Human-Machine Integration System and Method

Abstract

To provide systems and methods for human-machine integration to facilitate human fusions by realizing reliable endpoint-to-endpoint connection and communication between humans and devices.SOLUTION: A method comprises: receiving movement-related physiological data from a user; translating the movement-related physiological data into a transmissible signal to be sent across a network; and sending, by the controller, the transmissible signal across the network to at least one device connected to the network. The at least one device translates at least a portion of the transmissible signal into a form usable by a component of the at least one device to perform an action based on the movement-related physiological data. Optionally, the device provides feedback to the controller for transmission to the user.SELECTED DRAWING: Figure 8

Description

Detailed Description of the Invention

[0001] (Related Application) This application claims priority to U.S. Provisional Application No. 62 / 819,698, filed on March 18, 2019, with the title "SOW ON HUMAN FUSIONS WITH UTL / CDL TO NEURAL INTERFACES". The entire content of the provisional application is incorporated herein by reference for all purposes.

Technical Field

[0002] The present disclosure generally relates to the symbiotic integration (fusion) of human and machine networked (human) functions on the nervous system, and more specifically to human-machine integration systems and methods for facilitating human fusion by providing reliable endpoint connections and communications between humans and devices.

Background Art

[0003] Recently, prosthetic devices have been developed that can provide long-term reliable sensory input to users, directly collect command information from the users' nerves and muscles, and provide a direct connection between the users and the prosthetic devices. In fact, the direct connection can be established without the prosthetic device contacting the user. As long as the prosthetic device can receive input from the user, the prosthetic device can be anywhere in the world. This physical separation between humans and prosthetic devices has given rise to the dream of the symbiotic integration (fusion) of human and machine networked (human) functions on the nervous system, which aims to connect the human brain, technology, and society through neural interfaces so that human thoughts can transcend the physical barriers of the body. In other words, human fusion theoretically enables a person physically present in one location to work or experience in another (real or virtual) location. However, human fusion requires reliable endpoint connections and communications between humans and devices, which have not yet been realized.

Summary of the Invention

Means for Solving the Problem

[0004] The present disclosure relates to a system and method for human-machine integration that promotes human fusion by providing a highly reliable connection and communication between humans and devices.

[0005] In one aspect, the present disclosure can include a method for human-machine integration that promotes human fusion by providing a highly reliable connection and communication between humans and devices. The steps of the method can be executed by a controller including a processor, and the method at least includes receiving physiological data related to movement from a user, translating the physiological data related to movement into a transmissible signal transmitted via a network, and transmitting the transmissible signal to at least one device connected to the network via the network. The at least one device translates at least a part of the transmissible signal into a form that can be used by a component of the device to execute an action based on the physiological data related to movement.

[0006] In another aspect, the present disclosure can include a system that records physiological data related to a user's movement and transmits the data to a device capable of performing an action based on the received data. The system can include at least one electrode configured to record physiological data related to nerve and / or muscle movement from the user. The system further includes a controller connected to the electrode and connected to a network including a processor. The processor is configured to receive physiological data related to movement, translate the physiological data related to movement into a transmissible signal, and transmit the transmissible signal to at least one device connected to the network via the network. The device translates at least a portion of the transmissible signal into a form that can be used by a component of the device to perform an action based on the physiological data related to movement.

[0007] The foregoing and other features of the present disclosure will become apparent to those of ordinary skill in the art to which the present disclosure pertains upon reading the following description with reference to the accompanying drawings.

Brief Description of the Drawings

[0008]

Figure 1

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[0009] I. Definitions Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by those skilled in the art to which the present disclosure pertains.

[0010] As used herein, unless the context clearly indicates otherwise, the singular form can include the plural form.

[0011] As used herein, the terms "comprising" and / or "comprised of" can identify the presence of the described features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups.

[0012] As used herein, the term "and / or" can include any and all combinations of one or more of the associated listed items.

