- Patent Title: Systems and methods for using artificial intelligence and machine learning to detect abnormal heart rhythms of a user performing a treatment plan with an electromechanical machine
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Application No.: US18217235Application Date: 2023-06-30
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Publication No.: US11923065B2Publication Date: 2024-03-05
- Inventor: Joel Rosenberg , Steven Mason
- Applicant: ROM Technologies, Inc.
- Applicant Address: US CT Brookfield
- Assignee: ROM Technologies, Inc.
- Current Assignee: ROM Technologies, Inc.
- Current Assignee Address: US CT Brookfield
- Agency: Dickinson Wright PLLC
- Agent Stephen A. Mason; Jonathan H. Harder
- Main IPC: A63B24/00
- IPC: A63B24/00 ; G16H20/30 ; G16H50/30

Abstract:
Computer-implemented systems, computer-implemented methods, and tangible, non-transitory computer-readable media for detecting abnormal heart rhythms of a user performing treatment plan with an electromechanical machine. The system includes, in one embodiment, an electromechanical machine, one or more sensors, and one or more processing devices. The electromechanical machine is configured to be manipulated by a user while the user is performing a treatment plan. The one or more sensors are configured to determine one or more measurements associated with the user. The one or more processing devices are configured to receive, from the one or more sensors while the user performs the treatment plan, the one or more measurements associated with the user. The one or more processing devices also configured to determine, using one or more machine learning models, a probability that the one or more measurements indicate that the user satisfies a threshold for a condition associated with an abnormal heart rhythm. The one or more processing devices are further configured to perform one or more preventative actions responsive to determining that the one or more measurements indicate the user satisfies the threshold for the condition associated with the abnormal heart rhythm. The one or more preventative actions are determined using the one or more machine learning models.
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