Therapeutically competent bioprinted living tissue

Abstract

An artificial tongue is provided. The artificial tongue includes a tongue tissue formed by a bioprinting process, an antenna embedded within the tongue tissue and configured to wirelessly receive power from an external device, a processor embedded within the tongue tissue and operably coupled to the antenna, and a piezoelectric element embedded within the tongue tissue and operably coupled to the processor. The piezoelectric element is configured to deform in response to an applied electrical bias, and the processor is configured to cause the electrical bias to be applied to the piezoelectric element based on the power received by the antenna.

Description

Technical Field

[0001] This disclosure relates to biotechnology and body tissue substitutes. Specifically, this disclosure relates to the manufacture of bioprinted body substitutes, including structural and software elements that facilitate the integration of transplanted body tissues and physical therapy. Background Technology

[0002] Bioprinting typically refers to the process of obtaining cells from a donor organ and fabricating multilayered cells using a computationally designed approach to form three-dimensional slices of tissue. An example of a body tissue substitute is the tongue. One of the challenges in tongue reconstruction and / or transplantation lies in its unique form and function. While most skeletal muscles in the human body move in a single plane, or at most two dimensions, the tongue is capable of movement in three dimensions. Furthermore, the tongue has the ability to voluminously alter the space of the oral cavity, thereby manipulating sound waves. Although neurovascular connections or reconstruction of the tongue can be performed, replicating the tongue's complex movements can be challenging because the tongue relies on coordinated muscular activity between the tongue itself and muscles in the floor of the mouth, throat, pharynx, palate, and lips. Therefore, full functional rehabilitation of a transplanted tongue can be difficult and may depend on the adequate recovery of various sensory and motor functions. Summary of the Invention

[0003] Embodiments of this disclosure relate to a bioprinted artificial tongue. The artificial tongue includes tongue tissue formed by a bioprinting process, an antenna embedded within the tongue tissue and configured to wirelessly receive power from an external device, a processor embedded within the tongue tissue and operatively coupled to the antenna, and a piezoelectric element embedded within the tongue tissue and operatively coupled to the processor. The piezoelectric element is configured to deform in response to an applied electrical bias voltage, and the processor is configured to apply an electrical bias voltage to the piezoelectric element based on power received from the antenna.

[0004] Other embodiments relate to a method of manufacturing a bioprinted artificial tongue. The method includes: bioprinting tongue tissue; forming an antenna within the tongue tissue, the antenna being configured to wirelessly receive power from an external device; forming a processor within the tongue tissue, the processor being operatively coupled to the antenna; and forming a piezoelectric element within the tongue tissue. The piezoelectric element is operatively coupled to the processor and configured to deform in response to an applied electrical bias. The processor is configured to apply an electrical bias to the piezoelectric element based on the power received by the antenna.

[0005] The above description of the invention is not intended to depict every illustrated embodiment or implementation of this disclosure. Attached Figure Description

[0006] The accompanying drawings included in this application are incorporated in and form a part of this specification. They illustrate embodiments of the present disclosure and, together with the description, explain the principles of the disclosure. The drawings are merely illustrative of certain embodiments and do not limit the scope of the disclosure.

[0007] Figure 1A This is a side view of the bioprinted tongue in the first position.

[0008] Figure 1B It is in the second position. Figure 1A A side view of a bioprinted tongue.

[0009] Figure 1C It is in the third position. Figure 1A A side view of a bioprinted tongue.

[0010] Figure 2 This is a schematic diagram of a bioprinted tongue system according to an embodiment.

[0011] Figure 3 This is a block diagram of a bioprinted tongue system according to an embodiment.

[0012] Figure 4 This is a block diagram of a method for training a knowledge base for a bioprinted tongue system according to an embodiment.

[0013] Figure 5 A block diagram of a processing system according to an embodiment is depicted.

[0014] Figure 6 This is a block diagram of an illustrative cloud computing environment according to an embodiment, the cloud computing environment having one or more computing nodes of local computing devices used by cloud customers to communicate with them.

[0015] Figure 7 This is a block diagram of a set of functional abstraction layers provided by a cloud computing environment according to an embodiment.

[0016] It is worth noting that, for simplicity and clarity, all elements in the figures are illustrated. For the sake of simplicity and to aid in understanding the illustrated embodiments, elements that are useful or necessary in commercially viable embodiments and are fully understood may not be shown. Detailed Implementation

[0017] This disclosure relates to bioprinted tissues and to systems for controlling the movement and position of such bioprinted tissues. Specifically, embodiments of this disclosure relate to a bioprinted tongue that can be transplanted into a patient and then programmably controlled during subsequent speech therapy to produce controlled movement of the tongue muscles. Controlled tongue movement enables more efficient and effective treatment and can accelerate the patient's recovery process. In some embodiments, the bioprinted tongue is not simply used for initial treatment but can facilitate appropriate movement of the tongue muscles throughout the lifespan of the bioprinted transplanted tongue.