[0013] As used herein, terms such as "first", "second", etc. should not be used to limit the elements described by these terms. These terms are only used to distinguish one element from another. Thus, the "first" element described below can also be referred to as the "second" element without departing from the teachings of the present disclosure. The order of operations (or actions / steps) is not limited to the order shown in the claims or the figures unless otherwise specified.

[0014] As used herein, the term "human fusion" (or "symbiotic integration (fusion) of networked (human) functions of humans and machines on the nervous system") relates to enabling a user present in one location to work or experience in another (real or virtual) location. Human fusion connects the user's brain technically and socially via a human-device interface, which enables the user's entire brain and nervous system to transcend the barriers of the user's body. The human-device interface uses connections between endpoints (e.g., between at least one person and at least one device) to enable communication between endpoints (e.g., two-way communication). For example, it receives control signals from the device user, executes actions based on the control signals, and transmits feedback signals to the user based on the actions.

[0015] As used herein, terms such as "user", "person", etc. can refer to any organism including, but not limited to, humans. In the context of human fusion, the user can be a human whose nervous system is integrated with a device via a network.

[0016] As used herein, the terms "device", "machine", etc. can refer to one or more machines or electronic devices manufactured or modified for a specific purpose.

[0017] As used herein, the term "component" can refer to additional hardware and / or software, which may be part of the user or the device, or may be connected to and operate with the user or the device.

[0018] As used herein, the term "network" can refer to a connection system between endpoints, including users, devices, and additional hardware or software components related to the users and / or devices. For example, a user and a device can be networked to exchange information between the user and the device.

[0019] As used herein, the term "round-trip" can refer to the process of communicating via a network. For example, the communication can include a control signal that can be sent from the user to the device, and the device is prompted to send a feedback signal to the user in response to the control signal and / or an action executed based on the control signal.

[0020] As used herein, the term "symbiosis" can refer to a mutually beneficial interaction or relationship between different users and / or devices (e.g., an interaction that improves the experience or function of all parties involved).

[0021] As used herein, the term "integration" can refer to the coordination and / or mixing of separate elements (e.g., a human and a device) that were not previously associated.

[0022] As used herein, the term "control signal" can refer to information based on and / or generated from physiological data related to biological functions, and the physiological data may be measured, recorded, and / or analyzed. For example, the physiological data can be associated with physical movements including one or more of the movements of a user's hands, fingers, eyes, head, etc. Biological functions can include nerve signals recorded by one or more recording electrodes, electromyogram (EMG) signals, results of physical movements (such as pressing a button), etc.

[0023] As used herein, the term "feedback signal" can refer to information generated from a device in response to a control signal (e.g., receiving a control signal and actions performed in response to the control signal, etc.). For example, a feedback signal transmitted from a device can be a neural input to a user, and the neural input can be received and processed by the user's nervous system without compromising the encoded information. As an example, the feedback signal can be transmitted to the user using one or more stimulation electrodes.

[0024] As used herein, the term "endpoint diagnosis" can perform data transmission via a network, and the data transmission can be connected to and received and used by any entity of a specific network (e.g., one or more users and / or one or more devices). Endpoint diagnosis data transmission can use one or more additional components, and the components can translate the signal into something that can be used by an entity.

[0025] As used herein, the terms "translate", "translating", "translation", etc. can refer to a process of converting one type of signal into another type of signal, changing the format, but not substantially changing the information conveyed by the signal. For example, physiological data generated by a user's movement needs to be translated into a control signal that can be received and understood by a device. Similarly, a feedback signal from a device needs to be translated into a format that can be received and understood by the user. A general-purpose translation layer having at least one common data library is used to facilitate the conversion of signals into different formats.

[0026] As used herein, the term "common data library" can refer to information or processing that aids in signal conversion. For example, a common data library can include a wide range of algorithms that can be used to translate one signal into one or more possible different formats.

