Orthotic support and stimulus systems and methods
Inventors
Assignees
Publication Number
US-12121465-B2
Publication Date
2024-10-22
Expiration Date
2031-09-29
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Abstract
An embodiment of the invention includes (a) modeling a first internal force applied to a model of a user's joint based on a first external force externally applied to the joint at a first position; (b) modeling a second internal force applied to the model based on a second external force externally applied to the joint at a second position unequal to the first position; (c) comparing the first and second modeled internal forces; and (d) stimulating the user based on the comparison. Other embodiments are described herein.
Core Innovation
The invention provides a system and method for modeling internal forces in a user's joint based on outputs from sensors affixed near the joint, and controlling stimulation based on modeled outcomes rather than only external motion parameters. When a user experiences an undesirable event, such as pain, the system models the internal force corresponding to that event and stores it. It then uses a physical model to interpret future sensor data, comparing newly modeled internal forces with the previously stored force profiles identified as problematic.
This approach addresses the limitations of conventional state machine controllers that rely on fixed or pre-defined template patterns derived from general populations and do not account for individual anatomical variations or new, unanticipated situations. By leveraging dynamic modeling of internal forces excited by measured movement and position, the system is able to optimize the criteria for state determination and stimulation, dynamically adapting to changes in biomechanical structure, movement, and environment.
The invention further allows for inclusion of user input (such as a button press) at the time of an undesirable condition, enabling dynamic creation and update of state criteria in the field as specific problematic events occur. The system identifies the most significant modeled characteristics during these events and later uses this information to protect the joint or provide corrective action even under novel or previously unencountered movement conditions. This results in a robust, individualized, and adaptable control architecture that extends beyond limitations of prior art.
Claims Coverage
There is one independent claim in the patent, covering a system with inventive features relating to modeling internal joint forces, storing user-marked events, comparing modeled forces, and stimulating accordingly.
Modeling internal forces based on sensor outputs at different joint positions
The system models a first internal force applied to a user's joint using output from at least one sensor affixed near the joint at a first position, and models a second internal force at a second, different position. This modeling is not limited to direct measurement but utilizes sensor data and a computational model to estimate internal joint forces.
Storing modeled internal force upon user input
The processor stores the first modeled internal force when it receives input from the user, allowing for event-driven marking of problematic or informative conditions directly as experienced by the user.
Comparison of modeled internal forces to determine similarity
The system compares the first and second modeled internal forces to determine if they are similar, enabling recognition of problematic internal states regardless of external joint position or motion.
Stimulation of the user via an electrode based on modeled force comparison
Upon determining that the second internal force is similar to the first, the system stimulates the user (e.g., muscle stimulation for protection or correction) using an electrode, based on this internal model-driven comparison.
In summary, the claims cover a system that models internal joint forces from sensor data, stores modeled force states as marked by user input, detects recurrence of these states through modeling and comparison, and triggers user stimulation accordingly.
Stated Advantages
Enables robust and accurate control operation in both previously-observed and completely new operational conditions by using modeled internal forces instead of pre-defined external templates.
Improves the adaptability and individualization of control architecture by dynamically creating and updating state criteria in response to real-world user events.
Reduces the complexity and impracticality of exhaustively defining templates for all possible movements, allowing protection or correction based on internal system response rather than broad external patterns.
Facilitates better discrimination of problematic states through dynamic selection of significant parameters, rather than relying on a fixed laundry list of data items.
Improves the overall system response by more closely reflecting the structure and behavior of the controlled environment.
Documented Applications
Orthopedic muscle stimulation devices for pain mitigation or joint protection, particularly for knee support using sensor data and modeled internal forces.
Golf cart stability control by modulating steering ratio to reduce the likelihood of rollover, using vehicle sensor data and terrain models.
Pogo stick safety enhancement by dynamically controlling damping to minimize rider upset, using modeled rider and pogo stick movement parameters.
General applications to other animal (including human) joints, such as elbow, finger, toe, ankle, hip, shoulder, neck, wrist, and spine.
Use in stimulation systems to couple with braces or prostheses, including replacement limbs.
Use in non-physical applications, including data flow control in state machine implementations.
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