SYSTEMS, METHODS, AND DEVICES FOR VIRTUALLY SUPERVISED MEDICAL WEIGHT LOSS TREATMENT PROGRAM ADMINISTERED VIA ON-DEMAND TELEHEALTH PROCTOR-OBSERVED PLATFORM
Disclosed herein are systems, methods, and devices for an image-based, computer vision approach for anthropometric measurement of a user using an automatically generated three-dimensional model of the user. Also disclosed herein are systems, methods, and devices associated with a telehealth proctoring platform that can be used to remotely proctor, monitor, and manage patients over the course of a medical treatment plan. The telehealth proctoring platform may be used to collect and retrieve various kinds of data associated with a patient, such as at-home diagnostic test data, the anthropometric measurements of the patient, or the generated three-dimensional models in order to remotely monitor and track changes to the body of a patient over time and make dynamic adjustments to the patient's medical treatment plan.
1 .- 20 . (canceled)
21 . A computer-implemented method for patient monitoring, the method comprising:
select a weight loss drug from a plurality of weight loss drugs based on a current or future supply chain status;
receiving, from a user device of a patient, a first set of images of the patient captured using a camera of the user device during a first imaging session at a first point in time, wherein the patient is enrolled in a medical treatment plan involving self-administration of a dosage of the selected weight loss drug, and wherein the first set of images of the patient comprises images of various body regions of the patient from multiple angles;
generating a first 3D model of the patient by processing the first set of images of the patient, wherein the first 3D model represents the patient's body during the first imaging session;
generating a user skeleton for the first 3D model based on motion of the patient detected in the first set of images, wherein the user skeleton identifies a location of a joint of the patient, and wherein the user skeleton provides static-over-time reference points for anthropometric measurements;
calculating a first anthropometric measurement for the patient based on the first 3D model and a reference point from the user skeleton, wherein the first anthropometric measurement is associated with the patient's body during the first imaging session;
receiving, from the user device of patient, a second set of images of the patient captured using a camera of the user device during a second imaging session at a second point in time, wherein the second set of images of the patient comprises images of various body regions of the patient from multiple angles, and wherein the second point in time is after the first point in time;
generating a second 3D model of the patient by processing the second set of images of the patient, wherein the second 3D model represents the patient's body during the second imaging session;
mapping the user skeleton to the second 3D model, such that the user skeleton continues to provide static-over-time reference points for anthropometric measurements;
calculating a second anthropometric measurement for the patient based on the second 3D model and the reference point from the user skeleton, wherein the second anthropometric measurement is associated with the patient's body during the second imaging session;
comparing the first anthropometric measurement and the second anthropometric measurement to determine a change in the patient between the first point in time and the second point in time; and
based on the change in the patient, determining an adjusted dosage of the weight loss drug administered in the medical treatment plan.
22 . The computer-implemented method of claim 21 , further comprising:
based on the second 3D model of the patient, generating a predictive 3D model of the patient that models and predicts the patient's body at a future point in time because of continued adherence to the medical treatment plan.
23 . The computer-implemented method of claim 21 , wherein the change in the patient is a reduction in weight of the patient, a reduction in BMI of the patient, or a reduction in waist circumference of the patient.
24 . The computer-implemented method of claim 21 , wherein the first and second set of images of the patient comprise images of the patient in a set of poses.
25 . The computer-implemented method of claim 21 , further comprising:
sending, to the user device of the patient, an electronic message with a behavioral recommendation associated with the medical treatment plan.
26 . The computer-implemented method of claim 21 , further comprising:
receiving information about the patient; and
applying an artificial intelligence system to the information about the patient to select the weight loss drug and generate the medical treatment plan for the patient.
27 . The computer-implemented method of claim 21 , wherein the patient participates in a virtual proctoring session between the first point in time and the second point in time, and wherein the virtual proctoring session is part of a series of virtual proctoring sessions scheduled for the patient as periodic check-ins under the medical treatment plan.
