Machine Learning Control for Personalized Rehab Exercise Devices

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Solution Overview

Problem

Conventional electromechanical devices for prehabilitation and exercise lack effective monitoring and control mechanisms, leading to potential over-exertion, improper form, and sub-optimal exercise sessions that may reinjure users or increase recovery time, and they fail to generate personalized and efficient prehabilitation plans.

Innovation Solution

A system utilizing machine learning to generate personalized prehabilitation plans and control electromechanical devices through real-time monitoring and adjustment of parameters, including modes, resistance, and configurations based on user data and treatment plans, enabling real-time physician oversight.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional electromechanical devices are used for prehabilitation and exercise, then basic exercise functionality is provided, but effective monitoring and control mechanisms are lacking leading to potential over-exertion and improper form

Engineering Contradiction:

Improvesafety of exercise sessionsVSAvoidmonitoring and control mechanisms

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system continuously monitors user performance data during exercise sessions and provides real-time feedback through the control system. This feedback mechanism enables dynamic adjustment of exercise parameters to prevent over-exertion and improper form, directly addressing the safety concerns of conventional devices without requiring complex manual intervention.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The electromechanical device performs self-monitoring and self-adjustment of exercise parameters based on prehabilitation plan specifications. The device automatically regulates resistance, speed, and range of motion according to the personalized plan, eliminating the need for constant professional supervision while maintaining safety and effectiveness.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If conventional electromechanical devices are used, then exercise sessions can be performed, but they fail to generate personalized and efficient prehabilitation plans

Engineering Contradiction:

Improvepersonalization of prehabilitation plansVSAvoidplan generation system

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system generates personalized prehabilitation plans in advance based on user-specific factors including injury type, surgical procedure, health history, and functional limitations. These pre-planned exercise protocols are prepared before the user begins exercise sessions, enabling immediate customization without requiring complex real-time decision-making during exercise.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The prehabilitation plan includes specific parameters for each exercise such as resistance levels, speed, range of motion, and duration that are customized to the user's needs. The system varies these parameters across different exercise sessions to progressively challenge the user while remaining within safe limits, providing personalization without excessive complexity.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If real-time monitoring and adjustment are implemented, then exercise safety and efficiency are improved, but system complexity increases

Engineering Contradiction:

Improveefficiency of prehabilitationVSAvoidcontrol system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The control system serves multiple functions: it stores prehabilitation plans, monitors exercise performance in real-time, provides feedback, and adjusts exercise parameters automatically. By consolidating these functions into a single integrated system, the patent achieves high productivity and safety without proportionally increasing overall system complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12558594B2Systems and methods for using machine learning to control an electromechanical device used for prehabilitation, rehabilitation, and/or exercise

Publication Date: 2026.02.24 ROM TECH INC

AI summary

Systems, methods, and computer-readable mediums for operating an electromechanical device are disclosed. The system includes, in one example, the electromechanical device, a patient portal, and a computing device. The computing device is configured to receive user data relating to a user, and receive treatment data relating to treatment plans and outcomes. The computing device is also configured to generate a prehabilitation plan by using a machine learning model to process the user data and the treatment data. The computing device is further configured to select, for the electromechanical device, an electromechanical device configuration that enables exercises of the prehabilitation plan to be performed by the user such that performance improves an area of the user's body. The computing device is also configured to enable the electromechanical device to implement the electromechanical device configuration.