[0018] Typically, bioprinting is the process of obtaining cells from a donor organ and turning those cells into printable bio-ink. Cell layers are laid out according to a calculated design to create small tissue slices. For example, bioprinting can be used to create artificial bone, skin, blood vessels, tongue tissue, and various internal organs. In one example method of bioprinting, cells are taken from a human and cultured to allow them to multiply. The cultured cells are then loaded into a specialized bioprinter. The cells are then layered, for example, using a hydrogel as a support structure. Finally, as several layers of cells are printed into a three-dimensional (3D) structure, they grow into mature tissue and can be used for medical purposes. It should be understood that this is merely one example method of using bioprinting to form tissue (e.g., a tongue), and any suitable bioprinting method can be used in the context of embodiments of this disclosure. That is, bioprinting methods can be modified in any suitable way to create various 3D tissues for regenerative medicine, drug testing trials, and body part transplantation. For a bioprinted tongue, it may be desirable to ensure that the tongue moves properly during speech, ensuring that the tongue contacts different parts of the mouth, and thus producing different types of sounds. If the tongue does not move properly, the user will not be able to speak properly. Therefore, it may be desirable to ensure proper movement of the tongue within the mouth.

[0019] In some embodiments, piezoelectric devices (e.g., piezoelectric actuator strips) can be used to control the movement or position of a bioprinted tongue. Typically, a piezoelectric actuator converts an electrical signal (or electrical bias) into a precisely controlled physical displacement (i.e., stroke). When current and / or voltage is applied, the underlying piezoelectric material changes size. By extension, if a force is applied to the piezoelectric device, current and / or voltage can be generated. Piezoelectric actuators release relatively little heat and consume a small amount of electricity when operating under energized conditions, and are therefore suitable for bioimplantation systems. One example type of piezoelectric actuator is called a strip actuator (also known as a bending actuator), and it is designed to produce a relatively large mechanical deflection in response to an electrical signal. This deflection provides a large stroke and a very limited stopping force (i.e., low stroke and high stopping force) compared to stacked actuators. In a strip actuator, two thin layers of piezoelectric ceramic are bonded together, typically with a consistent polarization orientation, and electrically connected in parallel. When an electrical input is applied, one ceramic layer expands while the other contracts, causing the actuator to bend. In this embodiment discussed below, one or more piezoelectric devices may be embedded (or printed) into the bioprinted tongue, and the bending of the piezoelectric devices may be coordinated to precisely change the position of specific portions of the tongue.

[0020] In this embodiment, neural networks and other deep learning systems can be used to assist speech therapy by intelligently controlling the deformation and bending of various piezoelectric devices implanted in a bioprinted tongue to move different parts of the muscles to desired locations. Artificial neural networks (ANNs) (more generally also called neural networks) are computational systems composed of multiple simple, highly interconnected processing elements (nodes) that process information through their dynamic state responses to external inputs. ANNs are processing devices (algorithms and / or hardware) loosely modeled based on the neuronal structure of the mammalian cerebral cortex, but modeled on a much smaller scale. Such systems learn tasks progressively and autonomously through examples, and they have been successfully applied to, for example, speech recognition, text processing, and computer vision. Large ANNs may have hundreds or thousands of processor units, while the mammalian brain has billions of neurons, and the magnitude of their overall interaction and developmental behavior increases accordingly.

[0021] Many types of neural networks are known, starting with feedforward neural networks such as multilayer perceptrons, deep learning neural networks (DNNs), and convolutional neural networks. Feedforward neural networks are artificial neural networks (ANNs) where connections between units do not form loops. Deep learning neural networks are artificial neural networks with multiple layers of hidden units between the input and output layers. Similar to shallow ANNs, DNNs can model complex nonlinear relationships. For example, DNN architectures used for object detection and parsing generate synthetic models where objects are represented as hierarchical synthesis of image primitives. Additional layers enable the synthesis of features from lower layers, thus giving the potential to model complex data with fewer units than shallow networks that perform similarly. DNNs are often designed as feedforward networks.

[0022] In some embodiments, neural networks and other deep learning systems can be used to generate speech therapy models based on, for example, tongue movement patterns captured from MRI image analysis, spoken content from the history of one or more users, and sounds corresponding to different tongue movement patterns. These trained models can be used to assist speech therapy by intelligently controlling the deformation and bending of various piezoelectric devices implanted in a bioprinted tongue to move different parts of the tongue muscles to desired positions.

[0023] Various embodiments of this disclosure are described herein with reference to the accompanying drawings. Flowcharts and cross-sectional views in the drawings illustrate these systems and methods according to different embodiments. In some alternative implementations, the steps in the flowcharts may occur in a different order than that indicated in the drawings. Alternative embodiments may be designed without departing from the scope of this disclosure. It should be noted that various connections and positional relationships (e.g., above, below, adjacent, etc.) are illustrated between elements in the following description and drawings. Unless otherwise specified, these connections and / or positional relationships may be direct or indirect, and this disclosure is not intended to limit this aspect. Thus, coupling of entities may refer to direct or indirect coupling, and positional relationships between entities may be direct or indirect positional relationships. As an example of an indirect positional relationship, the reference in this specification to forming layer "A" on layer "B" includes one or more intermediate layers (e.g., layer "C") between layer "A" and layer "B," provided that the intermediate layers substantially do not alter the relevant characteristics and functions of layer "A" and layer "B."