28 . The computer-implemented method of claim 21 , further comprising:
generating an electronic prescription with the adjusted dosage of the weight loss drug; and
sending the electronic prescription to a pharmacy.
29 . The computer-implemented method of claim 21 , further comprising:
sending, to the user device of the patient, a message containing a link for attending a virtual proctoring session.
30 . The computer-implemented method of claim 21 , further comprising:
sending, to the user device of the patient, a message indicating the dosage of the weight loss drug has been adjusted.
31 . A system for patient monitoring, the system comprising:
at least one hardware processor; and
a computer-readable, non-transitory storage medium have instructions thereon that, when executed by the at least one hardware processor, cause the system to perform operations comprising:
select a weight loss drug from a plurality of weight loss drugs based on a current or future supply chain status;
receiving, from a user device of a patient, a first set of images of the patient captured using a camera of the user device during a first imaging session at a first point in time, wherein the patient is enrolled in a medical treatment plan involving self-administration of a dosage of the selected weight loss drug, and wherein the first set of images of the patient comprises images of various body regions of the patient from multiple angles;
generating a first 3D model of the patient by processing the first set of images of the patient, wherein the first 3D model represents the patient's body during the first imaging session;
generating a user skeleton for the first 3D model based on motion of the patient detected in the first set of images, wherein the user skeleton identifies a location of a joint of the patient, and wherein the user skeleton provides static-over-time reference points for anthropometric measurements;
calculating a first anthropometric measurement for the patient based on the first 3D model and a reference point from the user skeleton, wherein the first anthropometric measurement is associated with the patient's body during the first imaging session;
receiving, from the user device of patient, a second set of images of the patient captured using a camera of the user device during a second imaging session at a second point in time, wherein the second set of images of the patient comprises images of various body regions of the patient from multiple angles, and wherein the second point in time is after the first point in time;
generating a second 3D model of the patient by processing the second set of images of the patient, wherein the second 3D model represents the patient's body during the second imaging session;
mapping the user skeleton to the second 3D model, such that the user skeleton continues to provide static-over-time reference points for anthropometric measurements;
calculating a second anthropometric measurement for the patient based on the second 3D model and the reference point from the user skeleton, wherein the second anthropometric measurement is associated with the patient's body during the second imaging session;
comparing the first anthropometric measurement and the second anthropometric measurement to determine a change in the patient between the first point in time and the second point in time; and
based on the change in the patient, determining an adjusted dosage of the weight loss drug administered in the medical treatment plan.
32 . The system of claim 31 , wherein the operations further comprise:
based on the second 3D model of the patient, generating a predictive 3D model of the patient that models and predicts the patient's body at a future point in time because of continued adherence to the medical treatment plan.
33 . The system of claim 31 , wherein the change in the patient is a reduction in weight of the patient, a reduction in BMI of the patient, or a reduction in waist circumference of the patient.
34 . The system of claim 31 , wherein the first and second set of images of the patient comprise images of the patient in a set of poses.
35 . The system of claim 31 , wherein the operations further comprise:
sending, to the user device of the patient, an electronic message with a behavioral recommendation associated with the medical treatment plan.
36 . The system of claim 31 , wherein the operations further comprise:
receiving information about the patient; and
applying an artificial intelligence system to the information about the patient to select the weight loss drug and generate the medical treatment plan for the patient.
37 . The system of claim 31 , wherein the patient participates in a virtual proctoring session between the first point in time and the second point in time, and wherein the virtual proctoring session is part of a series of virtual proctoring sessions scheduled for the patient as periodic check-ins under the medical treatment plan.
38 . The system of claim 31 , wherein the operations further comprise:
generating an electronic prescription with the adjusted dosage of the weight loss drug; and
sending the electronic prescription to a pharmacy.
39 . The system of claim 31 , wherein the operations further comprises:
sending, to the user device of the patient, a message containing a link for attending a virtual proctoring session.
40 . The system of claim 31 , wherein the operations further comprises:
sending, to the user device of the patient, a message indicating the dosage of the weight loss drug has been adjusted.