Orthotic support and stimulus systems and methods
Inventors
Assignees
Publication Number
US-10923235-B2
Publication Date
2021-02-16
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 involving modeling internal forces experienced by a biological joint (such as a human knee) based on external measurements, and then using the comparison of modeled internal forces from different external conditions to drive control actions such as muscle stimulation. The system uses sensors to acquire measurements of limb positions or movements and employs a model of the joint to estimate the corresponding internal forces. When a specific condition (such as pain or instability) is experienced by the user, it is denoted via input (for example, a button press), allowing the system to associate that problematic event with internal force characteristics rather than only with external motion.
The background problem addressed is the limitation of existing state machine-based control architectures, particularly in assistive rehabilitation, prosthetics, and movement aids. Traditional systems rely on static, pre-defined templates of movement or position that do not account for the wide variability from user to user or changing external conditions. These systems fail to adequately recognize or respond to dynamic conditions that fall outside the template, and direct measurement of relevant internal joint forces is generally impractical.
By employing modeling of internal joint forces based on measured external data, and allowing for dynamic creation or adaptation of state definitions in response to marked problematic conditions, the invention enables more accurate control actions that maintain internal joint force magnitudes within desired limits. The method improves state discrimination by selecting the optimal parameters, from both measured and modeled data—including those found most significant during real-world operation—for determining control states.
Claims Coverage
There are two primary independent claims in the patent, each defining a system for modeling internal forces applied to a joint using measured movement data and controlling muscle stimulation based on comparisons of these forces.
System for modeling and comparing internal joint forces to control muscle stimulation
The system includes at least one memory, at least one electrode, at least one sensor (which can include an additional electrode, accelerometer, or positional angular sensor or combinations thereof), and at least one controller. The controller: 1. Measures first and second movements or positions of a limb attached to a user's joint via the sensor(s). 2. Conditions the measurements using at least one signal conditioner including a frequency filter and analog-to-digital converter. 3. Models first and second internal forces applied to the joint based on the conditioned measurements at different time points. 4. Compares the modeled internal forces. 5. Stimulates muscle of the user, via the electrode, based on the comparison of the modeled internal forces.
System for modeling internal forces and controlling a stimulator based on comparison
The system comprises at least one memory and at least one controller (coupled to the memory) configured to: - Measure first and second movements of a limb attached to a user's joint using at least one sensor (which may include electrodes, accelerometers, or positional angular sensors or combinations). - Condition these measurements via at least one signal conditioner. - Model first and second internal forces to the joint based on the conditioned measurements at different points in time. - Compare the first and second modeled internal forces. - Communicate with a stimulator to stimulate the user's muscle via an additional electrode based on the comparison.
In summary, the inventive features center on a system that, by modeling and comparing internal joint forces derived from external movement data, enables adaptive and targeted muscle stimulation based on conditions relevant to the user's unique biology and real-world experience.
Stated Advantages
The invention enables robust and accurate control operation in both previously-observed and new, previously unencountered operational conditions.
By modeling internal forces rather than only relying on external position or motion, the system extends control to encompass effects not readily measured and allows for better analogs to specific joint pains or problematic states.
State discrimination is improved by dynamically selecting and using parameters (measured or modeled) most indicative of problematic conditions, even if not known at the time of system design.
Creation of predictive models and state definitions can occur long after initial deployment, allowing adaptation to user-specific differences and real-world scenarios.
The approach reduces the computational inefficiency of exhaustive, broad state templates by focusing on derived, salient characteristics relevant to the control goal.
Systems using the invention better reflect the structure being controlled and improve overall system response by using internal force modeling in state determination.
Documented Applications
Control of orthopedic muscle stimulation devices affixed to a leg to mitigate pain or instability by supporting the knee joint.
Improvement of golf cart stability by modulating steering ratio to reduce the risk of roll-over, based on modeled internal stability parameters.
Augmentation of pogo stick safety by modulating damping of the device in response to modeled unsafe conditions during use.
General application to various animal (including human) joints such as elbow, finger, toe, ankle, hip, shoulder, neck, wrist, and spine, including coupling with braces or prostheses.
Operation in data flow control and broader control situations where direct control of higher-order effects from multiple excitation sources is desired.
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