone dielectric layer. Preferably, electrode 404 comprises a carbon-doped silicone layer that can be cured and cut into a desired shape before contact with the dielectric layer. This configuration can further allow the electrode to be at least partially recessed within the surface of the dielectric layer or support layer during use.

[0287] In other examples of this technology, electrode 404 may not be configured to be chemically bonded to dielectric layer 406. For example, electrode 404 may be composed of a thin, flexible and / or compliant layer configured to deform under stress or strain of the capacitive sensor.

[0288] The use of these materials should not be considered a limitation on the scope of this technology. For example, other conductive electrode 404 materials, such as copper, aluminum, silver, gold, or platinum, can be used. Similarly, the use of silicone as the dielectric layer 406 material should not be considered a limitation, and other materials, including thermoplastic elastomers, styrene block copolymers, polyolefin elastomers, vulcanized rubber, polyurethane, polyamide, and copolyester materials, can be used.

[0289] Now refer to Figure 4C It shows a side view of a capacitive sensor 104 according to an example of the present technology, in which the sensor includes:

[0290] Support layer 410;

[0291] First electrode layer 404A;

[0292] First dielectric layer 406A;

[0293] Second electrode layer 404B;

[0294] Second dielectric layer 406B;

[0295] The third electrode layer is 404C; and

[0296] Top floor 412.

[0297] In the example shown, the first electrode layer 404A and the third electrode layer 404C are essentially planar conductive structures, which in some applications can shield the second electrode layer 404B from electromagnetic noise radiated from external sources during use. For example, as... Figure 4D As shown, the first electrode layer 404A and the third electrode layer 404C can be configured to extend outward beyond the second electrode layer 404B such that each of the first electrode layer 404A and the third electrode layer 404C extends beyond the outer edge of the second electrode layer 404B by at least the thickness "T" of the dielectric material disposed therebetween.

[0298] In other words, the boundaries of the first electrode layer 404A and the third electrode layer 404C can extend beyond the boundary of the second electrode layer 404B by a distance "W", which is greater than or equal to the thickness "T". In this way, the outermost edge of the first electrode layer 404A extends beyond the outer edge of the second electrode layer 404B by at least the thickness "T" of the first dielectric layer 406A, and similarly, the third electrode layer 404C extends beyond the outer edge of the second electrode layer 404B by at least the thickness of the second dielectric layer 406B.

[0299] In use, the support layer 410 and the top layer 412 encapsulate the sensor and provide protection for the first electrode layer 404A and the third electrode layer 404C. These layers can be formed of any suitable material, as those skilled in the art will understand. In some examples, the support layer 410 and the top layer 412 can be formed of a flexible elastomeric material (e.g., silicone), for example, they can be formed of the same elastomeric material as the dielectric described herein.

[0300] exist Figure 4E In another example of this technology shown, the capacitive sensor 104 is provided with:

[0301] Support layer 410;

[0302] First electrode layer 404A;

[0303] First dielectric layer 406A;

[0304] Second electrode layer 404B; and

[0305] Top floor 412.

[0306] Therefore, in this example of the present technology, capacitance can be measured between the first electrode layer 404A and the second electrode layer 404B. Providing a capacitive sensor 104 with a reduced number of layers (e.g., by omitting the third electrode layer 404C) can advantageously increase the flexibility of the capacitive sensor 104 and / or reduce its manufacturing cost. Therefore, although the example described herein includes the third electrode layer 404C, this should not be considered as a limitation on the scope of the invention.

[0307] It should also be understood that in the example of this technology described and illustrated in the accompanying drawings, the second electrode layer 404B has been shown as having a plurality of electrode segments 414. Therefore, a plurality of capacitive elements may be provided between the first electrode layer and the second electrode layer; however, this should not be considered a limitation on the scope of the technology, and the technology described herein can be used for any number of electrode segments 414 per layer.

