Human-Machine Signal Translation for Reliable Remote Control Feedback
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Solution Overview
Problem
Human-machine networked functional symbiotic integration, or Human Fusions, is hindered by the lack of reliable endpoint-to-endpoint connection and communication between humans and devices, preventing seamless control and sensory feedback across distances.
Innovation Solution
A system and method that utilize a controller with a processor to receive and translate physiological data from users into transmissible signals, enabling reliable communication across a network for devices to perform actions, and vice versa, using universal translation layers for endpoint-agnostic data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If direct neural connection is established between user and prosthetic device, then control precision and sensory feedback reliability are improved, but device complexity and implementation difficulty increase
Solution Approach 1:
The patent introduces an intermediary system comprising signal transducers, processors, and communication interfaces that mediate between the neural signals and the prosthetic device. This intermediary layer converts complex neural signals into standardized control commands while translating device feedback into perceptible sensory information, thereby maintaining control reliability without requiring direct neural-device connection
Solution Approach 2:
The system is divided into distinct functional modules: neural signal acquisition module, signal processing module, communication module, and device control module. Each module handles specific tasks independently, reducing overall system complexity while maintaining reliable control through specialized processing at each stage
2Stability of the object's composition
If physical connection between user and device is maintained, then control stability is improved, but user mobility and device versatility are restricted
Solution Approach 1:
The patent replaces mechanical/physical connection systems with wireless communication systems. Neural signals and control commands are transmitted via electromagnetic fields through standardized communication protocols, eliminating the need for physical tethers while maintaining control stability through error-correcting protocols and continuous signal validation
Solution Approach 2:
The system employs universal communication interfaces and standardized data formats that enable the same control system to work with multiple different device types (prosthetics, exoskeletons, robotic systems). This universality maintains control stability across different devices while significantly enhancing user mobility and device versatility
3Adaptability or versatility
If neural interface system is implemented, then human-machine integration capability is improved, but ease of operation and accessibility decrease
Solution Approach 1:
The system incorporates automated calibration and adaptive learning algorithms that automatically adjust to individual user characteristics without requiring manual configuration. The neural interface automatically trains and optimizes signal interpretation over time, reducing the operational burden on users while maintaining high integration capability
Solution Approach 2:
The system dynamically adjusts operational parameters such as signal threshold, sampling rate, and feedback intensity based on user state and environmental conditions. These automatic parameter changes maintain optimal integration performance while simplifying operation for users with varying levels of technical expertise
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Facilitates bidirectional communication between humans and devices, allowing users to control remote devices while experiencing sensory feedback, thereby transcending physical barriers and enhancing applications in various industries by providing a universal and reliable connection.
Implementation Method 1
at least one electrode configured to record a physiological data related to movement from a nerve and/or a muscle of a user
Data Source
AI summary
Systems and methods for human-machine integration to facilitate Human Fusions by providing reliable endpoint-to-endpoint connection and communication between humans and devices are described. A controller that includes a processor can receive physiological data related to movement from a user; translate the physiological data related to movement to a transmissible signal to be sent across a network; and send, by the controller, the transmissible signal across the network to at least one device connected to the network. The at least one device can translate at least a portion of the transmissible signal to a form usable by a component of the at least one device to perform an action based on the physiological data related to movement. In some instances, the device can provide feedback to the controller for transmission to the user.