[0024] The following definitions and abbreviations will be used to interpret the claims and description. As used herein, the terms “comprising,” “including,” “having,” “possessing,” “containing,” or any other variation thereof are intended to cover non-exclusive inclusion. For example, a composition, mixture, process, method, article, or apparatus that comprises a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such composition, mixture, process, method, article, or apparatus.

[0025] For the purposes described below, the terms “up,” “down,” “right,” “left,” “vertical,” “horizontal,” “top,” “bottom,” and their derivatives will refer to the structures and methods described in the orientation shown in the figure. The terms “cover,” “top,” “on top,” “positioned on,” or “positioned on top of” mean that a first element (such as a first structure) is present on a second element (such as a second structure), wherein an inserted element may be present between the first and second elements. The term “direct contact” means that a first element, such as a first structure, and a second element, such as a second structure, are connected at the interface of the two elements without any intermediate structure.

[0026] Referring now to the accompanying drawings, where similar reference numerals denote the same or similar elements, and first referring to Figure 1, several examples of tongue positions are shown, each different tongue position relating to a different sound. Human 100 is shown having different body parts related to speech. Specifically, Figure 1A The palate 106, the roof of the mouth 116, the oral cavity 114, the lips 104, the nose 102, the epiglottis 108, the larynx 110, and the tongue 112 are shown. Figure 1A As shown, the tongue 112 is in the first position to form, for example, the sound "th". Figure 1B In this position, the tongue 112 is in the second position to form, for example, the sound "r". Figure 1C In this position, the tongue (112) is in the third position to produce the "bl" sound. It should be understood that... Figure 1A-1C The examples shown are presented only to illustrate that the tongue can be positioned in various different locations (i.e., relative to the lips 104, the top of the mouth 116, and within the oral cavity 114, etc.) to produce various different sounds. In some embodiments of the invention, the bioprinted tongue can be moved into these different locations using (or by means of) an embedded piezoelectric band, one or more processors, a power supply, and a knowledge base based on, for example, machine learning and / or deep learning neural networks. Generally, the knowledge base includes information about the relationship between tongue position and sound, and the processor causes the piezoelectric band to be powered according to the information contained in the knowledge base. The power (i.e., current or voltage) applied to the piezoelectric band causes the band to bend or deform, which in turn causes the bioprinted tongue to twist in a specific manner corresponding to the desired tongue position associated with a particular sound.

[0027] Now for reference Figure 2 An example of a bioprinted tongue system 150 is shown. Figure 2As shown, the bioprinted tongue system 150 includes a bioprinted tongue 112 and an external mobile device 206 connected to a network 208. As discussed in detail below, the external mobile device 206 may be a cellular phone, and this is merely one example of a mobile device capable of communicating with and transmitting power to the bioprinted tongue 112. It should be understood that any other suitable type of mobile device may be used.

[0028] In some embodiments, the bioprinted tongue 112 includes a processor 202, an antenna 200, and a plurality of piezoelectric strips 204. In some embodiments, the processor 202 (or a printed integrated circuit) is printed (or formed) inside the bioprinted tongue 112 and includes a unique identifier. In these embodiments, the bioprinted tongue 112 is controlled by an external mobile device 206 based on the unique identifier.

[0029] In other embodiments, one or more of the processor 202, antenna 200, and piezoelectric bands 204 may be surgically implanted into a patient's actual tongue (i.e., not a bioprinted tongue) to assist in speech therapy. In these embodiments, these components may be manufactured individually and then inserted into the tongue.

[0030] In some embodiments, antenna 200 is configured to wirelessly receive power from a wireless power source and distribute energy from antenna 200 to processor 202 and / or piezoelectric band 204. Antenna 200 may receive power according to one or more of a variety of different wireless charging technologies. One technology utilizes a charging pad using tightly coupled electromagnetic induction or non-radiative charging. Another technology utilizes a charging bowl or surface-mount charger using loosely coupled or radiative electromagnetic resonant charging, which can transfer charge over a distance of several centimeters. Both tightly coupled inductive and loosely coupled resonant charging technologies operate on the same physical principle: a time-varying magnetic field that induces current in a closed loop in the line (e.g., antenna 200). Another technology is the use of decoupled radio frequency (RF) wireless charging, which allows trickle charging capability over distances of many feet. RF wireless charging can be particularly effective in the current embodiment, where the wireless power source can be located at a greater distance from the bioprinted tongue 112 so as not to interfere with speech function or tongue movement.