[0308] 5.5.1 Connecting the Sensor Layer

[0309] In use, it is desirable to link each of one or more layers together to provide a capacitive sensor 104. This can be achieved using a combination of pressure and / or heat. For example, a compressive force can be applied between the support layer 410 and the top layer 412 to force each layer of the stack to engage with each other.

[0310] In some examples, the application of compressive force and / or heat may be sufficient to bond each of one or more layers 410, 404A, 404B, 404C, 406A, 406B, 412 together. For example, the combined application of compressive force and / or heat can cause adjacent layers within a sensor to bond together.

[0311] In examples where the dielectric layer and / or support layer 410 and top layer 412 comprise uncured silicone, the application of compressive force and / or heat can cure the silicone, resulting in bonding between any adjacent layers. In some examples, the bonding between electrode layers 404A, 404B, 404C and dielectric layers 406A, 406B or outer layers 410, 412 can result in the formation of conductive doped silicone regions within the respective layers.

[0312] In other examples of this technology, the adhesive may be applied between any of the one or more layers prior to compression. However, a major advantage of using uncured or more preferably partially cured materials for dielectric layers 410, 406, 412 is that no additional adhesive is required.

[0313] In some examples of this technology, for example Figure 4A As shown, one or more rollers 402 can be used to apply the compressive force; however, this should not be considered a limitation of the technique, and other means of providing the compressive force can be used, including the use of a press or a vacuum.

[0314] By applying compressive force directly to a stack comprising one or more layers of 410, 404A, it is possible to efficiently form a capacitive sensor as described herein. However, using a single compression / heating process may have some drawbacks, including any or more of the following:

[0315] The relative thickness of layers in a capacitive sensor has limited controllability. For example, applying a known compressive force between the support layer 410 and the top layer 412 will cause the stack to be compressed to the desired total height. However, it may not be guaranteed that each layer experiences the same amount of deformation during the application of the compressive force. For instance, when the layers are manufactured at different times or using different processes, the stiffness of each layer may differ, and each layer may experience different amounts of deformation in response to the compressive force. This will affect the capacitance measured between the electrode layers 404A, 404B, and 404C of the sensor, and how the capacitance of sensor 104 changes in response to applied stress and strain. Furthermore, if the layers deform by different amounts, the layer with the greatest deformation may become too thin and fail, resulting in an electrical short circuit between 404A and 404B or between 404B and 404C. Even in the ideal case where the dielectric layers have the same properties, the thicker the overall stack, the more prone the stack is to barrelling. In other words, when the stack is compressed, the incompletely cured layer near the center of the stack will expand in area more than layers 410 and 412. This may result in uneven distribution of dielectric layer thickness in the finished stack, and subsequently lead to the aforementioned problems.

[0316] Surface defects. For example, regarding Figure 4F In areas of the support layer 410, top layer 412, and / or dielectric layers 406A, 406B that do not include electrodes 404A, 404B, 404C in their cross-sectional stack, the total thickness of the compressed sensor 104 may be smaller. This can result in indentations 416 in the support layer 410 and / or top layer 412. These indentations may be aesthetically unappealing and potentially affect how the capacitive sensor deforms under applied stress and strain. Furthermore, these locations may also cause bubbles / cavities trapped between the layers of the stack. This is particularly problematic if a heating stage is subsequently used to solidify the stack, as heat causes air to expand and introduce further defects within the stack.

[0317] Therefore, in an alternative form of the present technology, the capacitive sensor 104 can be formed by first forming one or more sensor layer pairs, thereby at least partially solving any or more of the aforementioned problems.

[0318] 5.5.1.1 Forming a sensor layer pair

[0319] Reference Figure 5A Another example of this technology relates to forming a sensor layer stack 502 comprising two or more layers. In the illustrated example, the sensor layer stack 502 is formed between the support layer 410 and the first electrode 404A; however, this should not be considered a limitation of the technology, and layer pairs can be formed between any adjacent layers in the layer stack.

