| CPC A61N 1/37282 (2013.01) [A61B 5/1101 (2013.01); A61B 5/1114 (2013.01); A61B 5/1118 (2013.01); A61B 5/112 (2013.01); A61B 5/4082 (2013.01); A61B 5/742 (2013.01); A61B 5/7455 (2013.01); A61N 1/36135 (2013.01); A61N 1/37247 (2013.01); A61N 1/37264 (2013.01); G06F 21/6254 (2013.01); G06T 11/00 (2013.01); G06T 19/006 (2013.01); G06V 10/82 (2022.01); G06V 40/25 (2022.01); G16H 20/30 (2018.01); G16H 40/40 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); G16H 80/00 (2018.01); H04N 5/272 (2013.01); H04N 7/141 (2013.01); A61N 1/36067 (2013.01); A61N 1/36071 (2013.01); A61N 1/36132 (2013.01); G06T 2210/41 (2013.01)] | 14 Claims |

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1. A method of remotely programming an implantable medical device that provides therapy to a patient, comprising:
establishing a first communication between a patient controller (PC) device and the implantable medical device, wherein the implantable medical device provides therapy to the patient according to one or more programmable parameters, the PC device communicates signals to the implantable medical device to set or modify the one or more programmable parameters, and the PC device comprises a video camera;
establishing a video connection between the PC device and a clinician programmer (CP) device of a clinician for a remote programming session in a second communication that includes an audio/video (A/V) session;
communicating a value for a respective programmable parameter of the medical device from the CP device to the PC device during the remote programming session; and
modifying, by the PC device, the respective programming parameter of the medical device according to the communicated value from the CP device during the remote programming session;
wherein the method further comprises:
automatically analyzing, by one or more processors, video data of the patient from the A/V session to identify a plurality of landmark points along a body of the patient indicative of pose or posture of the patient;
processing data related to the landmark points to identify a plurality of first metrics with each first metric representing a ratio of areas defined relative to selected landmark points;
processing data related to landmark points to identify a plurality of second metrics with each second metric representing a ratio of distances across the pose or posture of the patient;
providing the first and second metrics to a trained neural network to generate a patient metric indicative of patient condition; and
displaying a graphical user interface (GUI) component indicative of the patient metric using the CP device during the remote programming session.
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