fMRI-Guided VR Motion Selection for Phantom Limb Therapy
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Solution Overview
Problem
Existing virtual reality systems for treating phantom limb pain do not account for individual patient characteristics, leading to suboptimal movement patterns that fail to maximize neural activity in the brain.
Innovation Solution
A magnetic resonance imaging system combined with virtual reality is used to acquire k-space data, reconstruct functional magnetic resonance images, and determine optimal movement patterns for the missing limb by comparing baseline and reference images, utilizing brain symmetry to identify the phantom limb functional region and assigning numerical scores to movement patterns based on neural activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If virtual reality systems are used to treat phantom limb pain with generic movement patterns, then treatment can be provided, but the neural activity in the phantom limb functional region is not maximized
Solution Approach 1:
The system performs preliminary functional MRI scanning to map the patient's specific brain anatomy and identify the phantom limb functional region before designing the virtual reality treatment protocol. This preliminary characterization enables subsequent customization of movement patterns to target the individual's unique neural architecture, resolving the contradiction between providing treatment and maximizing effectiveness through personalization.
Solution Approach 2:
The system uses real-time fMRI feedback during virtual reality treatment sessions to monitor neural activity in the phantom limb functional region. The movement patterns are dynamically adjusted based on this feedback to maximize neural activation, thereby achieving both effective treatment and adaptation to individual patient responses throughout the therapy process.
2Reliability
If functional MRI scanning is performed to identify optimal movement patterns, then neural activity can be maximized, but the complexity of the treatment system increases
Solution Approach 1:
The system merges the functional MRI scanning capability with the virtual reality treatment platform into an integrated system. The MRI scanner and virtual reality environment are combined so that treatment sessions can be delivered within or alongside the MRI environment, allowing simultaneous neural monitoring and stimulus delivery while reducing the need for separate equipment and protocols.
Solution Approach 2:
A computational intermediary system processes the complex data from functional MRI scans and translates it into customized virtual reality movement patterns. This intermediary layer handles the complexity of neural image analysis, feature extraction, and protocol generation, shielding clinicians from the technical complexity while enabling personalized treatment optimization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for the selection of virtual reality motion patterns that effectively stimulate the phantom limb functional region, potentially reducing pain and restructuring neural activity, with the option for sensory stimulation and external virtual reality system integration.
Implementation Method 1
Magnetic Resonance Imaging (MRI) may be used to measure detailed visualizations of the anatomical structure of a subject as well as directly measuring some biochemical reactions within the subject. For example, MRI can be used to measure the Hemodynamic response function within the brain to map neural activity.
Data Source
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AI summary
Disclosed herein is a medical instrument (100) comprising a magnetic resonance imaging system (102) configured for acquiring k-space data (148, 152, 166) of a brain of a subject (118) with a missing limb (128) and a complementary limb (129) and a virtual reality system (122).The execution of machine executable instructions causes a computational system (132) to: identify (210) a complementary limb functional region (156) using functional magnetic resonance imaging and determine (212) a phantom limb functional region (158) in the brain by applying brain symmetry. Execution of the machine executable instructions causes the computational system to perform repetitions of: reconstructing (218) a phantom limb functional magnetic resonance image (168) from the phantom limb k-space data (166) acquired during the display of repetition specific motion patterns of the missing limb using the virtual reality system; and assigning (220) a numerical score (170) to the repetition specific movement pattern by detecting neural activity in the phantom limb functional region. Execution of the machine executable instructions further causes the computational system to construct (224) at least one virtual reality motion sequence (180) of the missing limb by selecting the varied movement parameters using the numerical score.