[0320] In use, the compressed stacked body 502 is formed in the following manner:

[0321] Optionally, an adhesive may be applied to either the first or second layer. This is typically not necessary if one of the layers is uncured or partially cured when the sensor layer pair is formed.

[0322] This allows the first layer to join with the second layer. For example, the second layer can be placed on top of the first layer, below the second layer, or side by side with the first layer.

[0323] Apply compressive force to cause the first layer to align with the second layer.

[0324] Optionally, heat may be applied to the first and / or second layers.

[0325] For example, refer to Figure 5B Compressive force can be applied using a compression device in the form of a press 504, such as a hydraulic, pneumatic, or mechanical press. For example, the press may include two substantially parallel surfaces 506A, 506B or plates. In use, the layers to be joined can be positioned between these parallel surfaces 506A, 506B and compressive force applied.

[0326] In some examples of this technology, the force applied between parallel surfaces 506A, 506B can be user-configurable. For example, press 504 can be configured to apply a predetermined force between the first surface 506A and the second surface 506B to generate a pressure, for example, between about 50 and 1000 kPa (e.g., between 500 and 800 kPa, such as about 650 kPa).

[0327] In other examples of this technology, the press 504 may be configured to move the first surface 506A and the second surface 506B toward each other to a predetermined interval distance, such as between 0.04 and 2 mm, for example, about 0.25 mm.

[0328] In other examples of this technology, the press 504 can be configured to have a combination of a predetermined force and a predetermined interval distance. For example, the press 504 can be configured to push the first surface 506A and the second surface 506B toward each other to achieve a target interval, and stop if the predetermined force is exceeded. By combining force limiting and distance limiting, the safety of the press 504 can be improved, and / or potential differences in material properties can be detected.

[0329] exist Figure 5B In the example shown, the layer stack 502 includes a support layer 410, an electrode layer 404A, and a sacrificial layer 408. However, this should not be considered limiting. In some examples, sacrificial layers may be provided on both sides of the layer stack 502 before compression. In some examples, the sacrificial layer may be made of a durable, non-stick material, such as a polyester film like biaxially oriented polyethylene terephthalate (BoPet), which may be referred to as Mylar by those skilled in the art. TM Using durable, non-stick materials can help protect the layers from damage under compression and / or prevent the layers from adhering to the first surface 506A and the second surface 506B.

[0330] Once compressive force is applied, a compressed stacked body 506 is formed, such as Figure 5C As shown, electrode layer 404A is partially compressed within dielectric layer or support layer 410. In examples of this technology, the electrode layer can have greater dimensional stability than the dielectric layer or support layer when combined; for example, the electrode layer can have a stiffness at least 10 times greater than that of the dielectric layer or support layer, or the electrode layer can be a cured carbon-doped silicone layer, which can be used with an uncured or more preferably partially cured silicone dielectric layer. In this way, the application of compressive force may cause the dielectric layer or support layer to undergo relatively larger deformation than the electrode layer.

[0331] This method allows for better control over the thickness of the resulting stack because the predetermined interval (or alternatively, predetermined force) between the first and second surfaces of the press causes known deformation within the stack 506.

[0332] Since the first surface 506A and the second surface 506B of the press are substantially flat, the support layer or dielectric layer is forced to bond to both the first and second surfaces under compression, resulting in the top surface 512A and the bottom surface 512B of the stacked body being substantially flat and parallel.

[0333] This process can also advantageously produce compressed stacked bodies, wherein the recessed electrode layers provide a substantially flat planar surface 512A to which adjacent stacked bodies can be bonded.

[0334] This process can be repeated to form multiple compressed layer stacks, such as Figure 5D As shown. For example:

[0335] The first stack 506 may include a support layer 410 and a first electrode 404A;

[0336] The second stack 508 may include a first dielectric layer 406A and a second electrode layer 404B;

[0337] The third stack 510 may include a second dielectric layer 406B and a third electrode layer 404C.