[0027] As used herein, the term "electrode" can refer to one or more conductors that contact a part of a user's body. In some cases, each individual conductor may also be referred to as a "contact". II. Summary

[0028] Human Fusions refers to a type of human-machine integration that enables a user to experience a sense of "direct" connection with a device while controlling a remote device located anywhere in the world. Thus, Human Fusions can expand human experience and expertise by enabling human-machine intervention between the user and the remote device, and such human-machine intervention can be further applied to a wide range of industries and applications, such as, for example, human health, humanoid robots, industry, military, social, entertainment, games, etc. However, due to the lack of a highly reliable and general-purpose connection and communication between humans and devices, Human Fusions has not yet been realized. This disclosure enables Human Fusions by providing such a highly reliable and general-purpose connection and communication between humans and devices.

[0029] This disclosure relates to a human-machine integration system and method for promoting Human Fusions by providing a reliable connection and communication between humans and devices at the endpoints, the system and method providing an endpoint diagnostic connection between at least one user and at least one remote device. During operation, the at least one remote device can receive a control signal from one or more users (transmitted via the network described herein) and execute an action based on the control signal. Similarly, one or more users can receive a feedback signal (e.g., a sensory feedback signal) regarding the action being executed from one or more remote devices (transmitted via the network described herein). Thus, one or more users can control one or more remote devices located anywhere in the world and experience a sense of "direct" connection feedback (without actually establishing a direct tactile connection) with the one or more devices. III. SYSTEM

[0030] One aspect of the present disclosure can include system 10 (FIG. 1), which can be used to achieve human-machine integration to facilitate human fusion by providing a highly reliable connection and communication between one or more humans and one or more devices. At the core of human fusion (or the symbiotic integration of networked functions of the nervous system between humans and machines) is the ability for a user in one location to work or experience in another (physical or virtual) location using a device in another location and to obtain sensory feedback from the device via a human-device interface. The human-device interface enables communication (e.g., two-way communication) between endpoints using a connection between endpoints (e.g., at least one human to at least one device). For example, a device can receive a control signal from a user, perform an action based on the control signal, and transmit a feedback signal to the user based on the action.

[0031] Accordingly, the human-device interface of system 10 connects one or more users 12 to one or more devices 14 via a network 16 that can facilitate two-way communication. The human-device interface of system 10 utilizes various hardware and software components to enable a general connection between one or more users 12 and one or more devices 14, and one or more users 12 and one or more devices 14 can transmit outputs or receive inputs via a common network structure capable of performing endpoint diagnostics. Note that one or more users 12 and one or more devices 14 can be referred to as endpoints, nodes, etc. of network 16. System 10 can enable any connection between user nodes and device nodes. FIG. 1 shows an example of a network arrangement from user 12 to device 14 via network 16, while FIGS. 2-4 show examples of different potential network arrangements. FIG. 2 shows an example of a network arrangement from multiple users 12-1, 12-2, …, 12-N to one device 14 via network 16. FIG. 3 shows another example of a network arrangement from user 12 to multiple devices 14-1, 14-2, …, 14-N via network 16. FIG. 4 shows another example of a network arrangement from users 12-1, 12-2, ..., 12-N to multiple devices 14-1, 14-2, ..., 14-N via network 16. Hereinafter, the terms "user 12" and "device 14" are used, but it can be understood that "user 12" refers to one or more users and "device 14" refers to one or more devices.

[0032] User 12 can provide physiological data related to movement, and the physiological data can be transmitted as a control signal to device 14 via network 16. As an example, the user may be a human, and the physiological data may be data recorded by, for example, one or more electrodes (e.g., surface electrodes, implanted electrodes, etc.) (e.g., data related to muscles, data related to nerves, etc.), or data collected by an input device (e.g., button presses, keystrokes, voice signals, etc.). The control signal can be transmitted to a component related to device 14 (e.g., a controller / microcontroller / processor related to the device), and device 14 can execute an action based on the control signal. The same or different components of device 14 (e.g., one or more sensors) can transmit a feedback signal in response to receiving the control signal and / or executing the action. The feedback signal can be transmitted to user 12 via network 16, and the user can receive the feedback signal. For example, the user can receive the feedback signal via one or more electrodes, and the feedback signal can include sensory feedback. Correspondingly, the communication between user 12 and device 14 can include a motor output from user 12, which is transmitted to device 14 via network 16 to instruct device 14 to execute an action, and device 14 transmits a feedback signal to user 12, and the user can receive sensory input. Thus, user 12 can control remote device 14 and also receive sensory feedback related to the control, enabling the user's brain and entire nervous system to transcend the barriers of the user's body and cross the distance separating user 12 and device 14. As an example, user 12 can be equipped with the HAPTIX iSens system, which can be connected to network 16 to provide physiological signals and receive feedback signals.

