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Publication Number
US-12508143-B2
Publication Date
2025-12-30
Expiration Date
Abstract
The present disclosure provides a knee brace for preventing or mitigating injury to a user's knee. The knee brace includes a first sensor positioned with respect to a femur, and a second sensor positioned with respect to a tibia. The knee brace further includes a stiffening component configured to stabilize the user's knee, and a processor that receives sensor data from the first sensor and the second sensor to determine a relative position between the femur location and the tibia location. The processor is configured to activate the stiffening component when the relative position exceeds at least one of a first threshold, a second threshold, and a third threshold, wherein the first threshold indicates a potential over-rotation, wherein the second threshold indicates a potential over-abduction, and wherein the third threshold indicates a potential hyperextension.
Core Innovation
The disclosed knee brace uses a first sensor positioned relative to a location on a femur and a second sensor positioned relative to a location on a tibia. A processor determines their relative position from sensor data and activates a stiffening component when the position exceeds thresholds indicating potential over-rotation, over-abduction, or hyperextension. Plural sensor arrangements reduce an effect of drift.
The patent also describes a knee-brace configuration in which a processor uses a machine-learning model and sensor data from the femur- and tibia-positioned sensors to determine whether to activate the stiffening component. A method determines and evaluates relative position against the three stated thresholds before activation. The problem stated in the background section is not explicitly described in patent.
Claims Coverage
The three independent claims are claims 1, 13, and 18. They cover two knee-brace configurations and a method, represented below as three inventive features.
Threshold-based sensor-controlled knee brace
Claim 1 covers a knee brace with sensors positioned relative to locations on the femur and tibia. The processor determines their relative position and activates a knee-stabilizing stiffening component when that position exceeds thresholds indicating potential over-rotation, over-abduction, or hyperextension. Plural sensor arrangements are configured to reduce an effect of drift among the sensor data.
Machine-learning-controlled knee brace
Claim 13 covers a knee brace with femur- and tibia-positioned sensors and a stiffening component. The processor uses a machine-learning model and sensor data from both sensors to determine whether to activate the stiffening component. The sensors include plural sensor arrangements configured to reduce an effect of drift among the sensor data.
Threshold-based method for stabilizing the knee
Claim 18 covers determining the relative position between a location on the femur and a location on the tibia using sensor data, evaluating that position against thresholds for potential over-rotation, over-abduction, and hyperextension, and activating a stiffening component when a threshold is exceeded. The plural sensor arrangements are configured to reduce an effect of drift among the sensor data.
The independent claims cover sensor-based and machine-learning-based brace activation, as well as a method that evaluates femur–tibia relative position against injury-related thresholds. The claims also specify plural sensor arrangements configured to reduce drift.
Stated Advantages
The knee brace is described as preventing or mitigating injury to a user's knee.
The stiffening component is configured to stabilize the user's knee.
The arrangement of plural sensors is configured to reduce an effect of drift among the sensor data.
Documented Applications
A knee brace and method for preventing or mitigating injury to a user's knee.
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