[0338] Each of these compressed stacked layers 506, 508, 510 can be combined to form a capacitive sensor 104 as described herein, such as Figure 5E As shown. For example, the individual layer stacks can be pressed together using compressive force and / or heat pressing as described herein. Because the compressed layer stacks 506, 508, and 510 have already been compressed to their desired thickness, the pressure required to compress the stacks is reduced to a level sufficient to ensure good contact between 506, 508, and 510. Eliminating the need for a large overall height of the compressed stacks avoids the situation where uncured or partially cured material may flow and take on geometries significantly different from their desired shape. These flow effects are particularly noticeable at the edges of the layers and where fine millimeter-scale features exist in any layer.

[0339] In a preferred example of this technology using uncured or partially cured silicone, heat is preferably applied during at least one compression stage to cure the silicone and provide a durable, elastic layer stack and the resulting durable capacitive sensor 104.

[0340] 5.5.1.2 Exposed electrode layer

[0341] In some examples of this technology, it may be preferable that the electrode layer of the capacitive sensor is exposed for easy connection to a sensing electronics configured to measure capacitance, as described herein. Therefore, referring to FIG6, a capacitive sensor comprising:

[0342] First support layer 410.

[0343] The first electrode layer 404A is supported by the first support layer 410.

[0344] The first dielectric layer 406A is supported by the first support layer 410 and / or the first electrode layer 404A, while at least a portion of the first electrode layer remains uncovered within the capacitive sensor 104.

[0345] The second electrode layer 404B is supported by the first dielectric layer 406A.

[0346] The second dielectric layer 406B is supported by the first dielectric layer 406A and / or the second electrode layer 404B, while ensuring that at least a portion of the second electrode layer remains uncovered within the capacitive sensor.

[0347] The third electrode layer 404C is supported by the second dielectric layer 406B.

[0348] The top layer 412 is supported by the second dielectric layer 406B and / or the third electrode layer 406C, while at least a portion of the third electrode layer remains uncovered within the capacitive sensor.

[0349] In the example shown, the uncovered sections of the electrode layers are shown exposed on the same side of the capacitive sensor 104. However, any one or more of these electrode layers may be exposed on different sides or the same side of the capacitive sensor 104.

[0350] In order to form a capacitive sensor 104 having these exposed electrode layers, it is advantageous that any one or more compression steps described herein employ one or more positioning devices 602 to support the exposed ends of the capacitive sensor 104 during compression.

[0351] Therefore, in Figure 6B In one example of the present technology shown, the positioning device 602 can be disposed between the parallel surfaces 506A and 506B of the press 504. This positioning device 602 can advantageously:

[0352] The auxiliary mechanism positions and secures the stacked bodies within the press 504;

[0353] Control or otherwise limit the amount of lateral expansion (i.e., expansion in a direction substantially perpendicular to the direction of the applied compressive force) that the stacked body may experience during compression.

[0354] A maximum compression depth is set within the press 504. For example, the frame 604 of the positioning device 602 may be substantially rigid, or otherwise have high material stiffness, such that when the parallel surfaces 506A, 506B engage and attempt to compress the positioning device 602, a predetermined force limit may be exceeded, thereby preventing the application of further compressive force.

[0355] Includes a support platform 606, which is configured to support one or more sections of a layer stack in use. For example, in a layer stack including... Figure 6A In the case of the exposed sections shown, it may be advantageous to keep these exposed sections supported during compression, so that the compressive force can be properly guided to better control the shape and form of the capacitive sensor after completion.

[0356] Because each layer of the stack can have different physical dimensions (e.g. Figure 6A As shown), a series of positioning devices 602 of different sizes can be provided to accommodate different layer stacks as described herein.