[0031] In some embodiments, antenna 200 is also configured to receive information or other suitable voice therapy instructions. This information may be processed by processor 202 to generate controlled electrical signals to be sent to the respective piezoelectric bands 204. This information may be received directly from external mobile device 206 (or more generally, external devices such as a user's cellular phone). In other examples, information may be received indirectly from network 208. In these examples, information is wirelessly transmitted from network 208 to external mobile device 206, and then from external mobile device 206 to antenna 200 of the bioprinted tongue 112. As described above, the example of a cellular phone as external mobile device 206 is merely one example of a device that can wirelessly connect the bioprinted tongue 112 to network 208, and any other suitable wireless device may be used.

[0032] In some embodiments, the wireless power source is the battery of an external mobile device 206 (e.g., a smartphone or personal digital assistant (PDA)). In these embodiments, the battery of the external mobile device 206 can be used to power the device itself and also wirelessly transmit a portion of its power to the bioprinted tongue 112. In an example where the external mobile device 206 uses uncoupled radio frequency (RF) wireless charging technology, a user may be able to position the phone several feet away from the bioprinted tongue 112 (e.g., in their pocket, on a nearby table, or plugged into a nearby charging station). Moreover, in some embodiments, the external mobile device 206 may have one or more physical therapy or speech training software applications installed thereon. In these embodiments, a user can view the display screen of the external mobile device 206 and follow any instructions provided by the application for speech therapy while receiving power from the battery of the external mobile device 206 to operate the different components of the bioprinted tongue 112. Although the above describes an example of a battery for a cellular phone (i.e., external mobile device 206), it should be understood that the power source can be any suitable device capable of sending sufficient energy to the antenna 200 and thereby powering any other peripheral power-consuming components of the processor 202, the piezoelectric band 204, and the bioprinted tongue 112.

[0033] like Figure 2 As shown, in some embodiments, the bioprinted tongue 112 includes a plurality of piezoelectric bands 204 connected to a processor 202. Figure 2 In the embodiment shown, antenna 200 wirelessly receives power from external mobile device 206 and distributes the power to processor 202, which in turn distributes a portion of the power to piezoelectric band 204. However, in other embodiments, power is distributed directly from antenna 200 to piezoelectric band 204 (i.e., without processor 202 as an intermediate element).

[0034] exist Figure 2In the diagram, piezoelectric bands 204 are shown distributed at various locations on the tongue 112. However, it should be understood that this is for illustrative purposes only, and the piezoelectric bands 204 may be distributed in any suitable manner according to the muscular system of a given tongue 112 and the desired deflection required to achieve certain sounds. Furthermore, the piezoelectric bands 204 (which are generally elongated rectangular in shape) are shown extending in the anteroposterior direction of the tongue 112. However, they may be oriented in any suitable direction, and some piezoelectric bands 204 may be oriented in a direction different from the others (i.e., some piezoelectric bands may extend diagonally relative to the anteroposterior direction of the tongue 112).

[0035] Furthermore, the piezoelectric bands 204 can be positioned at different depths within the thickness of the tongue 112. As discussed above, the 3D bioprinting process can involve configuring the cells of the tongue 112 for printing layer by layer. In this way, the piezoelectric bands 204 can be formed (or 3D printed) at intermediate locations within the thickness of the tongue 112 (i.e., in the intermediate stage of manufacturing the 3D product). For this purpose, some piezoelectric bands 204 can be located at different thicknesses of the tongue 112 relative to other piezoelectric bands 204. Furthermore, in some examples, multiple piezoelectric bands 204 can be stacked on top of each other in a plan view (i.e., a top view) to increase the bending strength of the stacked bands. In other words, for example, assuming that more energy is required to bend the central portion of the tongue 112 (i.e., where there may be a greater tissue thickness) compared to the sides of the tongue 112, multiple piezoelectric bands 204 can be stacked in this central portion to increase the overall bending strength in that region. In some embodiments, the piezoelectric bands 204 are also printed in layers during the layer-by-layer printing of the tongue 112.

[0036] like Figure 2 As shown, the bioprinted tongue 112 also includes a processor 202 (e.g., an integrated circuit chip). The processor 202 is operatively coupled to each of the piezoelectric bands 204 and is configured to individually control the application of current / voltage to each piezoelectric band 204. This allows for individual control over whether and how much current / voltage a particular piezoelectric band 204 receives. Therefore, for a specific sound (e.g., Figure 1A As shown in the “th” sound) and the associated tongue position, only some piezoelectric bands in piezoelectric band 204 can be activated, and some piezoelectric bands in piezoelectric band 204 can receive more / less current / voltage than other piezoelectric bands. Similarly, for different specific sounds (e.g., Figure 1B As shown in the “r” sound and the associated tongue position, different combinations of piezoelectric bands 204 can be activated relative to the “th” sound, and different piezoelectric bands 204 can receive more / less current / voltage than other piezoelectric bands.

