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US 2026/0215937 A1Published application
Method for controlling a movement behaviour of an artificial joint
AssigneeOtto Bock Healthcare Products GmbH
InventorRoland AUBERGER
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AssigneeOtto Bock Healthcare Products GmbH
InventorRoland AUBERGER
Estimating the term…
The invention relates to a method for controlling a movement behaviour of an artificial joint which has an upper part and a lower part, mounted thereon to pivot about a pivot axis, between which upper and lower part a device for influencing the pivotability or pivoting of the upper part relative to the lower part is arranged, which device is coupled to a control unit in which a rule set is stored and which activates, deactivates or modulates the device on the basis of input values for the rule set in order to influence the pivoting or pivotability, wherein sensor values of at least one sensor arranged on the upper part or lower part, which are detected during the use of the artificial joint, are supplied to at least one machine-learning-based estimating method which continuously calculates an estimate value for a kinetic or kinematic parameter or an expected kinetic or kinematic parameter from the sensor values and this estimate value is supplied to the rule set as an input value and is used therein as a criterion for activation, deactivation or modulation.
A method for controlling a movement behavior of an artificial joint which has an upper part and a lower part mounted on the upper part so as to pivot about a pivot axis between which upper part and lower part a device for influencing the pivotability or pivoting of the upper part relative to the lower part is arranged, which device is coupled to a control device in which a rule set is stored and which activates, deactivates, or modulates the device on the basis of input values for the rule set in order to influence the pivoting or pivotability, characterized in that sensor values from at least one sensor arranged on the upper part or the lower part (20), which are detected during the use of the artificial joint, are supplied to at least one machine-learning-based estimating method which continuously calculates an estimated value (K) for a kinetic or kinematic parameter (α) or an expected kinetic or kinematic parameter (α) on the basis of the sensor values and this estimated value (K) is supplied to the rule set as an input value and is used therein as a criterion for activation, deactivation, or modulation.
Dependencies are inferred from the claim text.