US 2026/0229333 A1 · SYSTEMS AND METHODS FOR USING AI/ML TO ENABLE, VIA AI-DRIVEN INTERVENTIONS, THE EARLY DETECTION OF PATIENTS DEEMED HIGH RISK DUE TO SLOW PROGRESSION IN REHABILITATION

Abstract

Systems, methods, and computer-readable media are disclosed relating to the control of electromechanical devices. An artificial intelligence (AI) engine may be trained with machine learning techniques on data that includes one or more operational parameters of a treatment apparatus that includes one or more electromechanical elements. Based on user data, some of which may be from the treatment apparatus, the AI engine may predict a probability that a user may not have a successful rehabilitation treatment. A modified treatment plan may be generated, and an operational parameter of the treatment apparatus may be controlled e.g. by using computer instructions to cause the treatment apparatus to operate in a certain manner for further rehabilitation treatment. Thus, real-world physical effects on a treatment apparatus may be due to using AI techniques that determine particular modifications to a treatment plan, which may also increase success chances for user rehabilitation in a therapeutic environment.

Claims20

Dependent claims

A computer-implemented method comprising:

receiving, from one or more of an electromechanical machine, a sensor, and a computing device, data associated with a user who uses the electromechanical machine to perform a treatment plan;
based on the data, predicting, using an artificial intelligence engine, a risk probability that satisfies a risk probability threshold level associated with a regression or an undesired progression in rehabilitation;
based on the risk probability satisfying the risk probability threshold level, generating a modified treatment plan that comprises information associated with modification of one or more operating parameters of the electromechanical machine;
and
based on the modified treatment plan, causing operation of the electromechanical machine to be controlled.

2 more elements

A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause one or more processing devices to:

receive, from one or more of an electromechanical machine, a sensor, and a computing device, data associated with a user who uses the electromechanical machine to perform a treatment plan;
based on the data, predicting, use an artificial intelligence engine, a risk probability that satisfies a risk probability threshold level associated with a regression or an undesired progression in rehabilitation;
based on the risk probability satisfying the risk probability threshold level, generate a modified treatment plan that comprises information associated with modification of one or more operating parameters of the electromechanical machine;
and
based on the modified treatment plan, cause operation of the electromechanical machine to be controlled.

2 more elements

A system comprising:

one or more memory devices storing instructions;
and
one or more processing devices communicatively coupled to the one or more memory devices, wherein the one or more processing devices execute the instructions to:
receive, from one or more of an electromechanical machine, a sensor, and a computing device, data associated with a user who uses the electromechanical machine to perform a treatment plan;
based on the data, predicting, use an artificial intelligence engine, a risk probability that satisfies a risk probability threshold level associated with a regression or an undesired progression in rehabilitation;
based on the risk probability satisfying the risk probability threshold level, generate a modified treatment plan that comprises information associated with modification of one or more operating parameters of the electromechanical machine;
and
based on the modified treatment plan, cause operation of the electromechanical machine to be controlled.

5 more elements

Dependencies are inferred from the claim text.

Facts

Application

19/435,021Filed 29 Dec 2025

Priority

3 Oct 2019

Published

6 Aug 2026

Term ends

Not estimatedThe source records don’t support an estimate.

Classification15 codes

G16H 20/10
ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient…:…
G06F 3/048
Input arrangements or combined input and output arrangements for interaction between user and computer: interaction techniques based on graphical…
G06N 3/045
Architecture, e.g. interconnection topology: combinations of networks
G06N 3/08
Neural networks: learning methods

Family

Application62/910,232Us provisional application · filed 3 Oct 2019

Application17/021,895Continuation in part · filed 15 Sep 2020

Application17/147,295Continuation · filed 12 Jan 2021

Application17/397,385Continuation · filed 9 Aug 2021

Application19/075,257Continuation in part · filed 10 Mar 2025

Application63/820,697Us provisional application · filed 9 Jun 2025

Application63/860,657Us provisional application · filed 8 Aug 2025

Application19/435,021Continuation in part

Application19/075,257Continuation

Application17/147,295Continuation in part

US 11,071,597 B2Related patent

US 11,087,865 B2Related patent

US 12,249,410 B2Related patent

US 2021/0100628 A1Published application

US 2021/0134419 A1Published application

US 2021/0366587 A1Published application

US 2025/0210173 A1Published application

US 2026/0229333 A1This patent

From the US filing history. Foreign family members aren’t listed.

Systems and methods for using ai/ml to enable, via ai-driven interventions, the early detection of patients deemed high risk due to slow progression in rehabilitation

Life of this patent

Systems and methods for using ai/ml to enable, via ai-driven interventions, the early detection of patients deemed high risk due to slow progression in rehabilitation

Life of this patent

Abstract

Claims20