[0037] As described above, in some embodiments, the processor receives instructions regarding the movement of the bioprinted tongue 112 from an external source, such as network 208 or external mobile device 206. These instructions for tongue movement may be based on a speech / physiotherapy program designed by a medical expert, or they may be based on text (e.g., a book or magazine) or any other suitable source. These instructions are then interpreted by processor 202 and relayed to piezoelectric band 204 to induce movement of the tongue 112. In some embodiments, the control of piezoelectric band 204 may be timed to synchronize with other instructions provided to the user on a display device (e.g., the display screen of external mobile device 206). For this purpose, the display device may display a word or sentence to the user and instruct the user to begin speaking the word at a given time. When the user attempts to speak the word by moving the bioprinted tongue 112, this effort can be enhanced (or assisted) by controlled deformation of piezoelectric band 204. In other embodiments, during speech therapy, the bioprinted tongue system 150 creates a visualization of tongue muscle movement patterns on a display screen of an external mobile device 206, and piezoelectric bands 204 generate additional forces on the bioprinted tongue muscles 112. In this way, users can understand how they should speak by viewing this information on the display screen.

[0038] As described above, regarding the general function of the piezoelectric device, if a force is applied to the piezoelectric band 204, a current and / or voltage can be generated. Accordingly, if a user undergoing speech therapy attempts to move the tongue 112 independently (i.e., without the assistance of the piezoelectric band 204), stress / strain is applied to the piezoelectric band 204, thereby generating a certain amount of electricity. In some embodiments, the bioprinted tongue system 150 includes sensors (not shown) that can measure the user-generated current in each piezoelectric band 204 and then transmit this information to the processor 202. Thus, in some embodiments, the processor 202 is capable of processing these user-generated current measurements, which allows insight into the unassisted strength of the user's bioprinted tongue 112. Therefore, in some examples, this can be achieved by storing the measurements in a memory device (e.g., Figure 3 The memory device 302, or Figure 5 These current measurements are stored in RAM 510 or ROM 508 to track the user's recovery or treatment progress over time. By monitoring the user's progress in this way, speech therapy can potentially be modified based on individual progress. For example, if the user is struggling with a particular sound (e.g., "th") or tongue position as evidenced by current measurements from a historical user, the speech therapy program can be modified to produce more / less deflection assistance regarding certain piezoelectric bands 204. In other words, if there is an indication that the user is struggling with unassisted movement on the left side of the tongue, the speech therapy program can be modified to increase assistance regarding the piezoelectric bands 204 located on that side of the tongue 112.

[0039] Now for reference Figure 3 A schematic diagram of a bioprinted tongue system 300 is shown. System 300 includes a bioprinted tongue 112, an external mobile device 206 operatively coupled to the bioprinted tongue 112, and a network 208 operatively coupled to the mobile device 206. The external mobile device 206 includes a power source 304 and is configured to transmit power and data 306 via an antenna (not shown) of the external mobile device 206. The bioprinted tongue 112 includes an antenna 200 configured to receive power and data 306 transmitted by the external mobile device 206. The bioprinted tongue 112 also includes a processor 202 operatively coupled to the antenna 200. In some embodiments, the bioprinted tongue 112 also includes a memory device 302 operatively coupled to the processor 202. Furthermore, the bioprinted tongue 112 includes a plurality of piezoelectric bands 204 electrically connected to the processor 202. The processor 202 is configured to send electrical signals to the piezoelectric bands 204, thereby causing deflection or bending of the piezoelectric bands 204.

[0040] It should be understood that in some embodiments, the bioprinted tongue system 300 also includes a power storage device (e.g., a battery or capacitor, not shown). In these embodiments, power received via the antenna can be stored in the battery for use by the processor and piezoelectric band (or any other component of the bioprinted tongue system 300). In this case, the system can still operate using the energy contained within the power storage device even if the external mobile device 206 does not actively transfer power to the bioprinted tongue system 300.

[0041] It should be understood that in embodiments where the bioprinted tongue 112 includes a memory device 302, the memory device 302 may include instructions or other data (e.g., information associated with certain sounds or tongue positions, and related instructions to move certain piezoelectric bands 204 to certain positions associated with these sounds) that enable the tongue to move without the assistance of an external mobile device 206. Therefore, if the external mobile device 206 is not in operation, powered off, not near the tongue, or otherwise not transmitting data / power, the bioprinted tongue 112 may still be able to operate for a period of time based on at least one of the memory device 302 and a power storage device (not shown).

[0042] Now for reference Figure 4This illustrates an exemplary embodiment of using a neural network and deep learning module 406 to create a knowledge base 408 to aid in the performance of speech therapy. In this embodiment, historical tongue movement data 402 and MRI image analysis and data 404 are fed into the neural network and deep learning module 406 to create a knowledge corpus 408. The historical tongue movement data 402 may be based on an individual user or multiple different users. The knowledge base 408 is then used to perform effective therapy on the user's bioprinted tongue 112. Furthermore, the speech therapy performed on the bioprinted tongue 112 can be used to collect additional MRI and movement data that can be used to further refine the knowledge base 408. In some embodiments, the system captures tongue movement patterns and historical spoken content from MRI image analysis and from various different users and adds them to the knowledge corpus 408. Sounds associated with tongue movement patterns are also collected and added to the knowledge corpus 408. Once the knowledge base 408 is created, the system will be able to simulate tongue muscle movement patterns and thus be able to identify how the muscles of the bioprinted tongue 112 should move. Based on tongue muscle movement patterns, the system will also be able to calculate how much force is required for different bioprinted tongues 112 to move.

