Attention-Bias Modification for Chronic Pain Relief
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Solution Overview
Problem
Current treatments for chronic pain conditions like Rheumatoid Arthritis, Diabetic Neuropathy, and Fibromyalgia face challenges in effectively addressing attentional biases, as existing therapies are often non-targeted, difficult to access, and have low adherence due to the nature of chronic pain, leading to ineffective symptom management.
Innovation Solution
A digital therapeutic treatment using individually-targeted visual stimuli through attention-bias modification training (ABMT) that filters out non-associated stimuli, providing curated sessions to reorient attention away from negative pain-related stimuli and towards neutral or positive ones, enhancing user adherence and symptom reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If in-person behavioral therapies are provided to address attentional biases, then treatment effectiveness may improve, but accessibility and frequency of treatment deteriorate due to difficulty in obtaining frequent access
Solution Approach 1:
The patent creates a digital copy of behavioral therapy through a computing system that delivers ABMT sessions via display devices. The system replicates the therapeutic intervention originally requiring in-person clinician delivery, making it accessible through digital interfaces while maintaining the core therapeutic mechanism of attentional bias modification through curated visual stimuli.
2Loss of energy
If non-personalized stimuli are provided to address attentional biases, then resource consumption is reduced, but treatment effectiveness deteriorates due to lack of targeting individual associations
Solution Approach 1:
The system performs preliminary assessment to identify the user's specific attentional biases and associations with pain-related stimuli before delivering the ABMT intervention. This preliminary characterization allows the system to curate highly targeted visual stimuli that address the individual's specific associations, maximizing treatment effectiveness while avoiding waste on non-relevant stimuli.
Solution Approach 2:
The system dynamically adjusts the parameters of visual stimuli based on the user's identified associations and responses during therapy sessions. By changing stimulus characteristics (selection, presentation timing, duration) according to individual association profiles and real-time performance data, the system optimizes both effectiveness and resource efficiency for each user.
3Ease of operation
If digital therapeutic interventions are provided to patients with chronic pain, then accessibility improves, but adherence deteriorates due to patients' inability to refrain from paying attention to negative stimuli
Solution Approach 1:
The system applies local quality by customizing the therapeutic intervention to match the specific attentional bias patterns of each user. Rather than using a uniform approach, the system tailors the visual stimuli to target the user's particular associations with pain-related concepts, making the intervention more engaging and relevant to their specific experience, thereby improving adherence.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor user responses and performance during ABMT sessions. This feedback is used to adjust subsequent stimulus presentation and provide real-time guidance, helping users successfully complete sessions despite the challenge of attentional biases. The feedback loop reinforces adherence by demonstrating progress and adapting to user needs.
Data Source
AI summary
Presented herein are systems and methods of providing individualized sessions to address chronic pain in users. A computing system may identify a set of stimuli identified by a user as not associated with the pain or the condition of the user. The computing system may present a first visual stimulus associated with the chronic pain of the user and a second visual stimulus neutral to the chronic pain. The computing system may present a visual probe corresponding to one of the first position or the second position to direct the user to interact with the visual probe. The computing system may increase the efficacy of the medication that the user is taking to address the condition.