[0357] 5.5.2 Other Examples

[0358] While the above examples of this technology have described the formation of layer stacks including a support layer or dielectric and electrodes, this combination should not be considered a limitation of this technology. For example, Figure 7A An example of the present technology is shown, in which a three-layer stack can be formed. For example, the three-layer pair may include at least one outer layer 410, 412 or dielectric layer 406, and at least one electrode 404.

[0359] In a manner similar to previous examples of this technology, these three-layer stacks can be coupled to any other layer stack, such as the two-layer stack described herein, to form a capacitive sensor. For example, Figure 7B An example of this technology is shown, in which two three-layer stacks are brought together on either side of the central electrode 404B to provide a capacitive sensor as described herein.

[0360] 5.6 Other Notes

[0361] Unless the context explicitly requires it, throughout the description and claims, the words “comprising,” “including,” etc., should be interpreted in an inclusive rather than exclusive or exhaustive sense; that is, meaning “including but not limited to.”

[0362] All disclosures of all applications, patents, and publications cited above and below (if any) are incorporated herein by reference.

[0363] Any reference to prior art in this specification is not, and should not be construed as, an acknowledgment or any form of implication that such prior art constitutes part of the common general knowledge of the art in any country in the world.

[0364] This technology can also be broadly described as consisting of the parts, elements and features pointed out or indicated in this application specification, individually or jointly, and any or all combinations of two or more of said parts, elements or features.

[0365] In the above description, if references have been made to integers or components that have known equivalents, these integers are incorporated herein by reference as if they were described separately.

[0366] It should be noted that various changes and modifications to the presently preferred embodiments described herein will be apparent to those skilled in the art. These changes and modifications can be made without departing from the spirit and scope of the present technology and without diminishing its accompanying advantages. Therefore, these changes and modifications are intended to be included within the scope of the present technology.

[0367] 6. Definition

[0368] Compliant, compliant materials—Compliant materials can be bent, stretched, and have elastic properties that allow them to return to near their initial size and shape after each bending or stretching action.

[0369] Compression—as used herein, the term is intended to be interpreted broadly as yielding under compressive force, and not limited to elements that change volume under pressure.

[0370] Compressible—as used in this article, the term is intended to be interpreted broadly as flattened by pressure.

[0371] Electronic components – as used herein, this term is intended to be interpreted broadly to include any electronic component, including circuit boards, sensors, generators, and actuators.

[0372] Electrodes and terminals—as used herein—are intended to refer broadly to the points where current enters or leaves electronic components or electrical devices.

Claims

1. A laminated elastomer sensing device, the laminated elastomer sensing device comprising: First electrical insulating layer; Second electrical insulation layer; Third electrical insulation layer; First conductive layer; Second conductive layer; Wherein, at least one of the electrically insulating layers is positioned between the first conductive layer and the second conductive layer to provide a dielectric layer, and Wherein, the first conductive layer is at least partially compressed into the first electrical insulating layer or the second electrical insulating layer, and wherein the second conductive layer is at least partially compressed into the second electrical insulating layer or the third electrical insulating layer.

2. A laminated elastomer sensing device, the laminated elastomer sensing device comprising: First electrical insulating outer layer and second electrical insulating outer layer; First conductive electrode layer, second conductive electrode layer and third conductive electrode layer; First electrically insulating dielectric layer and second electrically insulating dielectric layer; Wherein, the first electrically insulating dielectric layer is positioned between the first conductive electrode layer and the second conductive electrode layer, and the second electrically insulating dielectric layer is positioned between the second conductive electrode layer and the third conductive electrode layer; and in: The first conductive electrode layer is at least partially compressed into the first electrically insulating outer layer. The second conductive electrode layer is at least partially compressed into the first electrically insulating dielectric layer; and The third conductive electrode layer is at least partially compressed into the second dielectric insulating layer.

3. The laminated elastomer sensing device according to claim 1 or 2, wherein, The electrical insulating layer is formed of an elastomeric material or silicone.