[0043] In some embodiments, machine learning is performed relative to the movement patterns of the bioprinted tongue 112 within the oral cavity, and thus, sound generation from contact between the oral cavity and different parts of the bioprinted tongue 112 within the oral cavity is identified. In some embodiments, based on the movement patterns of the bioprinted tongue 112 within the oral cavity, the system can identify which part of the muscles of the bioprinted tongue 112 requires additional force. In some embodiments, based on the muscle movement patterns of the bioprinted tongue 112, the system identifies how much force is required to move the muscles of the bioprinted tongue 112, and this can be based on the unit weight of the tissue and / or the distance of movement required to move that part of the bioprinted tongue 112 to a specific location. In some embodiments, the system also identifies the sequence of movements of the bioprinted tongue 112 muscles required to perform particle movement of the bioprinted tongue 112 within the oral cavity. In some embodiments, the system identifies how much electricity is required for a specific movement of the muscles of the bioprinted tongue 112.

[0044] In some embodiments, the system is configured to create a 3D simulation of a bioprinted tongue 112 for manufacturing purposes, and this 3D simulation takes into account each of the desired movements and movement patterns of the bioprinted tongue 112. The system also simulates different spoken content and voice generation techniques. The simulation engine generates a model of how piezoelectric bands are printed inside the tongue muscles, such that the piezoelectric bands can also produce similar muscle movements and generate the required force in the bioprinted tongue 112. Based on the required force to be generated externally, the system simulates how much piezoelectric band to print and the position of the piezoelectric band within the muscles of the bioprinted tongue 112. The simulation engine identifies the position of the piezoelectric band within the muscles of the bioprinted tongue 112, enabling it to produce the desired muscle movements. The knowledge base 408 also captures muscle movement sequences as any bioprinted tongue 112 moves with the user's speech. In some embodiments, the sequences of muscle movements of the bioprinted tongue 112 are stored in processor 202 or another memory device. In some embodiments, the processor 202 (or printing circuitry) controls the movement of individual piezoelectric bands 204 printed at different locations on the bioprinted tongue 112. Each piezoelectric band 204 is identified based on the position of the bioprinted tongue 112, and therefore, the processor 202 controls each piezoelectric band 204 individually. When a simulation of the bioprinted tongue 112 along with the piezoelectric bands 204 and the processor 202 is generated, the proposed system initiates 3D tongue printing based on this simulation.

[0045] Now for reference Figure 5 An exemplary processing system 500 according to one embodiment is shown, to which this embodiment can be applied. The processing system 500 includes at least one processor (CPU) 504 operatively coupled to other components via a system bus 502. A cache 506, a read-only memory (ROM) 508, a random access memory (RAM) 510, an input / output (I / O) adapter 520, a sound adapter 530, a network adapter 540, a user interface adapter 550, and a display adapter 560 are operatively coupled to the system bus 502.

[0046] First storage device 522 and second storage device 524 are operatively coupled to system bus 502 via I / O adapter 520. Storage devices 522 and 524 can be any of disk storage devices (e.g., magnetic disk or optical disk storage devices), solid-state magnetic devices, etc. Storage devices 522 and 524 can be the same type of storage devices or different types of storage devices.

[0047] Speaker 532 is operatively coupled to system bus 502 via sound adapter 530. Transceiver 542 is operatively coupled to system bus 502 via network adapter 540. Display device 562 is operatively coupled to system bus 502 via display adapter 560.

[0048] First user input device 552, second user input device 554, and third user input device 556 are operatively coupled to system bus 502 via user interface adapter 550. User input devices 552, 554, and 556 may be any of a keyboard, mouse, keypad, image capture device, motion sensing device, microphone, device incorporating the functionality of at least two of the preceding devices, or any other suitable type of input device. User input devices 552, 554, and 556 may be of the same type or different types. User input devices 552, 554, and 556 are used to input information to and output information to system 500. In some embodiments, graphics processing unit (GPU) 570 is operatively coupled to system bus 502. In these embodiments, the GPU performs training and inference on MRI images of a bioprinted tongue system 590 using a deep learning object detection model.

[0049] The processing system 500 may also include other elements (not shown), and omit certain elements, as readily apparent to those skilled in the art. For example, various other input and / or output devices may be included in the processing system 500, depending on the specific implementation of the processing system 500, as readily understood by those skilled in the art. For example, different types of wireless and / or wired input and / or output devices may be used. Furthermore, additional processors, controllers, memories, etc., in different configurations may be utilized, as readily understood by those skilled in the art. These and other variations of the processing system 500 will readily occur to those skilled in the art in light of the teachings of the invention provided herein.