[0033] User 12 and device 14 are each an "endpoint" on network 16. User 12 and device 14 can include additional hardware and software elements, which are generally referred to as "controllers" and can include a processor and / or non-transitory memory, and facilitate connection to network 16 and / or communication via network 16. Network 16 between user 12 and device 14 can support a real-time, experiential human-in-the-loop system (for example, since at least the human sensory system is sensitive to multisensory integration and millisecond-level errors in timing between different information sources or in round-trip control cycles, the network needs to transmit data in a time-critical manner). Network 16 between user 12 and device 14 has high reliability, high bandwidth, low latency and guaranteed round-trip time, as well as proper management of incorrect packets and lost packets).

[0034] Even if the inputs and outputs may be different from each other, the connection between one or more humans and one or more devices may be a general-purpose connection. Note that network 16 takes into account hierarchical input and output distribution and is robust against failures in data transmission. As an example, this can be done as follows: negotiate and reach an agreement with user 12 and device 14 about the specific control information required, and train an algorithm for this specific translation (this action needs to be repeated for different users and / or devices). As another example, this can be done independently of the communication between user 12 and device 14 and has a general-purpose translation layer and a common data layer. In this example, when different common data layers are connected, the different common data layers can negotiate the mapping paradigm between the common data layers understood by the nodes. The mapping of different common data layers is automatically performed by software, requested from user 12 as a setup input, and / or adjusted as needed during connection. The common data library and translation enable general-purpose connection. When multiple users 12 (which may have different data collection / distribution mechanisms) are connected to network 16, each user 12 can have its own general-purpose translation layer. Similarly, when multiple devices 14 (which may have different data collection / distribution mechanisms) are connected to network 16, each device 14 can have its own general-purpose translation layer. As an example, if one user 12 is connected to network 16 but two different devices 14 are connected to network 16, the physiological data can be translated into a form acceptable by the two devices 14.

[0035] As shown in FIG. 5, network 16 includes a general-purpose translation layer 52 (general-purpose translation layer (U) 52) on the user side and a general-purpose translation layer 54 (general-purpose translation layer (D) 54) on the device side. Each general-purpose translation layer is generated with minimal computational overhead and does not significantly delay the round-trip signal. The general-purpose translation layers 52, 54 can be connected to network 16 and / or user 12 and device 14, and can also include hardware and software layers that convert between the application engine, and the input / output of user 12 and the general-purpose connection data stream, and between the input / output of device 14 and the general-purpose connection data stream. It should be noted that the general-purpose translation layer (U) 52 can convert human intentions and experiences into a data stream format acceptable to device 14 (and in some cases, vice versa, converting the output of the device into a format acceptable to user 12).

[0036] FIG. 6 further shows the general-purpose translation layers 52, 54 in detail. As shown in the figure, each of the general-purpose translation layers 52, 54 has a mapping layer, a common data library, and a network layer. In this example, each of the general-purpose translation layers 52, 54 is specific to the type of user (e.g., iSens or other data collection / distribution mechanisms that may be specific) or device. However, network 16 may have only a single general-purpose translation layer, and the translation layer may include one or more of the mapping layer, the common data library, and the network layer. One or more users 12 and one or more devices 14 can receive different data types and / or formats. The mapping layer and the common data library can encode / decode different data types and / or formats.

