fMRI-Guided VR Motion Selection for Phantom Limb Neural Stimulation

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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 effectively stimulate neural activity in the brain.

Innovation Solution

A magnetic resonance imaging system combined with virtual reality is used to acquire k-space data from a subject's brain with a missing limb and its symmetrical complimentary limb, reconstructing functional magnetic resonance images to identify and stimulate the phantom limb functional region, and determine movement patterns that maximize neural activity.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If virtual reality systems are used to treat phantom limb pain without considering individual patient characteristics, then the treatment can be applied broadly, but the effectiveness in stimulating neural activity is suboptimal

Engineering Contradiction:

Improveindividual customizationVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary functional MRI scanning to identify and map the patient's specific phantom limb functional region in the brain before designing the virtual reality treatment protocol. This preliminary characterization enables subsequent customization of movement patterns tailored to each patient's neural anatomy, resolving the contradiction between individual adaptability and system complexity by preparing patient-specific parameters in advance.

Inventive Principle:

Principle #10Preliminary action

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 measured neural responses, creating a closed-loop system that optimizes treatment effectiveness for each individual patient while managing complexity through automated feedback-driven adaptation.

Inventive Principle:

Principle #23Feedback

2Measurement precision

If movement patterns are selected without empirical determination based on patient characteristics, then the treatment protocol is simpler to implement, but the neural response optimization is insufficient

Engineering Contradiction:

Improveneural activity measurementVSAvoidtreatment setup time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system automatically determines optimal movement patterns by analyzing the patient's own neural responses during brief fMRI measurements. The computational algorithms self-calibrate to each patient's characteristics without requiring extensive manual setup or expert intervention, reducing treatment setup time while maintaining precise neural activity measurement and optimization.

Inventive Principle:

Principle #25Self-service

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 significantly stimulate the phantom limb functional region, potentially reducing pain and aiding in the retraining of neurons to cope with limb loss.

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

Methodology Applied

Scientific EffectMagnetic resonance imaging: Magnetic Field

Implementation Method 2

MRI can be used to measure the Hemodynamic response function within the brain to map neural activity

Methodology Applied

Scientific EffectHemodynamic response:

Data Source

PatentUS12569159B2Magnetic resonance guided selection of virtual reality motion patterns for phantom limbs

Publication Date: 2026.03.10 KONINKLIJKE PHILIPS NV

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.