[0050] It should be understood that while this disclosure includes a detailed description of cloud computing, the implementation of the teachings cited herein is not limited to cloud computing environments. Rather, embodiments of this disclosure can be implemented in conjunction with any other type of computing environment now known or developed hereafter.

[0051] Cloud computing is a service delivery model that enables convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with the service provider.

[0052] Cloud computing environments are service-oriented, focusing on statelessness, loose coupling, modularity, and semantic interoperability. At the heart of cloud computing is the infrastructure comprising a network of interconnected nodes.

[0053] See now Figure 6This describes an illustrative cloud computing environment 650. As shown, the cloud computing environment 650 includes one or more cloud computing nodes 610 that can communicate with local computing devices used by cloud consumers, such as, for example, personal digital assistants (PDAs) or cellular phones 654A, desktop computers 654B, laptop computers 654C, and / or automotive computer systems 654N. The nodes 610 can communicate with each other. They can be physically or virtually grouped (not shown) in one or more networks, such as private clouds, community clouds, public clouds, or hybrid clouds, or combinations thereof, as described above. This allows the cloud computing environment 650 to provide infrastructure, platforms, and / or software as services that cloud consumers do not need to maintain on their local computing devices. It should be understood that... Figure 6 The types of computing devices 654A-N shown are intended to be illustrative only, and computing node 610 and cloud computing environment 650 can communicate with any type of computerized device via any type of network and / or network-addressable connection (e.g., using a web browser).

[0054] See now Figure 7 This demonstrates the 650 (cloud computing environment) Figure 6 This provides a set of functional abstractions. It should be understood beforehand. Figure 7 The components, layers, and functions shown are intended to be illustrative only, and embodiments of the invention are not limited thereto. As described, the following layers and corresponding functions are provided:

[0055] The hardware and software layer 760 includes hardware and software components. Examples of hardware components include: a mainframe 761; a server 762 based on a RISC (Reduced Instruction Set Computer) architecture; a server 763; a blade server 764; a storage device 765; and a network and network components 766. In some embodiments, the software components include network application server software 767 and database software 768.

[0056] The virtualization layer 770 provides an abstraction layer from which the following examples of virtual entities can be provided: virtual servers 771; virtual storage 772; virtual networks 773, including virtual private networks; virtual applications and operating systems 774; and virtual clients 775.

[0057] In one example, management layer 780 may provide the following functionalities: Resource Provisioning 781 provides dynamic procurement of computing resources and other resources used to perform tasks within the cloud computing environment. Metering and Pricing 782 provides cost tracking as resources are utilized within the cloud computing environment and bills or invoices for the consumption of these resources. In one example, these resources may include application software licenses. Security provides authentication for cloud consumers and tasks, as well as protection for data and other resources. User Portal 783 provides access to the cloud computing environment for consumers and system administrators. Service Level Management 784 provides cloud resource allocation and management to ensure that required service levels are met. Service Level Agreement (SLA) Planning and Fulfillment 785 provides pre-scheduling and procurement of cloud resources, anticipating future requirements for those resources according to the SLA.

[0058] Workload layer 790 provides examples of functionalities that can leverage a cloud computing environment. Examples of workloads and functionalities that can be provided from this layer include: mapping and navigation 791; software development and lifecycle management 792; virtual classroom education delivery 793; data analytics processing 794; transaction processing 795; and training processing for a bioprinted tongue knowledge base 796.

[0059] This invention can be a system, method, and / or computer program product with any possible level of technical detail integration. The computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions thereon for causing a processor to execute aspects of the invention.

[0060] Computer-readable storage media can be tangible means for retaining and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital universal disk (DVD), memory sticks, floppy disks, mechanical encoding devices such as punch cards or protrusions in slots having instructions recorded thereon, and any suitable combination of the foregoing. As used herein, computer-readable storage media should not be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses passing through fiber optic cables), or electrical signals transmitted through wires.

[0061] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to a suitable computing / processing device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network), or to an external computer or external storage device. The network may include copper cables, optical fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to a computer-readable storage medium within the suitable computing / processing device.

[0062] Computer-readable program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, integrated circuit configuration data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​(such as Smalltalk, C++, etc.) and procedural programming languages ​​(such as the "C" programming language or similar programming languages). The computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as a standalone software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)) or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs) may execute computer-readable program instructions by utilizing state information from the computer-readable program instructions to personalize the electronic circuitry in order to perform aspects of this invention.

[0063] The present invention will now be described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0064] These computer-readable program instructions may be provided to a processor of a computer or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / actions specified in one or more blocks of a flowchart and / or block diagram. These computer-readable program instructions may also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner, such that the computer-readable storage medium storing the instructions includes an article of manufacture containing instructions that implement aspects of the functions / actions specified in one or more blocks of a flowchart and / or block diagram.