[0037] As shown in the figure, the general-purpose translation layer 52 can receive physiological data (physical data input) from the user 12 and process the physiological data before the processed physiological data is sent to the mapping layer. The mapping layer can obtain a translation key by referring to the common data library and encode the physiological data into a format that can be received by network transmission and / or a specific receiving device 14. For example, the common data library of the general-purpose translation layer 52 can provide translation between the user 12 and the network 16. The translated physiological data (or "transmittable data") can be sent to the network 16 via the network layer. In some cases, the network layer can add metadata to the translated physiological data.

[0038] The general-purpose translation layer 54 can receive physiological data (and any additional metadata) translated at the network layer. In some cases, the network layer can separate the metadata from the translated physiological data. The translated physiological data is sent to the mapping layer, which can obtain another translation key by referring to the common data library, decode the translated physiological data from the transmitted format, and encode the translated physiological data into a format acceptable to a specific receiving device 14. For example, the common data library of the general-purpose translation layer 54 can provide translation between the network 16 and the device 14. This re-translated physiological data (in a language acceptable to the device 14) can be processed and sent to the device 14 (physical data output). In response, the device 14 can send a feedback signal to the general-purpose translation layer 54 (physical data input), and the general-purpose translation layer can process the signal. The feedback signal can be sent to the mapping layer, which can obtain yet another translation key by referring to the common data library and encode the feedback signal into a format acceptable for transmission via the network and / or acceptable to a specific user 12. For example, the common data library of the general-purpose translation layer 54 can provide translation between the device 14 and the network 16. The translated feedback signal (which may also be referred to as "transmittable data") can be sent to the network 16 via the network layer. In some cases, the network layer can add metadata to the translated physiological data.

[0039] The general-purpose translation layer 52 can receive the feedback signal (and any additional metadata) translated in the network layer. In some cases, the network layer can separate the metadata from the translated feedback signal. The translated feedback signal is sent to the mapping layer, which can obtain an appropriate translation key by referring to the common data library, decode the translated feedback signal, and encode the feedback signal into a form acceptable to a specific receiving user 12. For example, the common data library of the general-purpose translation layer 52 can provide translation between the network 16 and the user 12. This re-translated feedback signal (in a language acceptable to the user 12, or a "feedback signal that the user can transmit") can be processed and sent to the user 12 (physical data output). For example, a feedback signal that the user can transmit can provide sensory feedback to the user 12 based on physiological data that provides instructions.

[0040] Figure 7 shows additional components that may be associated with the general-purpose translation layer 52 (user side) and 54 (device side) to facilitate communication between the user 12 and the device 14. For example, in addition to the general-purpose translation layer 52 or 54, both the user side and the device side have one or more physical layers (enabling data collection), an application layer, a security layer, and a network layer. As can be understood, the user side and / or the device side can include different layers, and Figure 7 simply shows an example. IV. Method

[0041] As shown in FIGS. 8 and 9, another aspect of the present disclosure can include methods 80, 90 for realizing human-machine integration in order to facilitate human fusion by providing a highly reliable connection and communication between one or more humans and one or more devices. For example, methods 80, 90 can be executed using the systems 10, 20, 30, or 40 shown in FIGS. 1-4 and using the translation hardware and software of FIGS. 5-7. Methods 80, 90 enable a user to control a remote device and also receive sensory feedback related to the control, allowing the user's entire brain and nervous system to transcend the barriers of the user's body and cross the distance between the user and the device. Network 16 provides a general-purpose connection between one or more users and one or more devices to enable the transmission of outputs and reception of inputs via a common network structure through which one or more users and one or more devices can each perform endpoint diagnostics. It should be noted that one or more users and one or more devices can be referred to as endpoints, nodes, etc. of the network. Hereinafter, the terms "user 12" and "device 14" are used, but it can be understood that "user 12" refers to one or more users and "device 14" refers to one or more devices.

