System and method for using AI ML and telemedicine to perform bariatric rehabilitation via an electromechanical machine
A computer-implemented system includes one or more processing devices configured to receive attribute data associated with a user, generate, based on at least one of a first bariatric procedure to be performed on the user and a second bariatric procedure already performed on the user, a selected set of the attribute data, determine, based on the selected set of the attribute data, at least one of a first probability of being eligible for the first bariatric procedure to be performed on the user and a second probability of improving a bariatric condition of the user subsequent to the second bariatric procedure being performed on the user, and generate, based on the at least one of the first probability and the second probability, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability, and a treatment apparatus configured for implementation of the treatment plan.
1. A computer-implemented system for controlling a treatment apparatus, the computer-implemented system comprising:
one or more processing devices that
receive attribute data associated with a user,
generate, based on at least one of a first bariatric procedure to be performed on the user and a second bariatric procedure already performed on the user, a selected set of the attribute data,
determine, based on the selected set of the attribute data, at least one of (i) a first probability of being eligible for the first bariatric procedure to be performed on the user and (ii) a second probability of improving a bariatric condition of the user subsequent to the second bariatric procedure being performed on the user, and
generate, based on the at least one of the first probability and the second probability, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability; and
a treatment apparatus, wherein the treatment apparatus (i) implements the treatment plan by controlling, based on the treatment plan, one or more operating parameters of an electromechanical machine of the treatment apparatus, (ii) generates and transmits, to the one or more processing devices, measurement information associated with performance of the treatment plan by the user while the user uses the electromechanical machine, wherein the attribute data includes the measurement information, and (iii) selectively adjusts the one or more operating parameters in response to modifications, by the one or more processing devices, of the treatment plan.
2. The computer-implemented system of claim 1 , wherein the attribute data includes data associated with bariatric health of the user.
3. The computer-implemented system of claim 1 , wherein the one or more processing devices execute an attribute data model, and wherein, to generate the selected set of the attribute data, the attribute model at least one of assigns weights to the attribute data, ranks the attribute data, and filters the attribute data.
4. The computer-implemented system of claim 3 , wherein the one or more processing devices execute a probability model, wherein the probability model determines the at least one of the first probability and the second probability.
5. The computer-implemented system of claim 3 , wherein the one or more processing devices execute a treatment plan model, wherein the treatment plan model generates the treatment plan to modify the at least one of the first probability and the second probability.
6. The computer-implemented system of claim 1 , wherein the one or more processing devices generate, based on the at least one of the first probability and the second probability and the selected set of the attribute data, a recommendation of whether the user should undergo the first bariatric procedure.
7. The computer-implemented system of claim 6 , wherein, subsequent to implementing the treatment plan using the treatment apparatus, the one or more processing devices modify, based on the recommendations, the treatment plan.
8. The computer-implemented system of claim 7 , wherein the one or more processing transmit the modified treatment plan to cause the treatment apparatus to implement at least one modified exercise of the modified treatment plan.
9. The computer-implemented system of claim 1 , wherein, while the user performs the treatment plan, the one or more processing devices initiate a telemedicine session between a computing device of the user and a computing device of a healthcare professional.
10. The computer-implemented system of claim 1 , wherein the attribute data includes data related to comorbid conditions of the user.
11. The computer-implemented system of claim 10 , wherein the one or more processors generate, further based on the data related to the comorbid conditions of the user, the treatment plan.
12. The computer-implemented system of claim 11 , wherein the one or more processors modify, based on the data related to the comorbid conditions of the user, the treatment plan to decrease at least one of (i) a third probability that the comorbid conditions will interfere with the treatment plan and (ii) a fourth probability that the treatment plan will worsen the comorbid conditions.
13. The computer-implemented system of claim 11 , wherein the one or more processors modify, based on the data related to the comorbid conditions of the user, to modify parameters of the treatment apparatus.
14. A method for controlling a treatment apparatus, the method comprising:
at one or more processing devices,
receiving attribute data associated with a user,
generating, based on at least one of a first bariatric procedure to be performed on the user and a second bariatric procedure already performed on the user, a selected set of the attribute data,
determining, based on the selected set of the attribute data, at least one of (i) a first probability of being eligible for the first bariatric procedure to be performed on the user and (ii) a second probability of improving a bariatric condition of the user subsequent to the second bariatric procedure being performed on the user, and
generating, based on the at least one of the first probability and the second probability, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability; and
controlling a treatment apparatus to implement the treatment plan, wherein controlling the treatment apparatus includes (i) controlling, based on the treatment plan, one or more operating parameters of an electromechanical machine of the apparatus, (ii) generating and transmitting, to the one or more processing devices, measurement information associated with performance of the treatment plan by the user while the user uses the electromechanical machine, wherein the attribute data includes the measurement information, and (iii) selectively adjusting the one or more operating parameters of the electromechanical machine in response to modifications, by the one or more processing devices, of the treatment plan.
15. The method of claim 14 , wherein the attribute data includes data associated with bariatric health of the user.
16. The method of claim 14 , further comprising, using the one or more processing devices, executing an attribute data model, wherein generating the selected set of the attribute data includes at least one of assigning weights to the attribute data, ranking the attribute data, and filtering the attribute data.
17. The method of claim 16 , further comprising, using the one or more processing devices, executing a probability model to determine the at least one of the first probability and the second probability.
18. The method of claim 16 , further comprising, using the one or more processing devices, executing a treatment plan model to generate the treatment plan to modify the at least one of the first probability and the second probability.
19. The method of claim 14 , further comprising, using the one or more processing devices, generating, based on the at least one of the first probability and the second probability and the selected set of the attribute data, a recommendation of whether the user should undergo the first bariatric procedure.
20. The method of claim 19 , further comprising, subsequent to implementing the treatment plan using the treatment apparatus and using the one or more processing devices, modifying the recommendations based on the treatment plan.
21. The method of claim 20 , further comprising, using the one or more processing devices, transmitting the modified treatment plan to cause the treatment apparatus to implement at least one modified exercise of the modified treatment plan.
22. The method of claim 14 , further comprising, while the user performs the treatment plan, initiating a telemedicine session between a computing device of the user and a computing device of a healthcare professional.
23. The method of claim 14 , wherein the attribute data includes data related to comorbid conditions of the user.
24. The method of claim 23 , further comprising, using the one or more processors and further based on the data related to the comorbid conditions of the user, generating the treatment plan.
25. The method of claim 24 , further comprising, using the one or more processors and based on the data related to the comorbid conditions of the user, modifying the treatment plan to decrease at least one of (i) a third probability that the comorbid conditions will interfere with the treatment plan and (ii) a fourth probability that the treatment plan will worsen the comorbid conditions.
26. The method of claim 24 , further comprising, using the one or more processors and based on the data related to the comorbid conditions of the user, modifying parameters of the treatment apparatus.