[0065] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus, or other device to produce computer-implemented processing, such that the instructions executed on the computer, other programmable apparatus, or other device perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0066] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than indicated in the figures. For example, two blocks shown consecutively may actually be completed as a single step, executed simultaneously, substantially simultaneously, or with partial or complete temporal overlap, or the blocks may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function.

[0067] Various embodiments have been described for illustrative purposes, and these descriptions are not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein has been chosen to best explain the principles of the embodiments, their practical application, or technical improvements to technologies found in the market, or to enable those skilled in the art to understand the embodiments disclosed herein.

Claims

1. An artificial tongue, comprising: Tongue tissue formed using bioprinting technology; An antenna, which is embedded within the tongue tissue and configured to wirelessly receive power from an external device; A processor, which is embedded within the tongue tissue and operatively coupled to the antenna; A piezoelectric element, which is embedded within the tongue tissue and operatively coupled to the processor, is configured to deform in response to an applied electrical bias. as well as sensor, The processor is configured to apply the electrical bias voltage to the piezoelectric element based on the power received by the antenna, and The sensor is configured to measure the current generated by stress or strain applied by the piezoelectric element, and the processor is configured to process the measurement of the current.

2. The artificial tongue of claim 1, wherein the plurality of piezoelectric elements are embedded in different locations and / or orientations within the tongue tissue, wherein the processor is configured to individually cause different electrical biases to be applied to at least some of the plurality of piezoelectric elements, thereby causing different portions of the tongue tissue to deform.

3. The artificial tongue according to claim 2, wherein, The plurality of piezoelectric elements are configured to cause the tongue tissue to change position within the user's oral cavity during selective deformation, the changed position of the tongue tissue corresponding to the type of sound.

4. The artificial tongue according to claim 1, wherein, The piezoelectric element is a belt actuator, which includes two elongated strip-shaped ceramic layers connected in parallel.

5. The artificial tongue according to claim 1, wherein, The antenna is further configured to receive instructions from the external device, which, when processed by the processor, cause the electrical bias to be applied to the piezoelectric element.

6. The artificial tongue according to claim 5, wherein, The instructions are based on a knowledge corpus generated by a deep learning neural network.

7. The artificial tongue according to claim 6, wherein, The knowledge corpus is generated from at least one of the historical movement data of the tongue tissue and the analysis of MRI images of the tongue tissue.

8. The artificial tongue according to claim 1, wherein, The external device includes a display element configured to display voice therapy instructions to the user.

9. The artificial tongue according to claim 8, wherein, The external device is configured to transmit voice therapy data to the processor via the antenna, the voice therapy data corresponding to the displayed voice therapy instructions.

10. The artificial tongue according to claim 9, wherein, The voice therapy data includes instructions that, when processed by the processor, cause the piezoelectric element to deform in a manner that is in parallel with the voice therapy instructions displayed on the display element.

11. A method for manufacturing an artificial tongue, the method comprising: Bioprinted tongue tissue; An antenna is formed within the tongue tissue, and the antenna is configured to wirelessly receive power from an external device; A processor is formed within the tongue tissue, the processor being operatively coupled to the antenna; A piezoelectric element is formed within the tongue tissue, the piezoelectric element being operatively coupled to the processor and configured to deform in response to an applied electrical bias. as well as A sensor is formed within the tongue tissue. The processor is configured to apply the electrical bias voltage to the piezoelectric element based on the power received by the antenna, and The sensor is configured to measure the current generated by stress or strain applied by the piezoelectric element, and the processor is configured to process the measurement of the current.

12. The method of claim 11, wherein the plurality of said piezoelectric elements are embedded in different locations and / or orientations within the tongue tissue, and wherein the processor is configured to individually cause different electrical biases to be applied to at least some of the plurality of piezoelectric elements, thereby causing different portions of the tongue tissue to deform.

13. The method according to claim 12, wherein, The plurality of piezoelectric elements are configured to cause the tongue tissue to change position within the user's oral cavity during selective deformation, the changed position of the tongue tissue corresponding to the type of sound.

14. The method according to claim 11, wherein, Forming the piezoelectric element includes forming two elongated strip ceramic layers and electrically connecting the strip ceramic layers in parallel.

15. The method according to claim 11, wherein, The antenna is further configured to receive instructions from the external device, which, when processed by the processor, cause the electrical bias to be applied to the piezoelectric element.

16. The method according to claim 15, wherein, The instructions are based on a knowledge corpus generated by a deep learning neural network.

17. The method according to claim 16, wherein, The knowledge corpus is generated from at least one of the historical movement data of the tongue tissue and the analysis of MRI images of the tongue tissue.

18. The method according to claim 11, wherein, The antenna was formed using a bioprinting process.

19. The method according to claim 11, wherein, The processor is formed using a bioprinting process.

20. The method according to claim 11, wherein, The piezoelectric element is formed using a bioprinting process.

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