[0042] For simplicity, methods 80, 90 are shown and described as being executed continuously, however, it should be understood and appreciated that the present disclosure is not limited by the illustrated order because some steps may occur in a different order and / or simultaneously with other steps shown and described herein. Also, not all of the described aspects are required to implement methods 80, 90, and / or more than the described aspects may be required to implement methods 80, 90. One or more aspects of methods 80, 90 can be stored in one or more non-transitory memory devices and can be executed by one or more hardware processors.

[0043] Referring to FIG. 8, the figure shows an example of method 80, which transmits physiological data from a user (e.g., user 12) as a control signal via a network (e.g., network 16). As an example, the user may be a human, and the physiological data may be, for example, data recorded by one or more electrodes (e.g., surface electrodes, implanted electrodes, etc.) (e.g., data related to muscles, data related to nerves, etc.), or data collected by an input device (e.g., button press, keystroke, voice signal, etc.). As an example, the user can be equipped with a HAPTIX iSens system, which may be connected to the network to provide physiological signals and can also receive feedback signals.

[0044] At step 82, physiological data related to movement can be received from a user (e.g., user 12) (e.g., received by the general-purpose translation layer (U) 52). At step 84, the physiological data related to movement can be translated into a control signal (e.g., translated by the general-purpose translation layer (U) 52 using a common data library). The control signal can be configured to be transmitted via the network. At step 86, the control signal can be transmitted via the network to at least one device (e.g., device 14) connected to the network (e.g., network 16).

[0045] Referring to FIG. 9, the figure shows an example of method 90 that receives a control signal and transmits a feedback signal via a network (e.g., network 16) (e.g., in response to receiving the control signal and / or performing an action based on the control signal, a feedback signal is transmitted from device 14).

[0046] In step 92, a control signal can be received (e.g., received by the general-purpose translation layer (D)). The control signal can be configured to be transmitted via a network. In step 94, the control signal can be translated into a form that can be used by at least one component of a device (e.g., device 14) (e.g., translated by the general-purpose translation layer (D)). Control data in a form that can be used by at least the components of the device (e.g., the controller / microcontroller / processor associated with the device) can be transmitted to at least the components of the device. The device can execute an action based on the control signal.

[0047] In step 96, based on the control signal, feedback can be received from a device (e.g., the same or different components of device 14) (e.g., received by the general-purpose translation layer (D)). In step 98, the feedback can be translated into a feedback signal so as to be transmitted via a network (e.g., transmitted to a component associated with user 12 via network 16) (e.g., translated by the general-purpose translation layer (D)). In step 100, the feedback signal can be transmitted via a network (e.g., network 16) to a user connected to the network (e.g., a component associated with user 12). The converted feedback signal may be a neural input (e.g., transmitted by one or more electrodes) that can provide sensory feedback to the user.

[0048] As shown in FIGS. 8 and 9, the communication between the user and the device can include the motor output from the user, and the output is transmitted to the device via the network to instruct the device to perform an action. Also, the device can send a feedback signal to the user, and the user can receive the sensory input. For example, the device or a component of the device can perform military actions, healthcare actions, game actions, entertainment actions, and / or social actions. V. Examples

[0049] The potential uses of human fusion are almost infinite. The following non-limiting examples show some potential uses of human fusion enabled by the systems and methods of the present disclosure, including medical uses, public security / defense uses, industrial uses, and social / entertainment / game uses. For example, the physiological data from user 12 can be input to control medical actions, public security / defense actions (e.g., related to the military, police, or similar organizations), industrial actions, and / or social / entertainment / game actions. User 12 can receive sensory feedback from devices related to medical actions, public security / defense actions (e.g., related to the military, police, etc.), industrial actions, and / or social / entertainment / game actions. The device can facilitate the implementation of medical actions, public security / defense actions (e.g., related to the military, police, etc.), industrial actions, and / or social / entertainment / game actions. The following examples are for illustrative purposes only and are not intended to limit the scope of the appended claims.

