GENERATING VIRTUAL OPTOELECTRONIC DATA

Abstract

An electronic device for simulating a joint, in particular a knee joint, and for providing kinematic data sets, includes a simulation unit configured to generate a joint model with at least a first joint bone and a second joint bone. The simulation unit is configured to integrate at least a first and a second virtual measuring unit into the joint model. The at least first virtual measuring unit is at the at least first joint bone and the at least second virtual measuring unit is at the second joint bone. A calculator unit is configured to process data of the at least first and second virtual measuring units.

Claims

1. An electronic device for simulating a joint, and for providing kinematic data sets, comprising: a simulation unit which is provided and configured to generate a joint model with at least a first joint bone and a second joint bone, wherein the simulation unit is provided and configured to integrate at least a first virtual measuring unit and a second virtual measuring unit into the joint model, wherein the first virtual measuring unit is arranged on the first joint bone and the second virtual measuring unit is arranged on the second joint bone; and a calculator unit provided and configured to process data of the at least first virtual measuring unit and the second virtual measuring unit.

2. The electronic device according to claim 1, wherein the device is provided and configured to infer a relative position of the first joint bone to the second joint bone based on data from the first virtual measuring unit and the second virtual measuring unit.

3. The electronic device according to claim 1, wherein a plurality of parameters and their combinations are variable or simulatable.

4. The electronic device according to claim 3, wherein the following parameters are selectable or combinable with each other as desired: different load cases; anatomical variants of the joint model; patient size and corresponding bone size; patient data; position of the first virtual measuring unit and the second virtual measuring unit on the joint; and orientation of the first virtual measuring unit and the second virtual measuring unit.

5. The electronic device according to claim 1, wherein base data of the first virtual measuring unit and the second virtual measuring unit is computable during a simulation cycle and the device is provided to output data sets resulting from the base data.

6. The electronic device according to claim 5, wherein the data sets resulting from the base data are provided for training neural networks.

7. The electronic device according to claim 1, wherein base data of the first virtual measuring unit and the second virtual measuring unit is outputted over time and over flexion and/or extension of the joint.

8. The electronic device according to claim 1, wherein the device is provided and configured to extend the simulation of the joint by further bony structures.

9. A method for simulating a joint using the electronic device according to claim 1, comprising the steps of: generating the joint model with the simulated unit, the joint model being generated with at least the first joint bone and the second joint bone; integrating at least the first virtual measuring unit and the second virtual measuring unit into the joint model; and processing data of the at least first virtual measuring unit and the second virtual measuring unit, wherein the joint is a hip joint, shoulder joint, elbow joint, knee joint, ankle joint, wrist joint and/or spine.

10. A computer-implemented method for simulating a joint model and training and validating neural networks using the electronic device according to claim 1, the method comprising the steps of: providing a validated, virtual joint model with the electronic device; integrating the first virtual measuring unit and the second virtual measuring unit into the joint model with a measuring device; outputting and processing data sets based on data output of the first virtual measuring unit and the second virtual measuring unit with the calculator unit; training neural networks based on the data sets from the previous step with a training unit; and validating the neural networks with a validation unit.

11. A computer-readable storage medium comprising instructions for performing the computer-implemented method according to claim 10.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0042] FIG. 1 is an illustration showing a device according to an embodiment of the present disclosure; and

[0043] FIG. 2 is an illustration showing a sequence according to an embodiment of the present disclosure.

DETAILED DESCRIPTION

[0044] The following describes configuration examples of the present disclosure based on the accompanying figures.

[0045] FIG. 1 is an illustration showing a device 1 according to an embodiment of the present disclosure. FIG. 1 shows the electronic device 1 for simulating a joint, in particular a knee joint, and for providing kinematic data sets.

[0046] The device 1 has a simulation unit 7, which is provided and configured to generate a joint model 2 with at least a first joint bone 3 and a second joint bone 4. The simulation unit 7 is provided and configured to integrate at least a first and a second virtual, preferably inertial measuring unit 5 into the joint model 2. The at least first virtual, preferably inertial measuring unit 5 is arranged at the at least first joint bone 3 and the at least second virtual, preferably inertial measuring unit 5 is arranged at the second joint bone 4.

[0047] FIG. 1 shows a calculator unit 8 and a measuring device 9. The measuring device 9 is provided and configured to integrate and use at least a first and a second measuring unit 5. The calculator unit 8 is provided and configured to process data of at least the first and second virtual, preferably inertial, measuring units 5. The arrangement of the virtual measuring units 5 at the first joint bone 3 and at the second joint bone 4 is merely exemplary. FIG. 1 also shows a training unit 10 and a validation unit 11 which are provided and configured to train and validate neural networks based on the data output of the device 1.

[0048] FIG. 2 is an illustration showing a sequence according to an embodiment of the present disclosure. In a first step S1, possible variant simulations are imported when a validated, virtual joint model 2 is provided. This concerns the setting of parameters, for example the anatomy, the load case, the BMI and/or the soft tissue situation.

[0049] In a step S2, the virtual, preferably inertial measuring units 5 are integrated at the first joint bone 3 and at the second joint bone 4. Position, orientation and type are taken into account due to the integration of the virtual measuring units 5.

[0050] In a next step S3, the acquisition and output of the data obtained/generated from the virtual, preferably inertial measuring units 5 takes place. This is inertial measuring unit data and/or kinematic data and/or a phenotype derived from the obtained data.

[0051] This is followed by a step S4 in which the neural network, in particular AI/ML applications 6 is/are trained by means of a training unit 10. The training refers to the kinematics, the phenotype and the relative position as well as orientation of the first joint bone 3 to the second joint bone 4, e.g. femur to tibia.

[0052] In a final step S5, the neural network/the AI/ML application 6 has to be validated by means of a validation unit 11 with respect to the simulation and with respect to at least one patient.