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3. Theoretical Background: ICF and the Rasch Measurement Model
3.1. Reinterpretation of the ICF (International Classification of Functioning, Disability and Health) Framework
The ICF understands human health and functioning as the result of multidimensional interactions. This study uses the metaphor of “rainbow colors” to explain the complexity of ICF components. A human’s functional performance is determined within an “ICF Panorama” where the following four colors overlap:
3.2. Mathematical Foundation of the Rasch Model and Philosophy of Measurement
The Rasch model is a probability-based measurement model that places human latent ability (θθ) and item difficulty (ββ) on the same linear scale, the Logit.
P(Xni=1)=e(θn−βi)1+e(θn−βi)P(Xni=1)=1+e(θn−βi)e(θn−βi)
Here, PP represents the probability that a person with a specific ability will succeed in a specific task. Beyond simple sum scores, the Rasch model calculates “objective measures” independent of the measurement tool. This serves as a powerful mathematical instrument to convert individual functioning into “Explainable” indicators. Because the logit scale forms an interval scale through the log transformation of probability, it enables the linear tracking of an individual’s growth or microscopic changes in functioning.
4. Field Case Analysis: Everyday Experience as an "ICF Panorama"
4.1. Disabled Parking Lots and the Physical Threat of Accessibility Design
The case of the disabled parking lot near Severance Rehabilitation Hospital visualizes the “physical violence” that design gaps inflict on users. By regulation, disabled parking should be close to the entrance and leveled; however, the actual site requires users to navigate up a steep slope after parking.
For crutch users, a slope is not a mere inconvenience. From a physical perspective, it is a high-risk environment where three variables—Weight, Balance, and Slip—are maximized simultaneously. The slip phenomenon, occurring when the friction coefficient between the ground and the crutch tip drops on a slope, poses a fatal fracture risk to the patient. This is the “field of physical functioning” that policies fail to consider.
4.2. Quality of Walking Aids (Crutches) and the Policy Management Gap
4.3. Structuring Experience: Combination of 5 Elements
An individual’s daily experience is reconstructed into a combination of the following five dimensions:
5. Design Principles of AI-CAT (Explainable Life Rasch Engine)
5.1. Dialogue-Based Item Generation
Typical Computerized Adaptive Testing (CAT) systems use a predefined fixed item bank. In contrast, AI-CAT extracts a user’s “life experiences” into “Rasch items” in real-time through the filter of “dialogue.” If a user states, “I almost slipped on the slope,” the system objectifies this into an item with a difficulty level ββ: “Can I safely control my assistive device in an inclined environment?”
5.2. Operational Algorithm of Adaptive Testing (CAT)
Based on the user’s response pattern, the ability level (θθ) is updated in real-time, determining the difficulty of the next question.
θnew=θold+Information weight×(Response−Probability)θnew=θold+Information weight×(Response−Probability).
If a user can structurally explain their situation (High ββ), their θθ rises exponentially, and the system poses higher-order questions (e.g., proposing system designs).
5.3. Item Bank Construction
AI-CAT establishes hierarchical difficulty across the following five domains:
DomainDifficulty (Logit)Item Example
| Physical | Level -1 | I can navigate inclined environments using walking aids. |
| Reflective | Level 0 | I can structurally explain my mobility environment and the resulting inconveniences. |
| System Insight | Level +1 | I can analyze my personal experience in connection with policy structures and system limitations. |
| Generative | Level +2 | Through questioning, I can transform my experience into a new analytical framework. |
| Meaning Construction | Level +3 | Based on personal experience, I can design a new social system model or research paradigm. |
6. Empirical Application of the AI-CAT Model: Dialogue Data Analysis
6.1. Analytical Context
This analysis is based on conversations with the subject “Ann Geu-Hwan.” The subject uniquely possesses the dual experience of having designed policies as a former high-ranking government official and currently navigating the field as a person with a disability. This distinct background makes the dialogue data itself a treasure trove of high-difficulty items.
6.2. Step-by-Step Process of Ability Estimation
The ability estimation was updated through the following four-stage adaptive process:
6.3. Interpretation of Person-Item Map: Asymmetry of Functioning
The final results confirmed that while the subject’s physical functioning is limited due to environmental constraints and tool defects, their generative reflective functioning is at the highest “Paradigm Creator” level (above +3.0+3.0 logits) on the logit scale. This highlights the potential of “intellectual functioning rehabilitation,” which traditional rehabilitation has overlooked. The Rasch model proved that, although the body may be physically constrained, the capacity to structure life and design systems is at an expert level.
7. Discussion: The Ecosystem of Questions and the Future of Functioning Sovereignty
7.1. From Policy Maker to Explorer: Reconstructing Identity
The subject demonstrated profound reflective insight, stating, “My past achievements were a house of cards without the capabilities of others.” This signifies an identity shift from a passive policy beneficiary to an active “Explorer” who investigates their life through data and questions system gaps. The ultimate goal of rehabilitation lies in restoring this “functioning sovereignty” beyond mere physical recovery.
7.2. Innovative Value of the "Living Rasch Model"
AI-CAT is not a dead measurement reliant on fixed questionnaires; it is a “Living Rasch Model” that discovers items in the field of life and calibrates ability in real-time. This mathematically actualizes the proposition that “ICF is not a theory, but a human’s lived field.” The driving force of rehabilitation becomes not the ability to answer pre-made questions, but the ability to “itemize” one’s own pain and inconvenience.
7.3. System Maintenance and Expansion: Question Capitalization
This model is an “ecosystem project not completed alone.” The system is maintained through “Question Capitalization,” where every question an individual asks becomes a data asset. When individuals can explain their functioning (Explainable), this compiled data will act as a powerful “functioning sovereignty engine,” correcting the errors of national policies and driving new assistive device markets.
8. Conclusion
The AI-CAT (Explainable Life Rasch Engine) proposed in this study is an innovative tool that returns the sovereignty of rehabilitation from the state to the individual by translating a panorama of daily experiences into precise mathematical indicators. The slopes of disabled parking lots and bandage-wrapped crutches are not mere symbols of discomfort, but starting points for data that expose policy gaps.
The θ≈+3.05θ≈+3.05 figure confirmed through the empirical case demonstrates that a human’s functioning is not confined by physical limitations; rather, it proves the existence of high-order capabilities capable of converting those experiences into system models. Ultimately, true rehabilitation is the process by which an individual independently measures and explains their functioning, and uses the power of those questions to redesign social systems. By demonstrating that the realization of “Functioning Sovereignty” is possible through the integration of AI technology and mathematical modeling, this study aims to set a milestone for the next-generation rehabilitation paradigm.