[0050] Medical Uses

[0051] Much of human fusion technology has emerged from research on mechanical devices for patients with severed limbs. One such mechanical device is a prosthetic device, which not only mechanically replaces a lost limb but also enables the patient to grasp, manipulate, and feel objects as if the limb had not been lost. In studying this prosthetic device, it was discovered that the prosthetic device did not even need to be connected to the patient for the patient to feel the object. Prosthetic devices that do not need to be connected to the patient lead to the concept of human fusion applicable to a wider range of medical uses, and using the human fusion system and method of the present disclosure, it is already possible to provide a reliable connection and communication between an endpoint between a human (e.g., a clinician) and one or more remote devices (e.g., medical tools related to a patient, which may be in a remote location). The system and method of the present disclosure can revolutionize medical practice by at least enabling medical practitioners to treat previously isolated populations and improving the safety and effectiveness of many medical procedures, both invasive and non-invasive.

[0052] Human fusion can materialize telemedicine. For example, using the system and method of the present disclosure, a physical examination will not be limited to a face-to-face interaction between a patient and a clinician. Instead, the patient and the clinician can be anywhere in the world, removing spatial, temporal, and financial barriers to medical care.

[0053] Human fusion technology can greatly expand the amount of information that can be collected when clinicians perform other common tests. Clinicians can better utilize the sense of touch to interpret and diagnose patients, rather than relying only on vision or other non-visual means. For example, when performing an intrauterine examination, an obstetrician can use human fusion to "sense" the fetal heartbeat or "sense" ultrasonic information indicating the presence of irregular tissue masses in the breast. As another example, surgeons engaged in robotic surgery can use human fusion to improve their sense of touch, which helps to identify specific anatomical structures that are difficult to detect visually.

[0054] Public security / defense applications

[0055] Human fusion also provides opportunities for the police, military, and other public security / defense organizations. The individual members of these police, military, and other public security / defense organizations receive high-level training but are exposed to danger on a daily basis. The lives of these individuals can be improved using the systems and methods of the present disclosure, building a symbiotic relationship between humans and robotic devices, enabling highly trained individuals to work more accurately from a safe distance, and ultimately preventing injuries that can lead to limb amputations and other diseases / deaths.

[0056] One of the most dangerous jobs in the military is that of an explosives disposal expert. The systems and methods of the present disclosure can enable an explosives disposal expert to experience the same feeling as working on-site even when not in the same location and use the device to disarm and dispose of explosives. This can eliminate the risk of a single mistake that could injure or kill the explosives disposal expert and also avoid the risk of being shot during the operation while working in a hostile environment.

[0057] Pilots can use robot control based on the systems and methods of the present disclosure to more precisely sense what is happening inside or to an aircraft. Feedback from a robot system (such as a drone pilot, a robotic aircraft, etc.) can be returned to the pilot to improve the control and operation of the aircraft.

[0058] Industrial applications

[0059] Human fusion can affect the experience of the physical reality of humanity, especially in relation to industry. By using the systems and methods of the present disclosure to fuse human consciousness with robots and other technologies, humans can physically distance themselves from dangerous or difficult-to-reach situations, but still perceive and function as if they were at the position of the robot.

[0060] By using the systems and methods of the present disclosure to enable humans to interact with materials remotely, manufacturing and other commercial purposes can be made safer, cheaper, and easier to achieve without losing the level of dexterity or sensory input that is usually directly obtained through physical interaction. A carpenter can use conventional carpentry tools, but can receive the sensation of fingers scanning a wall to feel studs and wires. A mechanic can diagnose the performance of an engine by "feeling" vibration or temperature information from sensors inside the engine. In other examples, an assembly worker can bend and manipulate iron with the strength and precision of a machine. That is, human fusion can democratize the advantages of manufacturing systems and give superhuman powers to various workers in various industries.

[0061] Social / entertainment / game applications

[0062] Human fusion can enhance the human experience of physical reality, particularly experiences related to social, entertainment, and / or gaming applications. Using the systems and methods of the present disclosure, sensations can be added to various social, entertainment, and / or gaming applications. The power of media lies in its ability to make users feel experiences through vision, sound, and interaction. Adding a sensory experience to video or audio data (other than vision and / or hearing) can enhance the experience and make it more powerful. Social media can be enhanced by enabling virtual contact between people, such as allowing a person to perceive the feeling of holding another person's hand. Sensory experiences also contribute to virtual contact in gaming applications, enhancing depth and immersion.