4. The laminated elastomer sensing device according to claim 1, 2 or 3, wherein, The conductive layer comprises carbon.

5. The laminated elastomer sensing device according to claim 1, 2 or 3, wherein, The conductive layer includes carbon particles doped into the elastomeric material matrix.

6. The laminated elastomer sensing device according to claim 5, wherein, The elastomer material is silicone.

7. The laminated elastomer sensing device according to any of the preceding claims, wherein, The conductive layer has a stiffness similar to that of the electrical insulating layer.

8. The laminated elastomer sensing device according to any of the preceding claims, wherein, The conductive layer has a stiffness greater than that of the electrical insulating layer.

9. The laminated elastomer sensing device according to any of the preceding claims, wherein, The stiffness of the conductive layer is at least 10 times greater than that of the electrical insulating layer.

10. A capacitive sensor, the capacitive sensor comprising: First electrical insulation support layer, The first conductive electrode layer is supported by the first electrically insulating support layer. A first electrically insulating dielectric layer, supported by a first electrically insulating support layer and / or a first conductive electrode layer, wherein at least a portion of the first electrode layer remains uncovered within the capacitive sensor. The second conductive electrode layer is supported by the first electrically insulating dielectric layer. A second electrically insulating dielectric layer, supported by the first electrically insulating dielectric layer and / or the second conductive electrode layer, wherein at least a portion of the second conductive electrode layer remains uncovered within the capacitive sensor. The third conductive electrode layer, which is supported by the second electrically insulating dielectric layer, and An electrically insulating top layer, which is supported by the second electrically insulating dielectric layer and / or the third conductive electrode layer, while at least a portion of the third conductive electrode layer remains uncovered within the capacitive sensor.

11. The capacitive sensor of claim 10, further comprising at least one adhesive between any one or more of the layers.

12. The capacitive sensor or laminated elastomer sensing device according to any of the preceding claims, wherein, The conductive layer is exposed within the capacitive sensor to facilitate connection to sensing electronics.

13. A method for manufacturing a stacked body for a capacitive sensor, the method comprising the steps of: To bond the first conductive layer to the second electrically insulating layer, A compressive force is applied to cause the first conductive layer to align with the second electrical insulating layer.

14. A method of manufacturing a capacitive sensor or laminated elastomer sensing device according to any of the preceding claims, the method comprising the steps of: Position at least two stacked layers in a compression device; as well as The compression device is used to apply a compressive force between the at least two stacked layers.

15. The method according to claim 14, wherein, The compression device is configured to move a predetermined distance during use.

16. The method according to claim 14 or 15, wherein, The compression device is configured to apply a predetermined force during use.

17. The method according to any one of claims 14 to 16, wherein, When the electrical insulating layer is in an uncured or more preferably partially cured state, compression occurs between the one or more conductive layers and the one or more electrical insulating layers.

18. The method according to any one of claims 14 to 17, the method further comprising the step of heating the one or more electrically insulating layers to transition the layers from an uncured or partially cured state to a cured state.

19. The method according to any one of claims 14 to 18, wherein, The conductive layer is substantially cured or cross-linked before it comes into contact with the electrically insulating layer.

20. The method according to any one of claims 14 to 19, wherein, The compression device is a compressor.

21. The method according to claim 20, wherein, The press includes a positioning device configured to assist in positioning and / or securing the stacked body within the press.

22. The method according to any one of claims 14 to 19, wherein, The compression device is a roller.

23. The method according to any one of claims 14 to 20 or 22, the method comprising a positioning device configured to assist in positioning and / or securing the stacked body, and wherein, The positioning device includes a frame configured to limit the lateral expansion of the stacked body in a direction substantially perpendicular to the compressive force.

24. The method according to claim 23, wherein, The framework includes a support platform configured to receive and support at least a portion of the layer stack.

25. The method according to claim 23 or 24, wherein, The positioning device is removable.

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