Patent ID: 11877870
Assignee: CONSULTATION SEMPERFORM INC
Field: Medical technology (Instruments)
Classification: CPC A | IPC A

Claim 7:
8. A computer-based system for determining a prediction of future injury to a knee anterior cruciate ligament of a subject, the computer-based system comprising:
a motion sensing input device generating a plurality of images of the subject, the subject having no markers attached to the subject, the motion sensing input device having photoelectric elements, transfer gates that are responsive to a control pulse for transferring the charges stored on the individual photoelectric elements as an image signal to vertical shift registers and a horizontal shift register for transferring an image signal from the vertical shift registers through a buffer amplifier to an outlet, the plurality of images being captured at least 30 frames per second, each of the plurality of images having a resolution of at least 640×480 pixels and 10 bit depth and having at least 2,048 levels of sensitivity;
a computer having a processor, a memory and input/output capability, the processor being configured to perform:
a pose recognition or a skeletal tracking and calculating of joint angles at different time points;
the processor being further configured to analyze from the plurality of images a motion of the subject, an angle of the knee joint of the subject, jumping and landing mechanics of the subject in reference to either the pose recognition, or the skeletal tracking and calculating of the joint angles at the different time points based on the analysis of the plurality of images;
the processor being then further configured to determine the prediction of future injury to the knee anterior cruciate ligament of the subject based on the analysis of the plurality of images, wherein the prediction of future injury to the knee anterior cruciate ligament of the subject further comprises an ACL risk score;
the processor being then further configured to save the ACL risk score into the memory as “at risk”;
and the processor being then further configured to generate and operate a prediction screen displaying the ACL risk score, wherein the ACL risk score is expressed on the prediction screen as “high risk” or “low risk”;
wherein the processor is configured to determine the prediction of future injury to the knee anterior cruciate ligament by performing machine learning processes utilizing a model trained from a set of data that contains both desired inputs and desired outputs,
in which the set of data for training the model includes images with and without the desired inputs,
and each image includes a label for the desired output designating whether the image contained a desired training object;
wherein the machine learning processes include supervised regression learning which produces continuous outputs, wherein the continuous outputs are a continuous range of values for the ACL risk score.