[0063] From the above description, those skilled in the art will recognize improvements, changes, and modifications. Such improvements, changes, and modifications are within the scope of the skilled person's art and are intended to be covered by the appended claims.

Claims

1. A system comprising: at least one electrode configured to record physiological data related to the movement of a user's nerves and / or muscles; a user-side controller connected to the at least one electrode, coupled to the user's nervous system via the at least one electrode, and connected to a network; the user-side controller includes a general-purpose translation layer having a mapping layer and a common data library, and a processor; the processor: receives physiological data related to movement; obtains a translation key by referring to the common data library, and maps the physiological data related to movement to a signal transmissible by using the translation key by the mapping layer, thereby translating the physiological data related to movement into the transmissible signal by the general-purpose translation layer; is configured to transmit the transmissible signal to a device-side controller connected to at least one device via the network; the device-side controller is connected to the user-side controller via the network, and includes another general-purpose translation layer having another common data library and another mapping layer, and another processor; the another processor: obtains another translation key by referring to the another common data library, and maps at least a part of the transmissible signal to a form that can be used by a component of the at least one device by using the another translation key by the another mapping layer, thereby translating at least a part of the transmissible signal into a form that can be used by a component of the at least one device in order to perform an action based on the physiological data related to movement; receives feedback from a sensor related to a component of the at least one device; obtaining yet another translation key by referring to the other common data library, and mapping the feedback to another transmissible signal by using the yet another translation key by the other mapping layer, thereby translating the feedback into the other transmissible signal, configured to transmit the other transmissible signal to the general-purpose translation layer of the controller on the user side, the other transmissible signal is translated into a format transmissible by the user by the controller on the user side, the format transmissible by the user is transmitted to the user as a feedback signal transmissible by the user, the controller on the user side generates the feedback signal transmissible by the user as an electrical stimulation signal transmitted to the nervous system of the user, for making the user experience a tactile sensation related to an action performed by the at least one device, as a nerve input of the nervous system of the user, and the common data library of the general-purpose translation layer of the controller on the user side has an additional translation key for translating the other transmissible signal into the format transmissible by the user. A system characterized by that.

2. The system according to claim 1, at least two devices are connected to the network, each of the at least two devices has a unique device-side controller, receives the transmissible signal, and each unique device-side controller of the at least two devices is configured to translate at least a part of the transmissible signal into a form that can be used by at least two components of the at least two devices in order to perform an action based on physiological data related to movement. A system characterized by that.

3. The system according to claim 2, The system is characterized in that the controller on the device side of the at least two devices translates at least a part of the transmissible signal into different forms that can be used by at least two components of the at least two devices.

4. The system according to claim 1, The system is characterized in that the processor of the controller on the user side promotes the translation from the physiological data related to the movement to the transmissible signal by executing the general-purpose translation layer.

5. The system according to claim 4, The system is characterized in that the processor of the controller on the device side promotes the translation from the transmissible signal to a form that can be used by a component of the at least one device by executing the other general-purpose translation layer.

6. The system according to claim 1, The system is characterized in that a component of the at least one device executes at least one of military actions, healthcare actions, game actions, entertainment actions, and social actions.

7. The system according to claim 1, The system is characterized in that the physiological data related to the movement is intended to control at least a part of at least one of military actions, healthcare actions, game actions, entertainment actions, and social actions.

8. The system according to claim 1, The system is characterized in that the at least one electrode includes at least one surface electrode or implantable electrode related to nerves and / or muscles.

9. The system according to claim 1, The at least one device includes a plurality of devices, and each of the plurality of devices has a different translation key for translating the transmissible signal into a form that can be used by components of each device of the plurality of devices. A system characterized by this.

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