AI Imaging Alignment Plans for Remote Treatment Positioning
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Solution Overview
Problem
Users often struggle to properly align their bodies with imaging sensors during treatment sessions, especially in remote settings, due to factors like pain, limited mobility, and lack of medical knowledge, which can hinder the effectiveness of treatment plans.
Innovation Solution
An artificial intelligence engine generates alignment plans using machine learning models to adjust the user's body position to bring targeted body parts within the imaging sensor's field of view, based on user data and characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a user performs a treatment plan remotely without direct healthcare professional assistance, then treatment accessibility and convenience are improved, but the ability to properly align the user with the imaging sensor deteriorates
Solution Approach 1:
The system enables self-service alignment by having the user independently position themselves using generated alignment plans without requiring direct healthcare professional assistance. The AI-generated instructions allow the user to autonomously adjust their body position to achieve proper alignment with the imaging sensor.
Solution Approach 2:
The patent replaces the mechanical guidance typically provided by healthcare professionals through manual adjustment with an AI-based system that uses machine learning models to generate digital alignment plans. This substitution allows remote operation while maintaining alignment precision through computational algorithms rather than physical guidance.
2Manufacturing precision
If alignment plans are generated using machine learning models, then alignment accuracy is improved, but system complexity increases
Solution Approach 1:
The machine learning model acts as an intermediary between the raw user data and the final alignment instructions. This intermediary component processes complex patterns in user data and translates them into actionable alignment plans, managing system complexity through a dedicated processing layer that bridges data input and output requirements.
Solution Approach 2:
The system manages complexity by transforming diverse user data parameters into standardized alignment plan parameters. The machine learning model processes various input characteristics and converts them into consistent alignment instructions, simplifying the output while maintaining accuracy despite the complexity of the underlying processing.
3Measurement precision
If the user adjusts their body position to align with the imaging sensor, then data gathering quality is improved, but user comfort and ease of movement deteriorate
Solution Approach 1:
The system performs preliminary action by generating alignment plans in advance that guide the user through the positioning process. These pre-computed instructions prepare the user for the alignment task, providing step-by-step guidance that makes the potentially uncomfortable positioning process more manageable and less confusing.
Solution Approach 2:
The system incorporates feedback mechanisms where the user can indicate discomfort or difficulty in following alignment instructions. This feedback loop allows the system to adapt and provide alternative guidance, balancing the need for precise alignment with the user's comfort and mobility limitations.
Data Source
AI summary
Systems, methods, and computer-readable mediums for generating, by an artificial intelligence engine, one or more alignment plans for aligning a user with an imaging sensor. The method comprises generating one or more machine learning models trained to identify alignment plans. The method also comprises receiving user data and determining that a targeted portion of a body of the user is outside of a field of view of the imaging sensor. The method further comprises generating the one or more alignment plans using the one or more machine learning models. Each of the one or more alignment plans comprises a target location within the field of view of the imaging sensor and one or more elements for adjusting the targeted portion of the body from a first location to the target location. The method also comprises transmitting the one or more alignment plans to a computing device.